diff --git a/_static/electricity_generation_fossil_nuclear.png b/_static/electricity_generation_fossil_nuclear.png new file mode 100644 index 0000000..2a96d9a Binary files /dev/null and b/_static/electricity_generation_fossil_nuclear.png differ diff --git a/_static/electricity_generation_renewable.png b/_static/electricity_generation_renewable.png new file mode 100644 index 0000000..a298a9d Binary files /dev/null and b/_static/electricity_generation_renewable.png differ diff --git a/_static/message-globiom.bib b/_static/message-globiom.bib deleted file mode 100644 index 5e962e2..0000000 --- a/_static/message-globiom.bib +++ /dev/null @@ -1,29 +0,0 @@ -@techreport{message_globiom_2016, - author = {Krey, V. and Havlik, P. and Fricko, O. and Zilliacus, J. and Gidden, M. and Strubegger, M. and Kartasasmita, G. and Ermolieva, T. and Forsell, N. and Gusti, M. and Johnson, N. and Kindermann, G. and Kolp, P. and McCollum, D. L. and Pachauri, S. and Rao, S. and Rogelj, J. and Valin, H. and Obersteiner, M. and Riahi, K.}, - title = {MESSAGE-GLOBIOM 1.0 Documentation}, - institution = {International Institute for Applied Systems Analysis (IIASA)}, - url = {http://data.ene.iiasa.ac.at/message-globiom/}, - year = {2016} -} - -@article{fricko_havlik_2017, - author = {Fricko, O. and Havlik, P. and Rogelj, J. and Klimont, Z. and Gusti, M. and Johnson, N. and Kolp, P. and Strubegger, M. and Valin, H. and Amann, M. and Ermolieva, T. and Forsell, N. and Herrero, M. and Heyes, C. and Kindermann, G. and Krey, V. and McCollum, D. L. and Obersteiner, M. and Pachauri, S. and Rao, S. and Schmid, E. and Schoepp, W. and Riahi, K.}, - title = {The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century}, - journal = {Global Environmental Change}, - volume = "42", - number = "", - pages = "251 - 267", - year = "2017", - issn = "0959-3780", - doi = "http://dx.doi.org/10.1016/j.gloenvcha.2016.06.004", -} - -@article{huppmann_2019_MESSAGEix, - author = {Huppmann, Daniel and Gidden, Matthew and Fricko, Oliver and Kolp, Peter and Orthofer, Clara and Pimmer, Michael and Kushin, Nikolay and Vinca, Adriano and Mastrucci, Alessio and Riahi, Keywan and Krey, Volker}, - title = {{The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp): An open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development}}, - journal = {Environmental Modelling \& Software}, - volume = {112}, - pages = {143-156}, - doi = {https://doi.org/10.1016/j.envsoft.2018.11.012}, - year = {2019} -} diff --git a/annex/index.rst b/annex/index.rst index cc5464a..0fa1bab 100755 --- a/annex/index.rst +++ b/annex/index.rst @@ -1,20 +1,7 @@ Annex: mathematical formulation ******************************* -This Annex provides a description of the mathematical formulation of MESSAGE-GLOBIOM and its modules. - -Note that the “MESSAGE V” module implementation was superseded by the generalized MESSAGEix energy model framework. +This mathematical formulation of MESSAGE-GLOBIOM relies on the generalized MESSAGEix energy model framework. See the :ref:`MESSAGEix documentation ` for a complete description of its formulation. -Although it is not in active use, the older MESSAGE V formulation is preserved here for reference. - -.. toctree:: - :maxdepth: 1 - - macro - message/index - - -Extra pages -=========== - -See :doc:`/_extra/index` for text that (as of 2020-03-05) is omitted from the main contents. +The equation system of the older MESSAGE V implementation can be found in the `2017 release +`_ of this documentation. diff --git a/annex/macro.rst b/annex/macro.rst deleted file mode 100755 index 062fd65..0000000 --- a/annex/macro.rst +++ /dev/null @@ -1,94 +0,0 @@ -.. _annex_macro: - -MACRO -===== - -MACRO is based on the macro-economic module of the global energy-economy-climate model Global 2100 :cite:`manne_buying_1992`, a predecesor of the `MERGE `_ model. The original soft-linkage between MACRO and MESSAGE has been described in :cite:`messner_messagemacro:_2000`, but several adjustments have been made compared to this original implementation. The description below builds to a certain degree on these two publications, but deviates in some places as discussed in the following paragraphs. It is worthwhile mentioning that MACRO as used with MESSAGE has similar origins as the MACRO module of MARKAL-MACRO :cite:`loulou_markal-macro_2004` with the exception of being soft-linked rather than hard-linked to the energy systems part of the model. - -On the one hand, while the version of MACRO described in :cite:`messner_messagemacro:_2000` like the MACRO module of Global 2100 operated at the level of electric and non-electric energy demands in the production function, the present version of MACRO operates at the level of the six commercial useful energy demands represented in MESSAGE (:ref:`demand`). This change was made in response to electrification becoming a tangible option for the transport sector with the introduction of electric cars over the past decade. Previously (and as described in :cite:`messner_messagemacro:_2000`), the electric useful energy demands in MESSAGE had been mapped to electric demand in MACRO and the thermal useful energy demands, non-energy feedstock and transport demands in MESSAGE had been mapped to non-electric demand in MACRO. - -On the other hand, as a result of switching the implementation of `MESSAGE to GAMS `_, the iterative information exchange between the two models is now handled within GAMS. This accelerates the iteration process considerably, because the solution of the previous iteration is kept in memory and can serve as a starting point for the next iteration. - -Finally, the parameterization of MACRO has changed in a specific way. As mentioned, the model's most important input parameters are the projected growth rates of total labor, i.e., the combined effect of labor force and labor productivity growth (note that labor supply growth is also referred to as reference or potential GDP growth) and the annual rates of reference energy intensity reductions, i.e. the so-called autonomous energy efficiecy improvement (AEEI) coefficients. In all recent applications of MACRO, including the Shared Socio-economic Pathways (SSPs), these are calibrated to be consistent with the developments in a MESSAGE scenario. In practice, this happens by running MACRO and adjusting the potential GDP growth rates and the AEEI coefficients on a sectoral basis until MACRO does not produce an energy demand response and GDP feedback compared to the MESSAGE scenario that it is calibrated to. - -MACRO parameterization ----------------------- - -Initial conditions -~~~~~~~~~~~~~~~~~~ -Total capital :math:`K_{r, y=0}` in the base year is derived by multiplying base year GDP with the capital-to-GDP ratio :math:`kgdp`. - -.. math:: K_{y=0, r} = kgdp \cdot GDP_{r, y=0} - -Similarly investments :math:`I_{r, y=0}` and consumpiton :math:`C_{r, y=0}` in the base year are derived from base year GDP, capital value share and depriciation rate. - -.. math:: I_{y=0, r} = K_{y=0, r} \cdot (grow_{r, y=0} + depr_r) -.. math:: C_{y=0, r} = GDP_{r, y=0} - I_{y=0, r} - -Total production :math:`Y_{y=0, r}` in the base year then follows as total GDP plus energy system costs (estimation based on MESSAGE): - -.. math:: Y_{y=0, r} = GDP_{r, y=0} + total\_cost_{r, y=0} - -The production function coefficients for capital, labor :math:`a_r` and energy :math:`b_{r, s}` are calibrated from the first-order optimality condition, i.e. -:math:`b_{r, s}` from :math:`\frac{\partial Y}{\partial NEWENE_{r,s}} = p_{r,s}^{ref}` and :math:`a_r` by inserting :math:`b_r` back into the production function, -setting the labor force index in the base year to 1 (numeraire) and solving for :math:`a_r` :cite:`manne_buying_1992`. - -.. math:: b_{r,s} = p_{r,s}^{ref} \cdot \left( \frac{Y_{y=0, r}}{{PHYSENE}_{r, s, y=0}} \right)^{\rho_r - 1} - -.. math:: a_r = Y_{y=0, r}^{\rho_r} - \sum_s b_{r,s} \cdot \frac{{{PHYSENE}_{r, s, y=0}}^{\rho_r}} {{K_{y=0, r}}^{\rho_r \cdot \alpha_r}} - -Macro-economic parameters -~~~~~~~~~~~~~~~~~~~~~~~~~ -Given that MESSAGE includes (exogenous) energy efficiency improvements in end-use technologies as well as significant potential final-to-useful energy efficiency improvements via fuel switching -(e.g., via electrification of thermal demands and transportation), for the elasticity of substitution between capital-labor and total energy demand :math:`\epsilon_r` in MACRO relatively low values in the range of 0.2 and 0.3 were chosen. The elasticities are region-dependent with developed regions :math:`r \in \{NAM, PAO, WEU\}` assumed to have higher elasticities of 0.3, -economies in transition :math:`r \in \{EEU, FSU\}` intermediate values of 0.25 and developing regions :math:`r \in \{AFR, CPA, LAM, MEA, PAS, SAS\}` the lowest elasticities of 0.2. - -The capital value share parameter :math:`\alpha_r` can be interpreted as the optimal share of capital in total value added :cite:`manne_buying_1992` and is chosen region-dependent -with lower values between 0.24 and 0.28 assumed for developed regions and slightly higher values of 0.3 assumed for economies in transition and developing country regions. - -Calibration -~~~~~~~~~~~ -Via a simple iterative algorithm, MACRO is typically calibrated to an exogenously specified set of regional GDP trajectories and useful energy demand projections from MESSAGE. -To calibrate GDP, after each MACRO run the realized GDP from MACRO and the GDP to be calibrated to are compared and the potential GDP growth rate :math:`{GROW}_{y, r}` used in MACRO is -then adjusted according to the following formula. - -.. math:: {GROW\_corr}_{y, r} = \left( \frac{{GDP\_cal}_{r, y+1}}{{GDP\_cal}_{r, y}} \right)^{\frac{1}{{duration\_period}_{y+1}}} - \left( \frac{{GDP\_MACRO}_{r, y+1}}{{GDP\_MACRO}_{r, y}} \right)^{\frac{1}{{duration\_period}_{y+1}}} - -where :math:`{GDP\_cal}_{r, y, s}` is the set of GDP values that MACRO should be calibrated to. In the next run of MACRO the potential GDP growth rate :math:`{GROW}_{y, r}` is chosen to be - -.. math:: {GROW}_{y, r} = {GROW}_{y, r} + {GROW\_corr}_{y, r} , - -after which the procedure is repeated. Similarly, to calibrate the physical energy demands :math:`{PHYSENE}_{r, y, s}` to ones from MESSAGE, the demand level realized in MACRO and the -desired demand level from a MESSAGE model run are compared and the autonomous energy efficiency improvements (AEEIs) are corrected according to the following equations. - -.. math:: {aeei\_corr}_{r, y, s} = \left( \frac{{PHYSENE}_{r, y+1, s}}{{DEMAND\_cal}_{r, y+1, s}} / \frac{{PHYSENE}_{r, y, s}}{{DEMAND\_cal}_{r, y, s}} \right)^{\frac{1}{{duration\_period}_{y+1}}} - 1 - -.. math:: {aeei}_{r, y, s} = {aeei}_{r, y, s} + {aeei\_corr}_{r, y, s} - -where :math:`{DEMAND\_cal}_{r, y, s}` is the set of demand levels from MESSAGE that MACRO should be calibrated to. - -Given that GDP and demand calibration interact with each other, in practice they are done in an alternating fashion, i.e. after the first MACRO model run, the potential GDP growth rates -are adjusted and in the second run the AEEI coefficients are adjusted. This calibration loop is continued until the correction factors for both the potential GDP growth rates -:math:`{GROW\_corr}_{y, r}` and the AEEI coefficients :math:`{aeei}_{r, y, s}` all stay below :math:`10^{-5}`. - -Iterating between MESSAGE and MACRO ------------------------------------ - -Exchanged parameters -~~~~~~~~~~~~~~~~~~~~ -MESSAGE and MACRO exchange demand levels of the six commercial servcie demand categories represented in MESSAGE, their corresponding prices as well as total energy system costs including -trade effects of energy commodities and carbon permits (if any explicit mititgation effort sharing regime is implemented). - -Convergence criterion -~~~~~~~~~~~~~~~~~~~~~ -The iteration between MESSAGE and MACRO is either stopped after a fixed number of iterations - in case of which the user needs to manually check convergence between the models - or -once the maximum of changes across all energy demand categories and regions (i.e. the convergence criterion) is less than a specified threshold. In both cases the convergence criterion -is typically set to around 1%. - -Constraint on demand response -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -Demand responses from MACRO to MESSAGE can be large if the initial demands are far from the equlibrium demand levels of a specific scenario (e.g., when using demand from a non-climate policy scenario -as the starting point for a stringent climate mitigation scenario that aims at limiting temperature change to 2 degrees C). To avoid oscillations of demands in subsequent MESSAGE-MACRO iterations, a constraint on the maximum permissible demand change between subquent iterations has been introduced which is usually set to 20%. In practical terms this means that the demand response is capped at -20% for each type of :ref:`demand` and for each of the MESSAGE :ref:`spatial`. -However, under specific conditions - typically under stringent climate policy - when price repsonses to small demand adjustments are large, an oscillating behavior between two sets of demand levels -can still occur. In such situations, the constraint on the demand response is reduced further until the changes in demand are less than the convergence criterion mentioned above. diff --git a/annex/message/1_introduction.rst b/annex/message/1_introduction.rst deleted file mode 100644 index 659a287..0000000 --- a/annex/message/1_introduction.rst +++ /dev/null @@ -1,29 +0,0 @@ -1 Introduction -************** - -This part of the document contains the mathematical formulation of MESSAGE as used at IIASA. The so-called matrix generator produces equations according to this formulation, -the input data determine the form these equations actually take. In its general formulation MESSAGE a dynamic linear programming model with a mixed integer option. -This implies that all relations that define the structure of a model are given as linear constraints between continuous variables. The variables of such a model are called -''Columns'', the equations ''Rows''. This nomenclature is derived from the usual notation used to write down linear models: in the shape of a matrix. -The variables (columns) of MESSAGE be grouped into three categories: - -1. Energy flow variables representing an annual energy flow quantity. The unit is usually GWyr for larger regions, -2. Power variables representing the production capacity of a technology (usual unit: GW), and -3. Stock-piles representing the quantity of a fuel being cumulated at a certain point in time (usual unit: GWyr). - -The constraints (rows) generated by MESSAGE can be grouped into the following categories: - -1. Energy flow balances modelling the flow of energy in the energy chain from resource extraction via conversion, transport, distribution up to final utilization, -2. sum or relational constraints limiting aggregate activities on an annual or cumulative basis, either absolute or in relation to other activities, -3. dynamic constraints setting a relation between the activities of two consecutive periods, and -4. counters that are only used for accounting purposes. - -This manual gives the mathematical formulation of MESSAGE. It contains a formalized description of all types of variables and equations that the matrix generator generates. -The reader of this paper is assumed to be familiar with the theory of linear and mixed integer programming. Each of the building stones of MESSAGE handled in a separate chapter, -which is again subdivided into sections on columns and rows. The notation used for the variable and equation names is the same as in the MPS-file. Uppercase letters are used to -indicate predefined identifiers, while lowercase letters represent characters that are chosen by the user or varied over a set of characters. In order to keep the notation simple and -the mathematical description as short as possible the more complex features are omitted from the description of the rows and described in an additional section (see :ref:`specialfeatures`). -Since practically all parameters of MESSAGE can be defined as time series (i.e. change over the planning horizon), the index for the period is often omitted in the formulation -(e.g., for the efficiencies or the plant factors of conversion technologies). - -The names of variables and equations used in this description follow the notation used in the mps and solution files of the problem. For variables and equations related to technologies this is generally \ *name*\ ....rrlllttt, A\ *name*\ ...rrlllttt, or \ *name*\ A...rrlllttt, where *name* is generated from main output level identifier, main input energy form identifier, a user given character, and the main output fuel identifier. A are indicators of related variables or rows like e.g. annual investments or market penetration. For used defined equations and variables the name is supplied by the user. rr denotes the region ('..' for the main region of a multi-region model and for one-regional models). lll denotes the load region (usually this is season index, day index and hour index all indexed feom a-Z). ttt is the model time period, calculated as :math:`year - int(year_0/100)*100`. diff --git a/annex/message/2_conversion_technologies.rst b/annex/message/2_conversion_technologies.rst deleted file mode 100644 index bfda8da..0000000 --- a/annex/message/2_conversion_technologies.rst +++ /dev/null @@ -1,292 +0,0 @@ -.. _annex_convtech: - - -2 Conversion Technologies -========================= - -2.1 Variables -------------- - -Energy conversion technologies, both on the supply and demand side of the energy system, are modelled using two types of variables, that represent - -* the amount of energy converted per year in a period (activity variables) and -* the annually installed capacity in a period (capacity variables). - -.. _activitiesECT: - -2.1.1 Activities of Energy Conversion Technologies -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - zsvd....rrllltt - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`z` - - level identifier of the main output of the technology. The demand level is handled differently to all other levels: Technologies with the main output on this level are defined without load regions. If defined, the input is split into the different load regions. - * - :math:`s` - - main energy input of the technology (supply). If the technology has no input :math:`s` is set to ”.” (e.g., solar technologies), - * - :math:`v` - - additional identifier of the conversion technology (used to distinguish technologies with the same main input and output), - * - :math:`d` - - main energy output of the technology, - * - :math:`rr` - - identifies the sub-region, :math:`rr` as defined in file "regid" or :math:`rr` = :math:`”..”`, if the model has no sub-regions or if the technology is in the main region, - * - :math:`lll` - - identifies the load region, :math:`lll` is :math:`sdp` (season, day, part of day) or :math:`lll` = :math:`”...”`, if the technology is not modelled with load regions, and - * - :math:`ttt` - - identifies the period, :math:`ttt` = :math:`year - int(year_0/100) * 100`. - -The activity variable of an energy conversion technology is an energy flow variable. It represents the annual consumption of this technology of the main input per period or load region. If a technology has no input, the variable represents the annual production of the main output divided by the efficiency. - -If the main output is *not* on the demand level and at least one of the energy carriers consumed or supplied is defined with load regions the technology is defined with load regions. In this case the activity variables are generated separately for each load region, which is indicated by the additional identifier "lll". However, this changes if the production of the technology over the load regions is predefined: one variable is generated for the time step, the distribution to the load regions is given by the definition of the user (e.g., production pattern of solar power-plants or consumption pattern of end-use devices). - -.. _capacititesECT: - -2.1.2 Capacities of Energy Conversion Technologies -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - yzsvd...rr...ttt - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`y` - - identifier for capacity variables. - * - :math:`z` - - identifies the level on that the main energy output of the technology is defined, - * - :math:`s` - - identifier of the main energy input of the technology, - * - :math:`v` - - additional identifier of the conversion technology, - * - :math:`d` - - identifier of the main energy output of the technology, - * - :math:`rr` - - identifier of the model region, - * - :math:`ttt` - - period in that the capacity is buildt. - -The capacity variables are power variables. Technologies can be modelled without capacity variables. In this case no capacity constraints and no dynamic constraints on construction can be included in the model. Capacity variables of energy conversion technologies can be defined as integer variables. - -If a capacity variable is continuous it represents the annual new installations of the technology in period :math:`t`, if it is integer it represents either the annual number of installations of a certain size or the number of installations of :math:`1/\Delta t` times the unit size (depending on the definition; :math:`\Delta t` is the length of period :math:`t` in years). - -The capacity is defined in relation to the main output of the technology. - -2.2 Constraints ---------------- - -These are equations used to calculate relations beween timesteps or between different variables in the model. Partially they are generated automatically, partially they are entirely defined by the user. - -* Utilization of a technology in relation to the capacity actually installed (capacity constraint), -* the activity or annual construction of a technology in a period in relation to the same variable in the previous period (dynamic constraints), -* limit on minimum or maximum total installed capacity of a technology, -* limit on minimum or maximum annual production of a technology modeled with load region, and -* user defined constraints on groups of technologies (activities or capacities). - -.. _capacityconstr: - -2.2.1 Capacity Constraints -~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - czsvd...rrlllttt - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`c` - - identifier for capacity constraints, - * - :math:`z` - - identifies the level on that the main energy output of the technology is defined, - * - :math:`s` - - identifier of the main energy input of the technology, - * - :math:`v` - - additional identifier of the conversion technology, - * - :math:`d` - - identifier of the main energy output of the technology, - * - :math:`rr` - - identifier of the model region, - * - :math:`lll` - - identifier of the load region, and - * - :math:`ttt` - - period in that the capacity is buildt. - -For all conversion technologies modelled with capacity variables the capacity constraints will be generated automatically. If the activity variables exist for each load region separately there will be one capacity constraint per load region. - -Additionally the activity variables of technologies with multiple operation modes (e.g., different fuels) can be linked to the same capacity variable, which allows the optimization to choose the activity variable used with a given capacity. - -**Technologies without Load Regions** - -For technologies without load regions (i.e. technologies, where no input or output is modelled with load regions) the production is related to the total installed capacity by the plant factor. For these technologies the plant factor has to be given as the fraction they actually operate per year. All end-use technologies are modelled in this way. - -.. math:: - \epsilon_{zsvd} \times zsvd....rr...ttt - \sum_{\tau =t-\tau_{zsvd}}^{min(t,\kappa_{zsvd})} \Delta(\tau-1)\times \pi_{zsvd}\times f_i \times f_p \times yzsvd...rr...\tau \leq hc_{zsvd}^t \times \pi_{zsvd} - -**Technologies with Varying Inputs and Outputs** - -Many types of energy conversion technologies do not have fix relations between their inputs and outputs (e.g.: a power plant may use oil or gas as input or can produce electricity and/or heat as output). MESSAGE has the option to link several activity variables of a conversion technology into one capacity constraint. For the additional activities linked to a capacity variable a coefficient defines the maximum power available in relation to one power unit of the main activity. - - -.. math:: - - & \sum_{z\sigma {v}'\delta }\frac{rel_{z\sigma {v}'\delta} ^{zsvd}\times\epsilon_{z\sigma {v}'\delta }\times z\sigma {v}'\delta ....rrlllttt}{\lambda _{lll}} - \\ - & \sum_{\tau=t-\tau_{zsvd}}^{min(t,\kappa_{zsvd})}\Delta \tau \times \pi_{zsvd}\times f_i \times f_p \times yzsvd...rr...\tau \leq hc_{zsvd}^t\times \pi_{zsvd} \qquad \forall {lll} - -The following notation is used in the above equations: - -.. list-table:: - :widths: 20 80 - :header-rows: 0 - - * - :math:`zsvd....rrlllttt` - - activity of conversion technology :math:`zsvd` in region :math:`rr`, period :math:`ttt` and, if defined so, load region :math:`lll` (see section :ref:`activitiesECT`), - * - :math:`yzsvd...rr...ttt` - - capacity variable of conversion technology :math:`zsvd` (see section :ref:`capacititesECT`). - * - :math:`\epsilon_{zsvd}` - - efficiency of technology :math:`zsvd` in converting the main energy input, :math:`s`, into the main energy output, :math:`d`, - * - :math:`\kappa_{zsvd}` - - last period in that technology :math:`zsvd` can be constructed, - * - :math:`\pi_{svd}` - - "plant factor" of technology :math:`zsvd`, having different meaning depending on the type of capacity equation applied, in case the plant life does not coincide with the end of a period it also is adjusted time the technology can be operated in that period, - * - :math:`\Delta \tau` - - length of period :math:`\tau` in years, - * - :math:`\tau_{zsvd}` - - plant life of technology :math:`zsvd` in periods, - * - :math:`hc_{zsvd}^t` - - represents the installations built before the time horizon under consideration, that are still in operation in the first year of period :math:`t`, - * - :math:`f_i` - - is 1. if the capacity variable is continuous, and represents the minimum installed capacity per year (unit size) if the variable is integer, - * - :math:`f_p` - - adjustment factor if the end of the plant life does not coincide with the end of a period (:math:`rest of plant life in period / period length`, - * - :math:`\pi(l_m, svd)` - - share of output in the load region with maximum production, - * - :math:`rel_{\sigma {v}'\delta}^{svd}` - - relative capacity of main output of technology (or operation mode) svd to the capacity of main output of the alternative technology (or operation mode) :math:`\sigma {v}'\delta`, and - * - :math:`\lambda_l` - - length of the load region :math:`l` or the length of the load region with maximum capacity use if the production pattern over the year is fixed or the length of the load region with maximum capacity requirements as fraction of the year. - - -.. _upper_dynamic_constraint_capacity: - -2.2.2 Dynamic Constraints on Activity and Construction Variables -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - Dzsvd...rrlllttt - -The dynamic constraints relate the activity or annual new installations of a technology in a period to the activity or annual construction during the previous period. - -.. math:: - yzsvd...rr...ttt - \gamma _{yzsvd,ttt} \times yzsvd...rr...(ttt-1) \sim g _{yzsvd,ttt} \\ - \sum_{lll} zsvd...rrlllttt - \gamma _{zsvd,ttt} \times \sum_{lll} zsvd...rrlll(ttt-1) \sim g _{zsvd,ttt}, - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`D` - - is :math:`M, L` for upper and lower capacity and :math:`m, l` for upper and lower activity constraints respectively, - * - :math:`\sim` - - is :math:`\leq, \geq` for upper and lower constraints respectively, - * - :math:`\gamma _{yzsvd,t}, \gamma _{zsvd,t}` - - maximum growth rate per period for the construction/operation of technology :math:`zsvd`, - * - :math:`g_{yzsvd,t}` - - initial size (increment) that can be given and which is necessary for the introduction of new technologies that start with zero capacity/activity, - * - :math:`yzsvd...rr...ttt` - - annual new installation of technology :math:`zsvd` in period :math:`ttt`. - * - :math:`zsvd...rrlllttt` - - activity of technology :math:`zsvd` in period :math:`ttt`, and load region lll. - -As described in Keppo and Strubegger (2010 :cite:`keppo_short_2010`) MESSAGE includes so called flexible or soft dynamic constraints to allow for faster diffusion -in case of economically attractive technologies. To operationalize the concept of soft dynamic constraints, a set of :math:`n` dummy variables with index :math:`i`, -:math:`Bzsvd..ti`, multiplied by a corresponding growth factor :math:`(1+\delta y_{zsvd,ti})` are added to the upper dynamic constraint described above. - -.. math:: - a_t = (1+r)^T \times a_{t-1} + \sum_{i=1}^n (1+r_i)^T \times b_{t-1}^i + S - -The maximum value for these dummy variables :math:`b^i` is limited to the activity of the underlying technology :math:`a`, i.e. - -.. math:: - a_t \leq b_t^i \qquad \qquad \forall i. - -Therefore, this new formulation increases the highest allowed growth factor from - -.. math:: - (1+r)^T - -to - -.. math:: - (1+r)^T + \sum_i (1+r_i)^T - -In addition, the objective function value for period :math:`t` is modified by the extra term - - .. math:: - \cdots + \sum_{i=1}^n c_i \times b_t^i - -which adds costs :math:`c_i` per additional growth factor utilized. - -.. _dynamic_constraints: - -2.2.3 Contraints on total installed capacity -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - Izsvd...rr...ttt - -These constaints allow to set upper and/or lower limits on the total installed capacity of a technology at a given point in time. - -.. math:: - \sum_{\tau=t-T}^t yzsvd...rr...\tau \sim M_t - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`T` - - plant life of the technology, - * - :math:`\sim` - - is :math:`\leq or \geq` for lower and ujpper constraints respectively, - * - :math:`M_t` - - maximum or minimum allowed total installed capacity in time step t - -2.2.4 User defined Constraints -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - nname...rrlllttt - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`n` - - may be 'n', 'p', or 'c' for three groups of user defined constraints, - * - :math:`name` - - is a user defined 4-character short name of the constraint. - -Each technology may have entries related to their activity, new installed capacity, or total installed capacity into any of the defined constraints. In multi-region models the constraint is first searched in the region where the entry is defined and then, if not found, in the main-region. With this it is possible to create relations between technologies in different sub-regions. -The main uses for such constraints are to put regional or global constraints on emissions or to relate the production from specific energy carrirer to the total production, e.g.: - -.. math:: - wind\_electricity + solar\_electricity + biomass\_electricity \geq \alpha \times total\_electricity. - -where :math:`total\_electricity` can usualy be taken from the input to the electricity transmission technology. - -2.3 Bounds -~~~~~~~~~~ - -Upper, lower, or fixed bounds may be put on activity or new installed capacity. This is usually very helpful at the beginning of the planning horizon to fit results to reality. In later time steps they may be used to avoid unrealistic behaviour like, e.g., too many new installations of a specific technology per year. diff --git a/annex/message/3_domestic_resources.rst b/annex/message/3_domestic_resources.rst deleted file mode 100644 index 9262c81..0000000 --- a/annex/message/3_domestic_resources.rst +++ /dev/null @@ -1,148 +0,0 @@ -3 Domestic Resources -==================== - -3.1 Variables -------------- - -Extraction of domestic resources is modelled by variables that represent the quantity extracted per year in a period. A subdivision into cost categories (which are called "grades" in the model) can be modelled. - - -.. _resourceextraction: - -3.1.1 Resource Extraction Variables -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - rzfg....rr...ttt - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`r` - - identifies resource extraction variables, - * - :math:`z` - - level on that the resource is defined (usually :math:`= r)`, - * - :math:`f` - - identifier of the resource being extracted, - * - :math:`g` - - grade (also called cost category) of resource :math:`r, g \in \{a, b, c, ...\}`. - * - :math:`rr` - - identifies the region. - * - :math:`ttt` - - identifies the time period. - -The resource variables are energy flow variables and represent the annual rate of extraction of resource :math:`f`. If several grades are defined, one variable per grade is generated (identifier :math:`g` in position 4). - -3.2 Constraints ---------------- - -The overall availability of a resource is limited in the availability constraint per grade, annual resource consumption can be constrained per grade and total. Additionally resource depletion and dynamic resource extraction constraints can be modelled. - - -3.2.1 Total Resource Availability per Grade -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - rzfgg...rr - -Limits the domestic resource available from one cost category (grade) over the whole time horizon. - -.. math:: - \sum_p\sum_t\Delta t\times rzfg....rr...ttt \leq rzfgg...rr - \Delta t_0R_{zfg,0}, - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`rzfgg...rr` - - total amount of resource :math:`f`, cost category :math:`g`, that is available for extraction in a given region :math:`rr`, - * - :math:`rzfg....rr...ttt` - - annual extraction of resource :math:`f`, cost category (grade) :math:`g` in region :math:`rr` and period :math:`ttt`, - * - :math:`\Delta t` - - length of period :math:`t`. - * - :math:`\Delta t_0` - - number of years between the base year and the first model year, and - * - :math:`R_{zfg,0}` - - extraction of resource :math:`r`, grade :math:`g` in the base year. - - -3.2.2 Resource Depletion Constraints -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - rzfgg...rr...ttt - -The extraction of a resource in a period can be constrained in relation to the total amount still existing at the beginning of the period. - -.. math:: - \Delta t \times rzfg....rr...ttt \leq \delta_{fg}^t \left [rzfgg...rr - \Delta t_0R_{rzfg,0} - \sum_{\tau=1}^{t-1} \Delta\tau\times rrzfg...rr...\tau \right ] - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`rzfgg...rr` - - total amount of resource :math:`f`, cost category :math:`g`, that is available for extraction, - * - :math:`rzfg....rr...ttt` - - annual extraction of resource :math:`f`, cost category (grade) :math:`g` and elasticity class :math:`p` in period :math:`t`, - * - :math:`\delta_{fg}^t` - - maximum fraction of resource :math:`f`, cost category :math:`g`, that can be extracted in period :math:`ttt`, - * - :math:`\Delta t` - - length of period :math:`t` in years, - * - :math:`\Delta t_0` - - number of years between the base year and the first model year, and - * - :math:`R_{rzfg,0}` - - extraction of resource :math:`r`, grade :math:`g` in the base year. - - -3.2.4 Maximum Annual Resource Extraction per Grade -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -Limits the domestic resource availability from one cost category per year. - -.. math:: - rzfg....rr...ttt \leq value. - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`rzfg....rr...ttt` - - annual extraction of resource :math:`f`, cost category (grade) :math:`g` in period :math:`ttt`. - -.. _upperdynamicREC: - -3.2.5 Dynamic Resource Extraction Constraints per Grade -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - mrzfg...rr...ttt - -The annual extraction level of a resource in a period can be related to the previous one by a growth parameter and an increment of extraction activity resulting in upper dynamic extraction constraints. For the first period the extraction is related to the activity in the baseyear. - -.. math:: - rzfg....rr...ttt - \gamma_fg \times rzfg....rr...(ttt-1) \leq g_{ft}^0, - -where - -.. list-table:: - :widths: 60 110 - :header-rows: 0 - - * - :math:`m` - - is m or l, indicating upper and lower constraints respectively (lower limits are generally not used), - * - :math:`\gamma_{ft}^0` - - maximum growth rate for the extraction of resource :math:`f` between period :math:`ttt − 1` and :math:`ttt`, - * - :math:`g_{ft}^0` - - annual increment of the extraction of resource :math:`f` in period :math:`ttt` (must be > 0 if the resource (grade) is not extracted in the base year), and - * - :math:`rzfg....rr...ttt` - - annual extraction of resource :math:`f`, cost category (grade) :math:`g` in period :math:`ttt`. diff --git a/annex/message/4_energy_flows.rst b/annex/message/4_energy_flows.rst deleted file mode 100644 index 213b0a9..0000000 --- a/annex/message/4_energy_flows.rst +++ /dev/null @@ -1,118 +0,0 @@ -4 Energy flows -============== - -.. _enebal: - -4.1 Balance Equations ---------------------- - -Energy flows are modelled by linking the activity variables of the different conversion, resource extraction technologies and demands in balance constraints. These constraints ensure that only the amounts of energy available are consumed. There are no further variables required to model energy flows. - -Energy demands are also modelled as part of a balance constraint: the right hand side defines the amount to be supplied by the technologies in this constraint. - -The description of the energy flow constraints in MESSAGE is given for the following set of level identifiers: - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`u` - - Useful energy (demand level), - * - :math:`f` - - Final energy (after transmission and distribution), - * - :math:`x` - - Secondary energy, - * - :math:`a` - - Primary energy, and - * - :math:`r` - - Energy resources. - -The first level in the above list gives it a special meaning (see section :ref:`activitiesECT`). Clearly any other combination of identifiers is also possible. - -Another exception is a level labelled :math:`q`, this letter is reserved for stock piles (see section :ref:`stockpiles`). - -**IMPORTANT:** Generally central production systems should not deliver to the first (demand) level. In this case the production of the system would be forced to follow the demand pattern. - -4.1.1 Demand Constraints -~~~~~~~~~~~~~~~~~~~~~~~~ -.. math:: - - zd......rr...ttt - -.. math:: - \sum_{sv} \epsilon_{zsvd} \times zsvd....rr...ttt + \sum_{sv} \beta_{zsv\delta}^d \times zsv\delta....rr...ttt \geq D_{drt} - -where - -.. list-table:: - :widths: 60 110 - :header-rows: 0 - - * - :math:`zd......rr...ttt` - - annual demand equation for :math:`d` in region :math:`rr` and period :math:`ttt`, - * - :math:`zsvd....rr...ttt` - - activity of end-use technology :math:`zsvd` in region :math:`rr` and period :math:`ttt` (see section :ref:`activitiesECT`), - * - :math:`\epsilon _{zsvd}` - - efficiency of end-use technology :math:`zsvd` in converting :math:`s` to :math:`d`, - * - :math:`\beta _{zsv\delta}^d` - - efficiency of end-use technology :math:`zsvd` in producing by-product :math:`d` from :math:`s` (:math:`\delta` is the main output of the technology), and - * - :math:`D_{drt}` - - annual demand for :math:`d` in region :math:`rr` and period :math:`ttt`. - - -The first level, usually labelled 'demand level', has a special feature. This is related to the fact that useful energy is usually produced on-site, e.g., space heat is produced by a central heating system, and the load variations over the year are all covered by this one system. Thus, an allocation of production technologies to the different areas of the load curve, like the model would set it up according to the relation between investment and operating costs would ignore the fact that these systems are not located in the same place and are not connected to each other. MESSAGE represents the end-use technologies by one variable per period that produces the required useful energy in the load pattern needed and requires the inputs in the same pattern. For special technologies like, e.g., night storage heating systems, this pattern can be changed to represent the internal storage capability of the system. - -Each energy form on any level can have an external demand. In this case the demand is given as right hand side to the balance equation (see section :ref:`enebal`). If the energy carrier is modelled with load regions, the right hand sides are given for each load region. If no load region pattern is defined, the demand is assumed to be a base load demand. - -.. _distbal: - -4.1.2 Other Balances -~~~~~~~~~~~~~~~~~~~~ - -These constraint match the consumption of a specific energy form with the production of this energy form on any of the defined energy levels. They are generated for each load region, if the energy form is modelled with load regions. - -.. math:: - - \sum_{sv} \epsilon_{zsve} \times zsve....rrlllttt + \sum_{sv} \beta_{zsv \kappa }^e \times zsv \kappa ....rrlllttt - \\ - \sum_{zvd} zevd....rrlllttt - \sum_{zkvd} \beta_{z \kappa vd}^e \times z \kappa vd....rrlllttt \geq 0 - -where - -.. list-table:: - :widths: 60 110 - :header-rows: 0 - - * - :math:`zsve....rrlllttt` - - activity of the technology producing energy form :math:`e` in regions :math:`rr`, load region :math:`lll` and period :math:`ttt` (see section :ref:`activitiesECT`), - * - :math:`\epsilon _{zsve}` - - efficiency of technology :math:`zsve` in producing :math:`s`, - * - :math:`zevd....rrlllttt` - - activity of the technology :math:`zevd` consuming energy form :math:`e` in region :math:`rr` and period :math:`ttt`, - * - :math:`\beta_{zsv \kappa }^e` - - production of fuel :math:`e` relative to the main output :math:` \kappa` by technology :math:`zsv \kappa`, and - * - :math:`\beta_{z \kappa vd}^e` - - consumption of fuel :math:`e` relative to the main output :math:`d` by technology :math:`z \kappa vd`. - -In case technologies are modeled with given production or consumption load curves, the variables are the annual variables multiplied by the share of the total energy flow in this load region :math:`\eta_{zsve}^l`: - -.. math: - \eta_{zsve}^l \times zsve....rr...ttt - -4.1.3 Resource Balance -~~~~~~~~~~~~~~~~~~~~~~ - -The resources produced by the extraction technologies in a period can come from different cost categories (also called grades), which can, e.g., represent the different effort to reach certain resources. Short-term variations in price due to steeply increasing demand can be represented by an elasticity approach (see section 9.11). - -.. math:: - \sum_{ttt} \sum_{g} rzfg....rr...ttt \leq rzfg....rr - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`rzfg....rr...ttt` - - annual extraction of resource :math:`f`, cost category (grade) :math:`g` in region :math:`rr` and period :math:`ttt`, and - * - :math:`rzfg....rr` - - total available amount of resource :math:`f`, grade :math:`g` in region :math:`rr`. diff --git a/annex/message/5_stock-piles.rst b/annex/message/5_stock-piles.rst deleted file mode 100644 index 45fc695..0000000 --- a/annex/message/5_stock-piles.rst +++ /dev/null @@ -1,66 +0,0 @@ -.. _stockpiles: - -5 Stock-piles -============= - -5.1 Variables -------------- - -Generally MESSAGE does not generate any variables related to an energy carrier alone. However, in the case of man-made fuels, that are accumulated over time, a variable that shifts the quantities from one load region or period to the next is generated. - -.. math:: - qfb.....rrlllttt - -where - -.. list-table:: - :widths: 40 110 - :header-rows: 0 - - * - :math:`q` - - identifies stock-pile variables, - * - :math:`f` - - identifies the fuel with stock-pile, - * - :math:`b` - - distinguishes the variable from the equation, and - * - :math:`rrlllttt` - - are the region, load region, and period identifiers respectively. - -The stock-pile variables represent the amount of fuel :math:`f` that is transferred from period :math:`t` into period :math:`t + 1`. Note that these variables do not, as usually, represent annual quantities, they refer to the period as a whole. These variables are a special type of storage, that just transfers the quantity of an energy carrier available in one period into the next period. Stock-piles are defined as a separate level. For all other energy carriers any overproduction that occurs in a period is lost. - -5.2 Constraints ---------------- - -.. math:: - qf......rrlllttt - -:math:`q` is a special level on that energy forms can be defined that are accumulated over time and may be consumed in later periods. One example is the accumulation of plutonium and later use in fast breeder reactors. - -The general form of this constraint is: - -.. math:: - qfb.....rrlllttt-qfb.....rrlll(ttt-1)-\sum_v \left[ \Delta t \times (zsvf....rrlllttt+\beta _{zsv\phi}^f\times zsv\phi....rrlllttt- \right. \\ - \epsilon _{zfvo}\times zfvo....rrlllttt - \beta _{z \phi vo}^f\times z \phi vo....rrlllttt) + \Delta t \times \iota_{zfvd} \times yzfvd...rr...(ttt)- \\ - \left. \Delta(t-\tau _{zfvd}-1)\times \rho_{zfvd} \times yzfvd...rr...(ttt-\tau_{zfvd}) \right] = 0 - - -where - -.. list-table:: - :widths: 60 110 - :header-rows: 0 - - * - :math:`f` - - identifier of the man-made fuel (e.g. plutonium, U_{233}), - * - :math:`\tau_{zsvd}` - - plant life of technology :math:`v` in periods, - * - :math:`\iota_{zsvf}` - - ”first inventory” of technology :math:`zsvf` of :math:`f` (relative to capacity of main output), - * - :math:`\rho_{zfvd}` - - ”last core” of :math:`f` in technology :math:`zfvd`, see also section :ref:`resourceextraction`, - * - :math:`\Delta t` - - length of period :math:`ttt` in years, - * - :math:`zfvd....rrlllttt` - - annual input of technology :math:`zfvd` of fuel :math:`f` in load region :math:`lll` and period :math:`ttt` (:math:`lll` is ”...” if :math:`zfvd` does not have load regions), and - * - :math:`yzfvd...rr...ttt` - - annual new installation of technology :math:`zfvd` in period :math:`ttt`. diff --git a/annex/message/6_user-defined_relations.rst b/annex/message/6_user-defined_relations.rst deleted file mode 100644 index a76e675..0000000 --- a/annex/message/6_user-defined_relations.rst +++ /dev/null @@ -1,43 +0,0 @@ -6 User-defined Relations -======================== - -.. math:: - nname...rrlllttt, pname...rrlllttt, Cname...rr - -The user-defined relations allow the user to construct constraints that are not included in the basic set of constraints. For each technology the user can specify coefficients with that either the production variables (see section :ref:`activitiesECT`), the annual new installation variables (see section :ref:`capacititesECT`) or the total capacity in a year (like it is used in the capacity constraints, see section :ref:`capacityconstr`) can be included in the relation. The relations can be defined with and without load regions, have a lower, upper or fix right hand side or remain free (non-binding) and may have an entry in the objective function, i.e., the objective function entries of all members of this relation are increased/decreased by this value. There are three types of user-defined constraints (denoted by :math:`n` for 'relations1', :math:`p` for 'relations2', or :math:`C` for 'relationsc' as first character). The entries to the objective function are (without discounting) summed up under the cost accounting rows :math:`car1` for 'relations1' and :math:`car2` for 'relations2' (see chapter :ref:`objectivecostcounters`). For 'relationsc' no additional accounting rows exist, as they are already just single numbers containing the sum over all load regions and time steps. - -The formulation of the user-defined relations is given for relations, that are related to the main output of the technologies. It is also possible (e.g., for greenhouse gas emissions) to relate the constraint to the main input of the technology, i.e. the amount of fuel used. In this case the efficiencies would be omitted from the formulation. - -Relations without load regions sum up the activities (multiplied with the given coefficients) of all variables defined to be in this constraint. If a technology has load regions, the activity variables for all load regions of this technology are included. If the total capacity of a technology is included, all new capacities from previous periods still operating are included, if new capacities are included, the annual new installation of the current period is taken. - -.. math:: - \sum_{zrvs}\left [ ro_{zrvs}^{mlt}\times\sum_{lll} zrvs...rrlllttt\times\epsilon_{zrvs}+ro_{zrvs}^{mt}\times zrvs....rr...ttt \times \epsilon_{zrvs}+ \right. \\ \left. \sum_{\tau=t-ip}^t pl_\tau \times rc_{zrvs}^{mt} \times yzrvs...rr...\tau \right ] \sim rhs_m^t - -where - -.. list-table:: - :widths: 60 110 - :header-rows: 0 - - * - :math:`zrvs....rrlllttt` - - activity variables of technologies (lll if modelled with and '...' without load regions, - * - :math:`yzrvs...rr...ttt` - - capacity variables of the technologies, - * - :math:`\epsilon_{zrvs}` - - efficiencies of the technologies; they are automatically included, - * - :math:`ro_{zsvd}^{mt}` - - relative factor per unit of output of technology :math:`zsvd` (coefficient) for relational constraint :math:`m`, - * - :math:`rc_{zsvd}^{mt}` - - relative factor per unit of new built capacity, - * - :math:`ro_{zrvs}^{mlt}` - - relative factor per unit of output of technology :math:`zsvd` (coefficient) for relational constraint :math:`m` and load region :math:`l`, - * - :math:`rc_{zrvs}^{mt}` - - relative factor per unit of new built capacity, - * - :math:`pl_t` - - is 1 for relations with new construction and :math:`\Delta\tau` (period length) for relations with total capacity, - * - :math:`ip` - - is 1 for accounting during construction and the plant life in periods for accounting of total capacity, - * - :math:`\sim` - - :math:`\geq, \leq, =, or free` indicating a lower, upper, equality, or free constraint, and - * - :math:`rhs_m^t` - - is the right hand side of the constraint. diff --git a/annex/message/7_objective_and_cost_counters.rst b/annex/message/7_objective_and_cost_counters.rst deleted file mode 100644 index 39d630f..0000000 --- a/annex/message/7_objective_and_cost_counters.rst +++ /dev/null @@ -1,106 +0,0 @@ -.. _objectivecostcounters: - -7 Objective and Cost Counters -============================= - -7.1 Cost Accounting Rows -~~~~~~~~~~~~~~~~~~~~~~~~ - -The different types of costs (i.e. entries for the objective function) can be accumulated over all technologies in built-in accounting rows. These rows can be generated per load region or per period or for the whole time horizon and contain the sum of the undiscounted costs. They can also be limited. In case of :math:`func` the entries are discounted as these are the entries into the objective function. The implemented types are: - -.. list-table:: - :widths: 45 110 - :header-rows: 0 - - * - :math:`func` - - objective functions and discounted accounting rows, - * - :math:`cvar` - - variable (related to the production) operation and maintenance costs, - * - :math:`cfix` - - fix (related to the installed capacity) operation and maintenance costs, - * - :math:`ccap` - - investment costs; if the investments of a technology are distributed over the previous periods, also the entries to this accounting rows are distributed, - * - :math:`cres` - - domestic fuel costs, - * - :math:`car1` - - costs related to the user defined relations of type 1 (see section 7), - * - :math:`car2` - - costs related to the user defined relations of type 2 (see section 7), - -The cost accounting rows are further separated into the following schemes: - -.. list-table:: - :widths: 80 110 - :header-rows: 0 - - * - :math:`name` - - total costs across all regions, load regions and time steps; :math:`func` is the objective function (see below), - * - :math:`name....rr` - - total costs across all load regions and time steps per region, - * - :math:`nameT........ttt` - - total costs across all regions and load regions per time step, - * - :math:`namet...rr...ttt` - - total costs per regions and time step, - * - :math:`namel...rrllltt` - - total costs per region, load region and time step. - -7.2 The Objective Function -~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. math:: - func - -In its usual form, the objective function contains the sum of all discounted costs. All costs related to operation (i.e. resource use, operation costs, taxes on emissions, ...) are discounted from the middle of the current period to the first year. Costs related to construction are by default discounted from the first year of the period to the first year. By using the facility of distributing the investment related costs over the construction time these costs can be distributed over some years before or equal to the current one (see section :ref:`distributionsofinv`). - -The objective function has the following general form: - -.. math:: - - & \sum_r \sum_t \left [ \beta_m^t \Delta t \sum_{zsvd} \sum_{lll} \left \{ \vphantom{\sum_i^t} zsvd....rrlllttt \times \epsilon_{zsvd} \times ccur(zsvd,t) + \right. \right. \\ - & \sum_{i=1,2,c} \sum_m rho_{zsvd}^{mlt} \times cari(ml,t) + \sum_{zsvd} \sum_{\tau=t-\tau_{zsvd}}^t \Delta\tau \times yzsvd..\tau \times cfix(zsvd,\tau) + \\ - & \left . \sum_g \sum_l \sum_p rzrg....rrlllttt \times cres(zrg,t) \right \} + \\ - & \beta_b^t \Delta(t-1) \sum_{zsvd} \sum_{\tau=t}^{t+t_d} \left \{ \vphantom{\sum_i^t} yzsvd...rr...\tau \times ccap(svd,\tau) \times fri_{zsvd}^{t_d-\tau} + \right. \\ - & \left. \left. \sum_{i=1,2,c} \sum_m rc_{zsvd}^{mt} \times cari(m,t) \times fra_{zsvd,m}^{t_d-\tau} \right \} \right ] \longrightarrow min - -with: - -.. math:: - \beta_b^t=\left [ \frac{1}{1+\frac{dr}{100}} \right ]^{t-t_0}, - \beta_m^t=\left [ \frac{1}{1+\frac{dr}{100}} \right ]^{t+ \frac{\Delta t}{2}-t_0}, - -.. list-table:: - :widths: 80 110 - :header-rows: 0 - - * - :math:`dr` - - is the discount rate in percent, - * - :math:`zsvd....rrlllttt` - - is the annual consumption of technology :math:`zsvd` of fuel :math:`s` load region :math:`l` and period :math:`t`; if :math:`zsvd` has no load regions, :math:`lll` = ”...”. - * - :math:`\epsilon_{zsvd}` - - is the efficiency of technology :math:`zsvd` in converting :math:`s` to :math:`d`, - * - :math:`ccur(zsvd,t)` - - are the variable operation and maintenance costs of technology :math:`zsvd` (per unit of main output) in period :math:`t`, - * - :math:`rho_{zsvd}^{mlt}` - - is the relative factor per unit of output of technology :math:`v` for relational constraint :math:`m` in period :math:`t`, load region :math:`l`, - * - :math:`car1(m,t)` - - and :math:`car2(m,t)` are the coefficients for the objective function, that are related to the user defined relation :math:`m` in period :math:`t`, - * - :math:`car1(ml,t)` - - and :math:`car2(ml,t)` are the same for load region :math:`l`, if relation :math:`m` has load regions, - * - :math:`rho_{zsvd}^{mt}` - - is the relative factor per unit of output of technology :math:`zsvd` for relational constraint :math:`m` in period :math:`t`, - * - :math:`yzsvd...rr...ttt` - - is the annual new built capacity of technology :math:`zsvd` in period :math:`t`, - * - :math:`cfix(zsvd,t)` - - are the fix operation and maintenance cost of technology :math:`zsvd` that was built in period :math:`t`, - * - :math:`ccap(zsvd,t)` - - is the specific investment cost of technology :math:`v` in period :math:`t` (given per unit of main output), - * - :math:`fri_{zsvd}^n` - - is the share of this investment that has to be paid n periods before the first year of operation, - * - :math:`rc_{zsvd}^{mt}` - - is the relative factor per unit of new built capacity of technology :math:`zsvd` for user defined relation :math:`m` in period :math:`t`, - * - :math:`fra_{zsvd,m}^n` - - is the share of the relative amount of the user defined relation :math:`m` that occurs :math:`n` periods before the first year of operation (this can, e.g., be used to account for the use of steel in the construction of solar towers over the time of construction), - * - :math:`rzrg....rrlllttt` - - is the annual consumption of resource :math:`r`, grade :math:`g` in load region :math:`l` and period :math:`t`, - * - :math:`cres(rgpl,t)` - - is the cost of extracting resource :math:`r`, grade :math:`g`, elasticity class :math:`p` in period :math:`t` and load region :math:`l` (this should only be given, if the extraction is not modelled explicitly), diff --git a/annex/message/8_special_features_of_the_matrix_generator.rst b/annex/message/8_special_features_of_the_matrix_generator.rst deleted file mode 100644 index 3fd024e..0000000 --- a/annex/message/8_special_features_of_the_matrix_generator.rst +++ /dev/null @@ -1,122 +0,0 @@ -.. _specialfeatures: - -8 Special Features of the Matrix Generator -========================================== - -The mathematical formulation of MESSAGE as presented in the previous sections shows the structure of all constraints as the matrix generator builds them up. The background of the more complicated features is given here for a better understanding. - -8.1 Discounting of Costs ------------------------- - -The whole time horizon of the calculations is divided into periods of optional length. All variables of MESSAGE are represented as average over the period they represent, resulting in a step-function. All entries in the objective function are discounted from the middle of the respective period to the first year, if they relate to energy flow variables and from the beginning of that period if they represent power variables. The function to discount the costs has the following form: - -.. math:: - c_t=\frac{C_t^r}{\prod_{k=1}^{t-1}(1+\frac{dr_k}{100})^{\Delta k}\times f_i} - -where - -.. list-table:: - :widths: 35 65 - :header-rows: 0 - - * - :math:`C_t^r` - - cost figure to be discounted, - * - :math:`c_t` - - objective function coefficient in period :math:`t`, - * - :math:`f_i` - - cost factor (see below), and - * - :math:`dr_t` - - discount rate in period :math:`t`; generally the discount rate is constant over the complete time horizon. -.. math:: - f_i = \left\{\begin{array}{ll} - 1 &\mbox{for costs connected to investments} \\ - (1+\frac{dr_t}{100})^{\frac{\Delta t}{2}} &\mbox{else} - \end{array}\right. - -.. _distributionsofinv: - -8.2 Distributions of Investments --------------------------------- - -Investment costs can be distributed over the construction time. As these points in time are closer to the beginning of the time horizon, investments become more expensive, this represents interest during construction. MESSAGE allows for two options: - -.. list-table:: - :widths: 35 65 - :header-rows: 0 - - * - shifted - - all costs are paid in the time period(s) prevoius to the start of operation. This is usually used for models with short period lengths, - * - half\-half - - half of the investments are paid in the period before the start of operation, the other half is paid in the period when the technology goes into operation. With this, the period when the technology starts operating is the same as the construction period. This is usually used for models with long time periods. - -Investment costs are spread evenly over the construction time. In reality the investment costs follow a bell-shape, but the resulting error after discounting and summing up over the construction time is very small. There still remains only one entry into the objective function, which is modified according to the sum over the distribution results. - -8.3 The Contribution of Capacities Existing in the Base Year ------------------------------------------------------------- - -The possible contribution of an installation that exists in the base year is kept track of over time. There are two possibilities to give the necessary information to MESSAGE. - -1. Define the capacities that were built in the years :math:`iyr, ..., iyr −\tau + 1`, with :math:`iyr` = base year and :math:`τ` = plant life in years explicitly. These capacities are then distributed to historic periods of the length :math:`\nu`. - -2. Define the total capacity, :math:`c_0`, that exists in :math:`iyr` and the rate at that it grew in the last :math:`\tau` years, :math:`\gamma`. This information is then converted to one similar to 1. by using the function: - -.. math:: - y_0=c_0\frac{\gamma^{-\nu}-1}{\nu(\gamma^{-\tau}-1)}, - y_t=y_0\gamma^{-t\times\nu}, t=1(1)\frac{\tau}{\nu} - -where - -.. list-table:: - :widths: 35 65 - :header-rows: 0 - - * - :math:`y_t` - - is the annual construction in period :math:`−t`, (0 = base year), - * - :math:`\gamma` - - is the annual growth of new installations before the base year, - * - :math:`c_0` - - is the total capacity in the base year, - * - :math:`\tau` - - is the plant life, and - * - :math:`\nu` - - is the length of the periods in that the time before the base year is divided. - -The right hand sides in the capacity constraints are derived by summing up all the old capacities that still exist in a certain period (according to the plant life). If the life of a technology expires within a period, MESSAGE takes the average production capacity in this period as installed capacity (this represents a linear interpolation between the starting points of this and the following period). - -In case of formulation 2. one has to consider that some of the capacity goes out of operation between the base year and the first year. - -8.4 Capacities which Operate Longer than the Time Horizon ---------------------------------------------------------- - -If a capacity of a technology is built in one of the last periods its life time can exceed the calculation horizon. This fact is taken care of by reducing the investment costs by the following formula: - -.. math:: - C_t^r=C_t\times\frac{\sum_{k=1}^{\tau_p-\nu}\prod_{\tau=t}^{t+k-1}\frac{1}{1+dr_\tau}}{\sum_{k=1}^{\tau_p}\prod_{\tau=t}^{t+k-1}\frac{1}{1+dr_\tau}} - -where - -.. list-table:: - :widths: 35 65 - :header-rows: 0 - - * - :math:`\nu` - - is the number of years the technology exists after the end of the calculation horizon, - * - :math:`dr_{\tau}` - - is the discount rate for year :math:`\tau`, - * - :math:`\tau_p` - - is the plant life in years, - * - :math:`C_t` - - is the investment cost in year :math:`t`, and - * - :math:`C_t^r` - - is the reduced investment. - -8.5 The Mixed Integer Option ----------------------------- - -If the LP-package used to solve a problem formulated by MESSAGE has the capability to solve mixed integer problems, this can be used to improve the quality of the formulated problems, especially for applications to small regions. - -The improvement consists in a definition of unit sizes for certain technologies that can only be built in large units. This avoids for instance the installation of a 10 kW nuclear reactor in the model of the energy system of a city or small region (it can only be built in units of e.g., 700 MW). Additionally this option allows to take care of the ”economies of scale” of certain technologies. - -This option is implemented for a technology by simply defining the unit size for this technology (keyword cmix). The according capacity variable is then generated as integer in the matrix, its value is the installation of one powerplant of unit size. - -If a problem is formulated as mixed integer it can be applied without this option by changing just one switch in the general definition file (keyword mixsw). Then all capacity variables are generated as real variables. diff --git a/annex/message/index.rst b/annex/message/index.rst deleted file mode 100755 index ea6f7cb..0000000 --- a/annex/message/index.rst +++ /dev/null @@ -1,14 +0,0 @@ -MESSAGE V -********* - -.. toctree:: - :maxdepth: 2 - - 1_introduction - 2_conversion_technologies - 3_domestic_resources - 4_energy_flows - 5_stock-piles - 6_user-defined_relations - 7_objective_and_cost_counters - 8_special_features_of_the_matrix_generator diff --git a/bibs/main.bib b/bibs/main.bib index da0e33e..c9ff868 100755 --- a/bibs/main.bib +++ b/bibs/main.bib @@ -1623,3 +1623,14 @@ @article{grubler_2018_led doi={10.1038/s41560-018-0172-6}, type = {Journal Article} } + +@article{roelfsema_2020_paris, +author = {Roelfsema, M. and van Soest, H. L. and Harmsen, M. and van Vuuren, D. P. and Bertram, C. and den Elzen, M. and Höhne, N. and Iacobuta, G. and Krey, V. and Kriegler, E. and Luderer, G. and Riahi, K. and Ueckerdt, F. and Després, J. and Drouet, L. and Emmerling, J. and Frank, S. and Fricko, O. and Gidden, M. and Humpenöder, F. and Huppmann, D. and Fujimori, S. and Fragkiadakis, K. and Gi, K. and Keramidas, K. and Köberle, A. C. and Aleluia Reis, L. and Rochedo, P. and Schaeffer, R. and Oshiro, K. and Vrontisi, Z. and Chen, W. and Iyer, G. C. and Edmonds, J. and Kannavou, M. and Jiang, K. and Mathur, R. and Safonov, G. and Vishwanathan, S. S.}, +title = {Taking stock of national climate policies to evaluate implementation of the Paris Agreement}, +journal = {Nature Communications}, +volume = {11}, +number = {1}, +year = {2020}, +doi = {https://doi.org/10.1038/s41467-020-15414-6}, +type = {Journal Article} +} diff --git a/bibs/messageix-globiom.bib b/bibs/messageix-globiom.bib new file mode 100644 index 0000000..9872235 --- /dev/null +++ b/bibs/messageix-globiom.bib @@ -0,0 +1,32 @@ +@techreport{message_globiom_2020, + address = {Laxenburg, Austria}, + author = {Krey, V. and Havlik, P. and Kishimoto, P. N. and Fricko, O. and Zilliacus, J. and Gidden, M. and Strubegger, M. and Kartasasmita, G. and Ermolieva, T. and Forsell, N. and Gusti, M. and Johnson, N. and Kikstra, J. and Kindermann, G. and Kolp, P. and Lovat, F. and McCollum, D. L. and Min, J. and Pachauri, S. and Parkinson S. C. and Rao, S. and Rogelj, J. and and Ünlü, G. Valin, H. and Wagner, P. and Zakeri, B. and Obersteiner, M. and Riahi, K.}, + doi = {10.22022/iacc/03-2021.17115}, + institution = {International Institute for Applied Systems Analysis (IIASA)}, + title = {{MESSAGEix-GLOBIOM Documentation -- 2020 release}}, + url = {https://pure.iiasa.ac.at/id/eprint/17115}, + year = {2020}, +} +% Alternately, use the following URL: +% url = {https://docs.messageix.org/projects/global/en/v2020/} + +@article{fricko_havlik_2017, + author = {Fricko, O. and Havlik, P. and Rogelj, J. and Klimont, Z. and Gusti, M. and Johnson, N. and Kolp, P. and Strubegger, M. and Valin, H. and Amann, M. and Ermolieva, T. and Forsell, N. and Herrero, M. and Heyes, C. and Kindermann, G. and Krey, V. and McCollum, D. L. and Obersteiner, M. and Pachauri, S. and Rao, S. and Schmid, E. and Schoepp, W. and Riahi, K.}, + doi = {10.1016/j.gloenvcha.2016.06.004}, + issn = {0959-3780}, + journal = {Global Environmental Change}, + pages = {251–267}, + title = {{The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century}}, + volume = {42}, + year = {2017}, +} + +@article{huppmann_2019_MESSAGEix, + author = {Huppmann, Daniel and Gidden, Matthew and Fricko, Oliver and Kolp, Peter and Orthofer, Clara and Pimmer, Michael and Kushin, Nikolay and Vinca, Adriano and Mastrucci, Alessio and Riahi, Keywan and Krey, Volker}, + doi = {10.1016/j.envsoft.2018.11.012}, + journal = {Environmental Modelling \& Software}, + pages = {143–156}, + title = {{The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp): An open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development}}, + volume = {112}, + year = {2019}, +} diff --git a/_static/message-globiom.ris b/bibs/messageix-globiom.ris similarity index 82% rename from _static/message-globiom.ris rename to bibs/messageix-globiom.ris index 05cefd7..b2ff57d 100644 --- a/_static/message-globiom.ris +++ b/bibs/messageix-globiom.ris @@ -2,6 +2,7 @@ AD - International Institute for Applied System Analysis (IIASA), Schlossplatz 1, 2361 Laxenburg, Austria AU - Krey, V. AU - Havlik, P. +AU - Kishimoto, P. N. AU - Fricko, O. AU - Zilliacus, J. AU - Gidden, M. @@ -11,23 +12,31 @@ AU - Ermolieva, T. AU - Forsell, N. AU - Gusti, M. AU - Johnson, N. +AU - Kikstra, J. AU - Kindermann, G. AU - Kolp, P. +AU - Lovat, F. AU - McCollum, D. L. +AU - Min, J. AU - Pachauri, S. +AU - Parkinson, S. C. AU - Rao, S. AU - Rogelj, J. +AU - Ünlü, G. AU - Valin, H. +AU - Wagner, P. +AU - Zakeri, B. AU - Obersteiner, M. AU - Riahi, K. CY - Laxenburg, Austria -DB - Scopus PB - International Institute for Applied Systems Analysis (IIASA) -PY - 2016 -ST - MESSAGE-GLOBIOM 1.0 Documentation -TI - MESSAGE-GLOBIOM 1.0 Documentation -UR - http://data.ene.iiasa.ac.at/message-globiom/ -ER - +PY - 2020 +ST - MESSAGEix-GLOBIOM Documentation - 2020 release +TI - MESSAGEix-GLOBIOM Documentation +DO - 10.22022/iacc/03-2021.17115 +UR - https://pure.iiasa.ac.at/id/eprint/17115 +UR - https://docs.messageix.org/global/en/v2020 +ER - TY - JOUR @@ -54,10 +63,9 @@ AU - Rao, S. AU - Schmid, E. AU - Schoepp, W. AU - Riahi, K. -DB - Scopus -DO - http://dx.doi.org/10.1016/j.gloenvcha.2016.06.004 +DO - https://doi.org/10.1016/j.gloenvcha.2016.06.004 VL - 42 -IS - +IS - SP - 251 EP - 267 DA - 2017/01/01/ @@ -65,7 +73,7 @@ PY - 2017 ST - The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century T2 - Global Environmental Change TI - The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century -ER - +ER - TY - JOUR @@ -89,4 +97,4 @@ T2 - Environmental Modelling & Software TI - The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp): An open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development VL - 112 ID - 817 -ER - +ER - diff --git a/conf.py b/conf.py index ec6929f..1ffd620 100644 --- a/conf.py +++ b/conf.py @@ -6,29 +6,36 @@ # -- Project information ----------------------------------------------------- -project = 'MESSAGE-GLOBIOM' -copyright = '2016–2020, IIASA Energy Program' -author = 'IIASA Energy Program' -# The major project version, used as the replacement for |version|. -version = '2020-03-05' -# The full project version, used as the replacement for |release|. -release = '2020-03-05' +project = "MESSAGEix-GLOBIOM" +copyright = "2016–2020, IIASA Energy Program" +author = "IIASA Energy Program" + +# Set this to the specific version number for a release; otherwise `latest` +version = "2020" +release = "2020" # -- General configuration ------------------------------------------------ -exclude_patterns = ["README.rst"] +exclude_patterns = [ + "README.rst", + # Uncomment this line to suppress warnings when these files are excluded. + # See corresponding comment at the bottom of index.rst. + "_extra/*.rst", + # Currently under development + "glossary.rst", +] # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ - 'sphinx.ext.autodoc', - 'sphinx.ext.coverage', - 'sphinx.ext.doctest', - 'sphinx.ext.intersphinx', - 'sphinx.ext.mathjax', - 'sphinx.ext.todo', - 'sphinxcontrib.bibtex', + "sphinx.ext.autodoc", + "sphinx.ext.coverage", + "sphinx.ext.doctest", + "sphinx.ext.intersphinx", + "sphinx.ext.mathjax", + "sphinx.ext.todo", + "sphinxcontrib.bibtex", ] # Figures, tables and code-blocks are automatically numbered if they have a @@ -37,13 +44,15 @@ # A string of reStructuredText included at the beginning of every source file # that is read. -rst_prolog = """ +rst_prolog = r""" +.. |MESSAGEix| replace:: MESSAGE\ :emphasis:`ix` + .. role:: strike .. role:: underline """ # Add any paths that contain templates here, relative to this directory. -templates_path = ['_templates'] +templates_path = ["_templates"] # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = True @@ -52,46 +61,43 @@ # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. -html_theme = 'sphinx_rtd_theme' - -html_logo = '_static/logo_white.png' - -html_static_path = ['_static'] - -html_style = 'css/custom.css' +html_theme = "sphinx_rtd_theme" +html_logo = "_static/logo_white.png" -# -- Options for HTML help output ----------------------------------------- +html_static_path = ["_static"] -# Output file base name for HTML help builder. -htmlhelp_basename = 'messagedoc' +html_style = "css/custom.css" # -- Options for LaTeX output --------------------------------------------- +# LaTeX engine to build the docs +latex_engine = "lualatex" + latex_elements = { # Paper size option of the document class. - 'papersize': 'a4paper', - + "papersize": "a4paper", # Additional preamble content. - 'preamble': r""" + "preamble": r""" \usepackage{tabularx} """, } -# Group the document tree into LaTeX source files. -# latex_documents = [ -# ('index', 'message.tex', 'MESSAGE-GLOBIOM Documentation', -# 'IIASA Energy Program', 'manual', False), -# ] - # The name of an image file (relative to this directory) to place at the top of # the title page. -latex_logo = '_static/logo_blue.png' +latex_logo = "_static/logo_blue.png" # -- Options for sphinx.ext.intersphinx -------------------------------------- intersphinx_mapping = { - 'python': ('https://docs.python.org/3/', None), - 'message_ix': ('https://docs.messageix.org/en/latest/', None), + "python": ("https://docs.python.org/3/", None), + "message_ix": ("https://docs.messageix.org/en/latest/", None), } + +# -- Options for sphinxcontrib.bibtex ----------------------------------------- + +bibtex_bibfiles = [ + "bibs/main.bib", + "bibs/messageix-globiom.bib", +] diff --git a/energy/conversion/electricity.rst b/energy/conversion/electricity.rst index e3e52ce..6b09ce0 100755 --- a/energy/conversion/electricity.rst +++ b/energy/conversion/electricity.rst @@ -2,13 +2,25 @@ Electricity =========== -MESSAGE covers a large number of electricity generation options utilizing a wide range of primary energy sources. For fossil-based electricity generation technologies, typically a number of different technology variants with different efficiencies, environmental characteristics and costs are represented. For example, in the case of coal, MESSAGE distinguishes subcritical and supercritical pulverized coal (PC) power plants where the subcritical variant is available with and without flue gas desulpherization/denox and one internal gasification combined cycle (IGCC) power plant. The superciritical PC and IGCC plants are also available with carbon capture and storage (CCS) which also can be retrofitted to some of the existing PC power plants. :numref:`tab-elec` below shows the different power plant types represented in MESSAGE. +MESSAGE covers a large number of electricity generation options utilizing a wide range of primary energy sources. For fossil-based electricity generation technologies, typically a number of different technology variants with different efficiencies, environmental characteristics and costs are represented. For example, in the case of coal, MESSAGE distinguishes subcritical and supercritical pulverized coal (PC) power plants where the subcritical variant is available with and without flue gas desulpherization/denox and one internal gasification combined cycle (IGCC) power plant. The supercritical PC and IGCC plants are also available with carbon capture and storage (CCS) which also can be retrofitted to some of the existing PC power plants (see :numref:`fig-elec-fossil-nuc`). :numref:`tab-elec` below shows the different power plant types represented in MESSAGE. + +.. _fig-elec-fossil-nuc: +.. figure:: /_static/electricity_generation_fossil_nuclear.png + + Schematic diagram of the fossil and nuclear power plants represented in MESSAGEix. + Four different nuclear power plant types are represented in MESSAGE, i.e. two light water reactor types, a fast breeder reactor and a high temperature reactor, but only the two light water types are included in the majority of scenarios being developed with MESSAGE in the recent past. In addition, MESSAGE includes a representation of the nuclear fuel cycle, including reprocessing and the plutonium fuel cycle, and keeps track of the amounts of nuclear waste being produced. -The conversion of five renewable energy sources to electricity is represented in MESSAGE (see :numref:`tab-elec`). For wind power, both on- and offshore electricity generation are covered and for solar energy, photovoltaics (PV) and solar thermal (concentrating solar power, CSP) electricity generation are included in MESSAGE (see also sections on :ref:`renewable` and :ref:`syst_integration`). +The conversion of five renewable energy sources to electricity is represented in MESSAGE (see :numref:`fig-elec-renewable`). For wind power, both on- and offshore electricity generation are covered and for solar energy, photovoltaics (PV) and solar thermal (concentrating solar power, CSP) electricity generation are included in MESSAGE (see also sections on :ref:`renewable` and :ref:`syst_integration`). Two CSP technologies are modeled: (1) a flexible plant with a solar multiple of one (SM1) and 6 h of thermal storage and (2) a baseload plant with a solar multiple of three (SM3) and 12 h of storage (Johnson et al. 2016, :cite:`johnson_vre_2016`). +.. _fig-elec-renewable: +.. figure:: /_static/electricity_generation_renewable.png + + Schematic diagram of the renewable power generation options represented in MESSAGEix. + + Most thermal power plants offer the option of coupled heat production (CHP, see :numref:`tab-elec`). This option is modeled as a passout turbine via a penalty on the electricity generation efficiency. In addition to the main electricity generation technologies described in this section, also the co-generation of electricity in conversion technologies primarily devoted to producing non-electric energy carriers (e.g., synthetic liquid fuels) is included in MESSAGE (see section on :ref:`other`). .. _tab-elec: @@ -40,6 +52,8 @@ Most thermal power plants offer the option of coupled heat production (CHP, see | | gas combustion turbine gas | yes | | +----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------+ | | combined cycle power plant | yes | + | +----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------+ + | | combined cycle power plant with CCS | yes | +------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------+ | nuclear | nuclear light water reactor (Gen II) | yes | | +----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------+ @@ -74,7 +88,7 @@ Most thermal power plants offer the option of coupled heat production (CHP, see .. figure:: /_static/costind-thermo.png :width: 700px - Cost indicators for thermoelectric power-plant investment (Fricko et al., 2017 :cite:`fricko_marker_2017`). + Cost indicators for thermoelectric power-plant investment (Fricko et al., 2017 :cite:`fricko_marker_2017`). In :numref:`fig-ther`, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively (see description of the :ref:`narratives`). Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region (Fricko et al., 2017 :cite:`fricko_marker_2017`). @@ -82,6 +96,6 @@ In :numref:`fig-ther`, the black ranges show historical cost ranges for 2005. Gr .. figure:: /_static/costind-nonthermo.png :width: 700px - Cost indicators for non-thermoelectric power-plant investment (Fricko et al., 2017 :cite:`fricko_marker_2017`). Abbreviations: CCS – Carbon Capture and Storage; IGCC – Integrated gasification combined cycles; ST – Steam turbine; CT – Combustion turbine; CCGT – Combined cycle gas turbine - + Cost indicators for non-thermoelectric power-plant investment (Fricko et al., 2017 :cite:`fricko_marker_2017`). Abbreviations: CCS – Carbon Capture and Storage; IGCC – Integrated gasification combined cycles; ST – Steam turbine; CT – Combustion turbine; CCGT – Combined cycle gas turbine + In :numref:`fig-nonth`, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively. Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. PV – Photovoltaic (Fricko et al., 2017 :cite:`fricko_marker_2017`). diff --git a/energy/demand.rst b/energy/demand.rst index d050d53..3ba35d5 100755 --- a/energy/demand.rst +++ b/energy/demand.rst @@ -2,8 +2,8 @@ Energy demand ============= -Baseline energy service demands are provided exogenously to MESSAGE, though they can be adjusted endogenously based on energy prices using the MESSAGE-MACRO link. There are seven energy -service demands that are provided to MESSAGE, including: +Baseline energy service demands are provided exogenously to |MESSAGEix|, though they can be adjusted endogenously based on energy prices using the |MESSAGEix|-MACRO link. There are seven energy +service demands that are provided to |MESSAGEix|, including: 1. Residential/commercial thermal 2. Residential/commercial specific @@ -13,8 +13,8 @@ service demands that are provided to MESSAGE, including: 6. Transportation 7. Non-commercial biomass. -These demands are generated using a so-called scenario generator which is implemented in the script language `R `_. The scenario generator relates historical country-level -GDP per capita (PPP) to final energy and, using projections of GDP (PPP) and population, extrapolate the seven energy service demands into the future. The +These demands are generated using a so-called scenario generator which is implemented in the script language `R `_. The scenario generator relates historical country-level +GDP per capita (PPP) to final energy and, using projections of GDP (PPP) and population, extrapolate the seven energy service demands into the future. The sources for the historical and projected datasets are the following: 1. Historical GDP (PPP) – World Bank (World Development Indicators, 2012 :cite:`world_bank_group_world_2012`) @@ -23,18 +23,18 @@ sources for the historical and projected datasets are the following: 4. Projected GDP (PPP) – Dellink et al. (2015) :cite:`dellink_long-term_2015`, also see Shared Socio-Economic Pathways database (`SSP scenarios `_) 5. Projected Population – KC and Lutz (2014) :cite:`kc_human_2014`, also see Shared Socio-Economic Pathways database (`SSP scenarios `_) -The scenario generator runs regressions on the historical datasets to establish the relationship for each of the eleven MESSAGE regions between the independent variable (GDP (PPP) per capita) and the following dependent variables: +The scenario generator runs regressions on the historical datasets to establish the relationship for each of the eleven |MESSAGEix| regions between the independent variable (GDP (PPP) per capita) and the following dependent variables: 1. Total final energy intensity (MJ/2005USD) 2. Shares of final energy among several energy end-use sectors (transport, residential/commercial and industry) 3. Shares of electricity use between the industrial and residential/commercial sectors. -In the case of final energy intensity, the relationship is best modeled by a power function so both variables are log-transformed. In the case of most sectoral shares, only the independent variable is log-transformed. -The exception is the industrial share of final energy, which uses a hump-shaped function inspired by Schafer (2005) :cite:`schafer_structural_2005`. +In the case of final energy intensity, the relationship is best modeled by a power function so both variables are log-transformed. In the case of most sectoral shares, only the independent variable is log-transformed. +The exception is the industrial share of final energy, which uses a hump-shaped function inspired by Schafer (2005) :cite:`schafer_structural_2005`. -In parallel, the same historical data are used, now globally, in `quantile regressions `_ to develop global trend lines that represent each percentile of the cumulative distribution function (CDF) of each dependent variable. Given the regional regressions and global trend lines, final energy intensity and sectoral shares can be extrapolated based on projected GDP per capita, or average income. +In parallel, the same historical data are used, now globally, in `quantile regressions `_ to develop global trend lines that represent each percentile of the cumulative distribution function (CDF) of each dependent variable. Given the regional regressions and global trend lines, final energy intensity and sectoral shares can be extrapolated based on projected GDP per capita, or average income. -A basic assumption here is that the regional trends derived above will converge to certain quantiles of the global trend when each region reaches a certain income level. Hence, two key user-defined inputs allow users to tailor the extrapolations to individual socio-economic scenarios: convergence quantile and the corresponding income. +A basic assumption here is that the regional trends derived above will converge to certain quantiles of the global trend when each region reaches a certain income level. Hence, two key user-defined inputs allow users to tailor the extrapolations to individual socio-economic scenarios: convergence quantile and the corresponding income. In the case of final energy intensity (FEI), the extrapolation is produced for each region by defining the quantile at which FEI converges (e.g., the 20th percentile within the global trend) and the income at which the convergence occurs. For example, while final energy intensity converges quickly to the lowest quantile (0.001) in SSP1, it converges more slowly to a larger quantile (0.5 to 0.7 depending on the region) in SSP3. Convergence quantiles and incomes are provided for each SSP and region in :numref:`tab-quantssp1`, :numref:`tab-quantssp2`, :numref:`tab-quantssp3`. The convergence quantile allows one to identify the magnitude of FEI while the convergence income establishes the rate at which the quantile is approached. For the sectoral shares, users can specify the global quantile at which the extrapolation should converge, the income at which the extrapolation diverges from the regional regression line and turns parallel to the specified convergence quantile (i.e., how long the sectoral share follows the historical trajectory), and the income at which the extrapolation converges to the quantile. Given these input parameters, users can extrapolate both FEI and sectoral shares. The total final energy in each region is then calculated by multiplying the extrapolated final energy intensity by the projected GDP (PPP) in each time period. Next, the extrapolated shares are multiplied by the total final energy to identify final energy demand for each of the seven energy service demands used in MESSAGE. Finally, final energy is converted to useful energy in each region by using the average final-to-useful energy efficiencies used in the MESSAGE model for each model region (:ref:`spatial`). diff --git a/energy/fuel_blending.rst b/energy/fuel_blending.rst index d064374..e5e328b 100644 --- a/energy/fuel_blending.rst +++ b/energy/fuel_blending.rst @@ -2,7 +2,7 @@ Fuel Blending ============= -Fuel blending in the energy system is a common practice, which allows the shared use of infrastructure by fuels with similar chemical attributes and thus use at the secondary and final energy level, without requiring the consumer to adapt the power plant or enduse devices. Fuel blending in the global energy model is modelled for two distinct blending processes. The first relates to the blending of natural gas with other synthetic gases. The second is related to the blending of light oil with coal derived synthetic liquids. In order to ensure that emissions and energy flows are correctly accounted for, blended fuels types are nevertheless explicitly modelled. +Fuel blending in the energy system is a common practice, which allows the shared use of infrastructure by fuels with similar chemical attributes and thus use at the secondary and final energy level, without requiring the consumer to adapt the power plant or enduse devices. Fuel blending in the global energy model is modelled for two distinct blending processes. The first relates to the blending of natural gas with other synthetic gases. The second is related to the blending of light oil with coal derived synthetic liquids. In order to ensure that emissions and energy flows are correctly accounted for, blended fuels types are nevertheless explicitly modelled. Natural gas and synthetic gas diff --git a/energy/index.rst b/energy/index.rst index d263d76..373c91a 100755 --- a/energy/index.rst +++ b/energy/index.rst @@ -1,17 +1,17 @@ .. _message: -Energy (MESSAGE) -**************** +Energy (|MESSAGEix|) +******************** -The `MESSAGEix `_ modeling framework, briefly known as MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impact), is a linear programming (LP) energy engineering model with global coverage. -As a systems engineering optimization model, MESSAGE is primarily used for medium- to long-term energy system planning, energy policy analysis, and scenario development +The `|MESSAGEix| `_ modeling framework, briefly known also as MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impact), is a linear programming (LP) energy engineering model with global coverage. +As a systems engineering optimization model, |MESSAGEix| is primarily used for medium- to long-term energy system planning, energy policy analysis, and scenario development (Huppmann et al., 2019 :cite:`huppmann_2019_messageix`; Messner and Strubegger, 1995 :cite:`messner_users_1995`). The model provides a framework for representing an energy system with all its interdependencies from resource extraction, imports and exports, conversion, transport, and distribution, to the provision of energy end-use services such as light, space conditioning, industrial -production processes, and transportation. In addition, MESSAGE links to GLOBIOM (GLObal BIOsphere Model, cf. Section :ref:`globiom`) to consistently assess the implications +production processes, and transportation. In addition, |MESSAGEix| links to GLOBIOM (GLObal BIOsphere Model, cf. Section :ref:`globiom`) to consistently assess the implications of utilizing bioenergy of different types and to integrate the GHG emissions from energy and land use and to the aggregated macro-economic model MACRO (cf. Section :ref:`macro`) to assess economic implications and to capture economic feedbacks. -MESSAGE covers all greenhouse gas (GHG)-emitting sectors, including energy, industrial processes as well as - through its linkage to GLOBIOM - agriculture and forestry. +|MESSAGEix| covers all greenhouse gas (GHG)-emitting sectors, including energy, industrial processes as well as - through its linkage to GLOBIOM - agriculture and forestry. The emissions of the full basket of greenhouse gases including CO2, CH4, N2O and F-gases (CF4, C2F6, HFC125, HFC134a, HFC143a, HFC227ea, HFC245ca and SF6) as well as other radiatively active gases, such as NOx, volatile organic compounds (VOCs), CO, SO2, and BC/OC is represented in hte model. MESSAGE is used in conjunction with MAGICC (Model for Greenhouse gas Induced Climate Change) version 6.8 (cf. Section :ref:`magicc`) for calculating atmospheric concentrations, radiative forcing, and annual-mean global surface air temperature increase. @@ -26,10 +26,10 @@ the model identifies the least-cost portfolio of mitigation technologies. The ch economics of the abatement measures, assuming full temporal and spatial flexibility (i.e., emissions-reduction measures are assumed to occur when and where they are cheapest to implement). -The Reference Energy System (RES) defines the full set of available energy conversion technologies. In MESSAGE terms, energy conversion technology refers to all types +The Reference Energy System (RES) defines the full set of available energy conversion technologies. In |MESSAGEix| terms, energy conversion technology refers to all types of energy technologies from resource extraction to transformation, transport, distribution of energy carriers, and end-use technologies. -Because few conversion technologies convert resources directly into useful energy, the energy system in MESSAGE is divided into 5 energy levels: +Because few conversion technologies convert resources directly into useful energy, the energy system in |MESSAGEix| is divided into 5 energy levels: * Resources: raw resources (e.g., coal, oil, natural gas in the ground or biomass on the field) * Primary energy: raw product at a generation site (e.g., crude oil input to the refinery) @@ -37,11 +37,11 @@ Because few conversion technologies convert resources directly into useful energ * Final energy: finalized product at its consumption point (e.g., gasoline in the tank of a car or electricity leaving a socket) * Useful energy: finalized product satisfying demand for services (e.g., heating, lighting or moving people) -Technologies can take in energy commodities from one level and put out at another level (e.g., refineries produce refinded oil products at secondary level from crude oil at the primary level) +Technologies can take in energy commodities from one level and put out at another level (e.g., refineries produce refined oil products at secondary level from crude oil at the primary level) or at the same level (e.g., hydrogen electrolyzers produce hydrogen at the secondary energy level from electricity at the secondary level). The energy forms defined in each level can be envisioned as a transfer hub, that the various technologies feed into or pump away from. The useful energy demand is given as a time series. Technology characteristics generally vary over time period. -The mathematical formulation of MESSAGE ensures that the flows are consistent: demand is met, inflows equal outflows and constraints are not exceeded. In other words, MESSAGE itself is a partial +The mathematical formulation of |MESSAGEix| ensures that the flows are consistent: demand is met, inflows equal outflows and constraints are not exceeded. In other words, |MESSAGEix| itself is a partial equilibrium model. However, through its linkage to MACRO general equilibrium effects are taken into account (cf. Section :ref:`macro`). .. toctree:: diff --git a/energy/policy.rst b/energy/policy.rst index 4a991e2..ad87c80 100644 --- a/energy/policy.rst +++ b/energy/policy.rst @@ -14,10 +14,7 @@ The targets formulated in the NDCs come in many different flavors. This applies 4. Macro-economic targets A detailed description of the methodological implementation of the NDCs in the global energy model, along with an extensive list of the energy-related targets considered can be found in Rogelj et al. (2017) :cite:`rogelj_indc_2017`. - -.. TODO complete the following. See iiasa/message_doc#42 - - Additional policies implemented in the model can also be found in ('what reference for the CD_Links related policies?`). +Additional policies implemented in the model can also be found in Roelfsema et al. (2020) :cite:`roelfsema_2020_paris`. Emission targets ---------------- @@ -36,8 +33,8 @@ Some NDCs specify capacity installation targets, e.g. for planned power plants w .. TODO complete the following. See iiasa/message_doc#43 - Macro-economic targets - ---------------------- +Macro-economic targets +---------------------- Representation of taxes and subsidies diff --git a/energy/tech.rst b/energy/tech.rst index 4ef7bf4..a34c1ef 100755 --- a/energy/tech.rst +++ b/energy/tech.rst @@ -2,7 +2,7 @@ Technological change ====================== -Technological change in MESSAGE is generally treated exogenously, although pioneering works on the endogenization of technological change via learning curves in energy-engineering type models (Messner, 1997 :cite:`messner_endogenized_1997`) and the dependence of technology costs on market structure have been done with MESSAGE (Leibowicz, 2015 :cite:`leibowicz_growth_2015`). The current cost and performance parameters, including conversion efficiencies and emission coefficients are generally derived from the relevant engineering literature. For the future, alternative cost and performance projections are developed to cover a relatively wide range of uncertainties that influence model results to a good extent. +Technological change in |MESSAGEix| is generally treated exogenously, although pioneering works on the endogenization of technological change via learning curves in energy-engineering type models (Messner, 1997 :cite:`messner_endogenized_1997`) and the dependence of technology costs on market structure have been done with |MESSAGEix| (Leibowicz, 2015 :cite:`leibowicz_growth_2015`). The current cost and performance parameters, including conversion efficiencies and emission coefficients are generally derived from the relevant engineering literature. For the future, alternative cost and performance projections are developed to cover a relatively wide range of uncertainties that influence model results to a good extent. Technology cost ---------------- @@ -13,18 +13,18 @@ Technological costs vary regionally in all SSPs, reflecting marked differences i Technology diffusion --------------------- -MESSAGE tracks investments by vintage, an important feature to represent the inertia in the energy system due to its long-lived capital stock. In case of shocks -(e.g., introduction of stringent climate policy), it is however possible to prematurely retire existing capital stock such as power plants or other energy conversion +MESSAGE tracks investments by vintage, an important feature to represent the inertia in the energy system due to its long-lived capital stock. In case of shocks +(e.g., introduction of stringent climate policy), it is however possible to prematurely retire existing capital stock such as power plants or other energy conversion technologies and switch to more suitable alternatives. -An important factor in this context that influences technology adoption in MESSAGE are technology diffusion constraints. Technology diffusion in MESSAGE is determined -by dynamic constraints that relate the construction of a technology added or the activity (level of production) of a technology in a period *t* to construction or the -activity in the previous period *t-1* (Messner and Strubegger, 1995 :cite:`messner_users_1995`, cf. section :ref:`upper_dynamic_constraint_capacity`). +An important factor in this context that influences technology adoption in |MESSAGEix| are technology diffusion constraints. Technology diffusion in |MESSAGEix| is determined +by dynamic constraints that relate the construction of a technology added or the activity (level of production) of a technology in a period *t* to construction or the +activity in the previous period *t-1* (Messner and Strubegger, 1995 :cite:`messner_users_1995`, cf. section :ref:`Dynamic constraints `). -While limiting the possibility of flip-flop behavior as is frequently observed in unconstrained Linear Programming (LP) models such as MESSAGE, a drawback of such hard -growth constraints is that the relative advantage of some technology over another technology is not taken into account and therefore even for very competitive technologies, -no rapid acceleration of technology diffusion is possible. In response to this limitation, so called flexible or soft dynamic constraints have been introduced into MESSAGE -(Keppo and Strubegger, 2010 :cite:`keppo_short_2010`). These allow faster technology diffusion at additional costs and therefore generate additional model flexibility +While limiting the possibility of flip-flop behavior as is frequently observed in unconstrained Linear Programming (LP) models such as |MESSAGEix|, a drawback of such hard +growth constraints is that the relative advantage of some technology over another technology is not taken into account and therefore even for very competitive technologies, +no rapid acceleration of technology diffusion is possible. In response to this limitation, so called flexible or soft dynamic constraints have been introduced into MESSAGE +(Keppo and Strubegger, 2010 :cite:`keppo_short_2010`). These allow faster technology diffusion at additional costs and therefore generate additional model flexibility while still reducing the flip-flop behavior and sudden penetration of technologies. :numref:`fig-difconstraint` below illustrates the maximum technology growth starting at a level of 1 in year *t* =0 for a set of five diffusion constraints which jointly lead to a soft constraint. @@ -35,5 +35,4 @@ while still reducing the flip-flop behavior and sudden penetration of technologi Illustration of maximum technology growth starting at a level of 1 in year t=0 for a set of soft diffusion constraints with effective growth rates r as shown in the legend. -For a more detailed description of the implementation of technology diffusion constraints, see the Annex Section :ref:`annex_convtech`. - +For a more detailed description of the implementation of technology diffusion constraints, see the Section :ref:`Dynamic constraints ` of the :doc:`|MESSAGEix| documentation `. diff --git a/energy/tech_addon.rst b/energy/tech_addon.rst index 8339cac..b64f8f0 100644 --- a/energy/tech_addon.rst +++ b/energy/tech_addon.rst @@ -1,12 +1,16 @@ -.. tech_addon: +.. _tech_addon: Add-on technologies =================== -Add-on technologies in the global model refer to a distinct formulation in MESSAGEix. The formulation is used to represent two main types of technical extensions/options for technologies. Add-on technologies provide additional modes of operation for a single or multiple technologies. They can also be used to depict emission mitigation options. +Add-on technologies in the global model refer to a distinct formulation in |MESSAGEix|. The formulation is used to represent two main types of technical extensions/options for technologies. Add-on technologies provide additional modes of operation for a single or multiple technologies. They can also be used to depict emission mitigation options. General description of add-on technologies ------------------------------------------ -Add-on technologies can be defined using all the same parameters as any other technology. What makes a technology an `add-on technology`, is the fact that their activity is bound to the activity of one or more other technologies, henceforth referred to as the parent technology. The mathematical formulation can be found `here `_. One of the main benefits of the add-on technology formulation, over specifying an alternative `mode`, is that it allows a single add-on technology to be coupled to the activity of multiple parent technologies. Furthermore, multiple add-on technologies can be linked to the activity of a single parent technology. +Add-on technologies can be defined using all the same parameters as any other technology. +What makes a technology an `add-on technology`, is the fact that their activity is bound to the activity of one or more other technologies, henceforth referred to as the parent technology. +The mathematical formulation can be found :ref:`here `. +One of the main benefits of the add-on technology formulation, over specifying an alternative `mode`, is that it allows a single add-on technology to be coupled to the activity of multiple parent technologies. +Furthermore, multiple add-on technologies can be linked to the activity of a single parent technology. Modelling Combined Heat Powerplants (CHPs) ------------------------------------------ diff --git a/further-reading.rst b/further-reading.rst new file mode 100644 index 0000000..978f125 --- /dev/null +++ b/further-reading.rst @@ -0,0 +1,6 @@ +Further reading +*************** + +.. bibliography:: /bibs/main.bib + :list: enumerated + :notcited: diff --git a/glossary.rst b/glossary.rst index ed7286c..c27403a 100644 --- a/glossary.rst +++ b/glossary.rst @@ -5,7 +5,5 @@ Glossary :sorted: ADVANCE - - A project finishing in 2016 designed to update the current generation of - IAMs and perform validation exercises. See the `ADVANCE website - `_ for more details. + A project finishing in 2016 designed to update the current generation of IAMs and perform validation exercises. + See the `ADVANCE website `_ for more details. diff --git a/index.rst b/index.rst index e0f32ea..2556127 100644 --- a/index.rst +++ b/index.rst @@ -1,27 +1,29 @@ -MESSAGE-GLOBIOM -=============== +MESSAGEix-GLOBIOM +================= -These webpages document the IIASA Integrated Assessment Modeling (IAM) framework, also referred to as MESSAGE-GLOBIOM, owing to the fact that the energy model MESSAGE and the land use model GLOBIOM are its most important components. MESSAGE-GLOBIOM 1.0 was developed for the quantification of the so-called Shared Socio-economic Pathways (SSPs) which are the first application of the IAM framework. +These pages document the IIASA Integrated Assessment Modeling (IAM) framework, also referred to as |MESSAGEix|-GLOBIOM, owing to the fact that the energy model |MESSAGEix| and the land use model GLOBIOM are its most important components. +|MESSAGEix|-GLOBIOM was developed for the quantification of the so-called Shared Socio-economic Pathways (SSPs) which are the first application of the IAM framework. -**This documentation is in part still under development and will be supplemented with additional information in certain sections.** +**This documentation is under constant development and is being expanded with additional information to reflect the latest changes in the modeling framework.** -When referring to MESSAGE-GLOBIOM 1.0 as described in this document, please use the following citations (Download :download:`ris `, :download:`BibTeX `): +When referring to |MESSAGEix|-GLOBIOM as described in this document, please use the following citations: [1]_ -* Krey V, Havlik P, Fricko O, Zilliacus J, Gidden M, Strubegger M, Kartasasmita G, Ermolieva T, Forsell N, Gusti M, Johnson N, Kindermann G, Kolp P, McCollum DL, Pachauri S, Rao S, Rogelj J, Valin H, Obersteiner M, Riahi K (2016) MESSAGE-GLOBIOM 1.0 Documentation. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria `http://data.ene.iiasa.ac.at/message-globiom/ `_. +.. bibliography:: + :list: bullet + :style: unsrt + :filter: key in {"message_globiom_2020", "fricko_havlik_2017"} -* Fricko O, Havlik P, Rogelj J, Klimont Z, Gusti M, Johnson N, Kolp P, Strubegger M, Valin H, Amann M, Ermolieva T, Forsell N, Herrero M, Heyes C, Kindermann G, Krey V, McCollum DL, Obersteiner M, Pachauri S, Rao S, Schmid E, Schoepp W, Riahi K (2017) The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century. Global Environmental Change, Volume 42, Pages 251-26, `DOI:10.1016/j.gloenvcha.2016.06.004 `_. +.. [1] Download these citations in :download:`RIS ` or :download:`BibTeX ` format (web only). -The MESSAGE-GLOBIOM Integrated Assessment Model is based on the |MESSAGEix| -framework, an open-source energy systems optimization modelling environment -including macro-economic feedback using a stylized computable general -equilibrium model. -When referring to the software underpinning MESSAGE-GLOBIOM rather than the data -or specific assessments, please use the following citation: +The |MESSAGEix|-GLOBIOM Integrated Assessment Model is based on the |MESSAGEix| framework, an open-source energy systems optimization modelling environment including macro-economic feedback using a stylized computable general equilibrium model. +When referring to the software underpinning |MESSAGEix|-GLOBIOM rather than the data or specific assessments, please see the :ref:`“User guidelines and notice” section ` of the documentation, which indicates to use at least the following citation: -* Huppmann D, Gidden M, Fricko O, Kolp P, Orthofer C, Pimmer M, Kushin N, Vinca A, Mastrucci A, Riahi K, Krey V (2019) The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp): An open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development. Environmental Modelling & Software, Volume 112, Pages 143-156, `DOI:0.1016/j.envsoft.2018.11.012 `_. +.. bibliography:: + :list: bullet + :style: unsrt + :filter: key == "huppmann_2019_messageix" and not cited - -We thank Edward Byers, Jessica Jewell, Simon C. Parkinson, Narasimha D. Rao for their valuable comments that helped improving this manuscript. +We thank Edward Byers, Jessica Jewell, Ruslana Palatnik, Narasimha D. Rao, and Fabio Sferra for their valuable comments that helped improving this manuscript. .. toctree:: :maxdepth: 1 @@ -34,13 +36,19 @@ We thank Edward Byers, Jessica Jewell, Simon C. Parkinson, Narasimha D. Rao for water/index emissions/index climate/index - z_bibliography annex/index + further-reading + z_bibliography + +.. Under development; excluded. + See also the exclude_patterns setting in conf.py. + glossary -.. toctree:: - :hidden: +.. Leave these lines commented for releases; uncommented during development/on + `master`. - _extra/index + .. toctree:: + :hidden: -.. |MESSAGEix| replace:: MESSAGE\ :emphasis:`ix` + _extra/index diff --git a/macro.rst b/macro.rst index 25dd9d2..3ff121a 100644 --- a/macro.rst +++ b/macro.rst @@ -8,4 +8,4 @@ MACRO is a macroeconomic model maximizing the intertemporal utility function of MACRO's production function includes six commercial energy demand categories represented in MESSAGE. To optimize, MACRO requires cost information for each demand category. The exact definitions of these costs as a function over all positive quantities of energy cannot be given in closed form because each point of the function would be a result of a full MESSAGE run. However, the optimality conditions implicit in the formulation of MACRO only require the functional values and its derivatives at the optimal point to be consistent between the two models. Since these requirements are therefore only local, most functions with this feature will simulate the combined energy-economic system in the neighborhood of the optimal point. The regional costs (of energy use and imports) and revenues (from energy exports) of providing energy in MACRO are approximated by a Taylor expansion to first order of the energy system costs as calculated by MESSAGE. From an initial MESSAGE model run, the total energy system cost (including costs/revenues from energy trade) and additional abatement costs (e.g., abatement costs from non-energy sources) as well as the shadow prices of the six commercial demand categories by region are passed to MACRO. In addition to the economic implications of energy trade, the data exchange from MESSAGE to MACRO may also include the revenues or costs of trade in GHG permits. -For a more elaborate description of MACRO's system of equations please consult the `MACRO section `_ of the `MESSAGEix documentation `_. Details on the implementation of MACRO, its parameterization and the calibration procedure can be found in the :ref:`annex_macro`. +Consult the :doc:`MACRO section ` of the :doc:`MESSAGEix documentation ` for a description of the MACRO system of equations, its implementation in :mod:`message_ix`, parameterization, and calibration procedure. diff --git a/overview/index.rst b/overview/index.rst index e6215da..be1c81b 100755 --- a/overview/index.rst +++ b/overview/index.rst @@ -2,15 +2,15 @@ Overview ============== -The IIASA IAM framework consists of a combination of five different models or modules - the energy model MESSAGE, the land use model GLOBIOM, the air pollution and GHG model GAINS, the aggregated macro-economic model MACRO and the simple climate model MAGICC - which complement each other and are specialized in different areas. All models and modules together build the IIASA IAM framework, also referred to as MESSAGE-GLOBIOM owing to the fact that the energy model MESSAGE and the land use model GLOBIOM are its central components. The five models provide input to and iterate between each other during a typical scenario development cycle. Below is a brief overview of how the models interact with each other, specifically in the context of developing the SSP scenarios. +The IIASA IAM framework consists of a combination of five different models or modules - the energy model |MESSAGEix|, the land use model GLOBIOM, the air pollution and GHG model GAINS, the aggregated macro-economic model MACRO and the simple climate model MAGICC - which complement each other and are specialized in different areas. All models and modules together build the IIASA IAM framework, also referred to as |MESSAGEix|-GLOBIOM owing to the fact that the energy model |MESSAGEix| and the land use model GLOBIOM are its central components. The five models provide input to and iterate between each other during a typical scenario development cycle. Below is a brief overview of how the models interact with each other, specifically in the context of developing the SSP scenarios. -MESSAGE (Huppmann et al., 2019 :cite:`huppmann_2019_messageix`) represents the core of the IIASA IAM framework (:numref:`fig-iiasaiam`) and its main task is to optimize the energy system so that it can satisfy specified energy demands at the lowest costs. MESSAGE carries out this optimization in an iterative setup with MACRO, a single sector macro-economic model, which provides estimates of the macro-economic demand response that results from energy system and services costs computed by MESSAGE. For the six commercial end-use demand categories depicted in MESSAGE (see :ref:`demand`), based on demand prices MACRO will adjust useful energy demands, until the two models have reached equilibrium (see :ref:`macro`). This iteration reflects price-induced energy efficiency adjustments that can occur when energy prices change. MESSAGE can represent different energy- and climate-related :ref:`policy_overview`. +|MESSAGEix| (Huppmann et al., 2019 :cite:`huppmann_2019_messageix`) represents the core of the IIASA IAM framework (:numref:`fig-iiasaiam`) and its main task is to optimize the energy system so that it can satisfy specified energy demands at the lowest costs. MESSAGE carries out this optimization in an iterative setup with MACRO, a single sector macro-economic model, which provides estimates of the macro-economic demand response that results from energy system and services costs computed by |MESSAGEix|. For the six commercial end-use demand categories depicted in MESSAGE (see :ref:`demand`), based on demand prices MACRO will adjust useful energy demands, until the two models have reached equilibrium (see :ref:`macro`). This iteration reflects price-induced energy efficiency adjustments that can occur when energy prices change. MESSAGE can represent different energy- and climate-related :ref:`policy_overview`. -GLOBIOM provides MESSAGE with information on land use and its implications, including the availability and cost of bioenergy, and availability and cost of emission mitigation in the AFOLU (Agriculture, Forestry and Other Land Use) sector (see :ref:`globiom`). To reduce computational costs, MESSAGE iteratively queries a GLOBIOM emulator which provides an approximation of land-use outcomes during the optimization process instead of requiring the GLOBIOM model to be rerun iteratively. Only once the iteration between MESSAGE and MACRO has converged, the resulting bioenergy demands along with corresponding carbon prices are used for a concluding analysis with the full-fledged GLOBIOM model. This ensures full consistency of the results from MESSAGE and GLOBIOM, and also allows producing a more extensive set of land-use related indicators, including spatially explicit information on land use. +GLOBIOM provides |MESSAGEix| with information on land use and its implications, including the availability and cost of bioenergy, and availability and cost of emission mitigation in the AFOLU (Agriculture, Forestry and Other Land Use) sector (see :ref:`globiom`). To reduce computational costs, MESSAGE iteratively queries a GLOBIOM emulator which provides an approximation of land-use outcomes during the optimization process instead of requiring the GLOBIOM model to be rerun iteratively. Only once the iteration between |MESSAGEix| and MACRO has converged, the resulting bioenergy demands along with corresponding carbon prices are used for a concluding analysis with the full-fledged GLOBIOM model. This ensures full consistency of the results from MESSAGE and GLOBIOM, and also allows producing a more extensive set of land-use related indicators, including spatially explicit information on land use. -Air pollution implications of the energy system are accounted for in MESSAGE by applying technology-specific air pollution coefficients derived from the GAINS model (see :ref:`gains`). This approach has been applied to the SSP process (Rao et al., 2017 :cite:`rao_2017_SSP_airpollution`). Alternatively, GAINS can be run ex-post based on |MESSAGEix|-GLOBIOM scenarios to estimate air pollution emissions, concentrations and the related health impacts. This approach allows analyzing different air pollution policy packages (e.g., current legislation, maximum feasible reduction), including the estimation of costs for air pollution control measures. Examples for applying this way of linking |MESSAGEix|-GLOBIOM and GAINS can be found in McCollum et al. (2018 :cite:`mccollum_2018_investment`) and Grubler et al. (2018 :cite:`grubler_2018_led`). +Air pollution implications of the energy system are accounted for in |MESSAGEix| by applying technology-specific air pollution coefficients derived from the GAINS model (see :ref:`gains`). This approach has been applied to the SSP process (Rao et al., 2017 :cite:`rao_2017_SSP_airpollution`). Alternatively, GAINS can be run ex-post based on |MESSAGEix|-GLOBIOM scenarios to estimate air pollution emissions, concentrations and the related health impacts. This approach allows analyzing different air pollution policy packages (e.g., current legislation, maximum feasible reduction), including the estimation of costs for air pollution control measures. Examples for applying this way of linking |MESSAGEix|-GLOBIOM and GAINS can be found in McCollum et al. (2018 :cite:`mccollum_2018_investment`) and Grubler et al. (2018 :cite:`grubler_2018_led`). -In general, cumulative global carbon emissions from all sectors are constrained at different levels, with equivalent pricing applied to other GHGs, to reach the desired radiative forcing levels (cf. right-hand side :numref:`fig-iiasaiam`). The climate constraints are thus taken up in the coupled MESSAGE-GLOBIOM optimization, and the resulting carbon price is fed back to the full-fledged GLOBIOM model for full consistency. Finally, the combined results for land use, energy, and industrial emissions from MESSAGE and GLOBIOM are merged and fed into MAGICC (see :ref:`magicc`), a global carbon-cycle and climate model, which then provides estimates of the climate implications in terms of atmospheric concentrations, radiative forcing, and global-mean temperature increase. Importantly, climate impacts and impacts of the carbon cycle are -- depending on the specific application -- currently only partly accounted for in the IIASA IAM framework. The entire framework is linked to an online database infrastructure which allows straightforward visualisation, analysis, comparison and dissemination of results (Riahi et al., 2017 :cite:`riahi_shared_2017`). +In general, cumulative global carbon emissions from all sectors are constrained at different levels, with equivalent pricing applied to other GHGs, to reach the desired radiative forcing levels (cf. right-hand side :numref:`fig-iiasaiam`). The climate constraints are thus taken up in the coupled |MESSAGEix|-GLOBIOM optimization, and the resulting carbon price is fed back to the full-fledged GLOBIOM model for full consistency. Finally, the combined results for land use, energy, and industrial emissions from |MESSAGEix| and GLOBIOM are merged and fed into MAGICC (see :ref:`magicc`), a global carbon-cycle and climate model, which then provides estimates of the climate implications in terms of atmospheric concentrations, radiative forcing, and global-mean temperature increase. Importantly, climate impacts and impacts of the carbon cycle are -- depending on the specific application -- currently only partly accounted for in the IIASA IAM framework. The entire framework is linked to an online database infrastructure which allows straightforward visualisation, analysis, comparison and dissemination of results (Riahi et al., 2017 :cite:`riahi_shared_2017`). The scientific software underlying the global MESSAGE-GLOBIOM model is called the |MESSAGEix| framework, an open-source, versatile implementation of a linear optimization problem, with the option of coupling to the computable general equilibrium (CGE) model MACRO to incorporate the effect of price changes on economic activity and demand for commodities and resources. |MESSAGEix| is integrated with the *ix modeling platform* (ixmp), a "data warehouse" for version control of reference timeseries, input data and model results. ixmp provides interfaces to the scientific programming languages Python and R for efficient, scripted workflows for data processing and visualisation of results (Huppmann et al., 2019 :cite:`huppmann_2019_messageix`). @@ -27,5 +27,3 @@ The scientific software underlying the global MESSAGE-GLOBIOM model is called th spatial temporal policy/index - -.. |MESSAGEix| replace:: MESSAGE\ :emphasis:`ix` diff --git a/overview/policy/index.rst b/overview/policy/index.rst index abd7058..14a43eb 100644 --- a/overview/policy/index.rst +++ b/overview/policy/index.rst @@ -2,7 +2,7 @@ Policies ======== -A number of different energy- and climate-related policies are, depending on the scenario setup and the research question addressed, explicitly represented in MESSAGE. This includes the following list of policies: +A number of different energy- and climate-related policies are, depending on the scenario setup and the research question addressed, explicitly represented in |MESSAGEix|. This includes the following list of policies: * GHG emission pricing * GHG emission caps and trading emission allowances diff --git a/overview/spatial.rst b/overview/spatial.rst index 6a288d7..6b0a01f 100755 --- a/overview/spatial.rst +++ b/overview/spatial.rst @@ -3,21 +3,22 @@ Regions ******* -The combined MESSAGE-GLOBIOM framework has global coverage and divides the world into 11 regions which are also the native regions of the MESSAGE model (see :numref:`fig-reg` and :numref:`tab-reg` below). GLOBIOM natively operates at the level of 30 regions which in the linkage to MESSAGE are aggregated to the 11 regions as listed in :numref:`tab-globiomreg`. +The combined |MESSAGEix|-GLOBIOM framework has global coverage and divides the world into 11 regions which are also the native regions of the |MESSAGEix| model (see :numref:`fig-reg` and :numref:`tab-reg` below). GLOBIOM natively operates at the level of 30 regions which in the linkage to |MESSAGEix| are aggregated to the 11 regions as listed in :numref:`tab-globiomreg`. .. _fig-reg: .. figure:: /_static/MESSAGE_regions.png :width: 800px - Map of 11 MESSAGE-GLOBIOM regions inclduing their aggregation to the four regions used in the Representative Concentration Pathways (RCPs). + Map of 11 |MESSAGEix|-GLOBIOM regions including their aggregation to the four regions used in the Representative Concentration Pathways (RCPs). -The country definitions of the 11 MESSAGE regions are described in the table below (:numref:`tab-reg`). In some scenarios, the MESSAGE region of FSU is disaggregated into four sub-regions resulting in a 14-region MESSAGE model. +The country definitions of the 11 |MESSAGEix| regions are described in the table below (:numref:`tab-reg`). In some scenarios, the |MESSAGEix| region of FSU (Former Soviet Union) is disaggregated into four sub-regions resulting in a 14-region |MESSAGEix| model. .. _tab-reg: -.. list-table:: Listing of 11 regions used in MESSAGE-GLOBIOM, including their country definitions. +.. list-table:: Listing of 11 regions used in |MESSAGEix|-GLOBIOM, including their country definitions. + :widths: 13 18 69 :header-rows: 1 - * - 11 MESSAGE regions + * - MESSAGE regions - Definition - List of countries * - **NAM** @@ -25,7 +26,7 @@ The country definitions of the 11 MESSAGE regions are described in the table bel - Canada, Guam, Puerto Rico, United States of America, Virgin Islands * - **WEU** - Western Europe - - Andorra, Austria, Azores, Belgium, Canary Islands, Channel Islands, Cyprus, Denmark, Faeroe Islands, Finland, France, Germany, Gibraltar, Greece, Greenland, Iceland, Ireland, Isle of Man, Italy, Liechtenstein, Luxembourg, Madeira, Malta, Monaco, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, United Kingdom | + - Andorra, Austria, Azores, Belgium, Canary Islands, Channel Islands, Cyprus, Denmark, Faeroe Islands, Finland, France, Germany, Gibraltar, Greece, Greenland, Iceland, Ireland, Isle of Man, Italy, Liechtenstein, Luxembourg, Madeira, Malta, Monaco, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, United Kingdom * - **PAO** - Pacific OECD - Australia, Japan, New Zealand @@ -54,14 +55,15 @@ The country definitions of the 11 MESSAGE regions are described in the table bel - Sub-Saharan Africa - Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Cote d'Ivoire, Congo, Democratic Republic of Congo, Djibouti, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Reunion, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, Saint Helena, Swaziland, Tanzania, Togo, Uganda, Zambia, Zimbabwe | -In addition to the 11 geographical regions, in MESSAGE there is a global trade region where market clearing of global energy markets is happening and international shipping bunker fuel demand, uranium resource extraction and the nuclear fuel cycle are represented. +In addition to the 11 geographical regions, in the glboal |MESSAGEix| model there is a global trade region where market clearing of global energy markets is happening and international shipping bunker fuel demand, uranium resource extraction and the nuclear fuel cycle are represented. .. _tab-globiomreg: -.. list-table:: Listing of 30 regions used in GLOBIOM, including their country definitions and the mapping to the 11 regions of the combined MESSAGE-GLOBIOM model. +.. list-table:: Listing of 30 regions used in GLOBIOM, including their country definitions and the mapping to the 11 regions of the combined |MESSAGEix|-GLOBIOM model. + :widths: 13 17 70 :header-rows: 1 - * - 11 MESSAGE regions - - 30 GLOBIOM regions + * - MESSAGE regions + - GLOBIOM regions - List of countries * - **NAM** - Canada diff --git a/overview/temporal.rst b/overview/temporal.rst index 434ea3f..b6c59c8 100755 --- a/overview/temporal.rst +++ b/overview/temporal.rst @@ -1,7 +1,7 @@ Time steps ================= -MESSAGE models the time horizon 2010 to 2110 generally in 10-year periods (2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100, 2110), using 2010 as the base year. The 2020 period is partly calibrated so far, some recent trends are included in this time period, but some flexibility remains. The reporting years are the final years of periods which implies that investments that lead to the capacities in the reporting year are the average annual investments over the entire period the reporting year belongs to. In some model versions, the model has been calibrated to 2015 running with 5-year modeling periods by the middle of the Century (2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060) and 10-year periods between 2060 and 2110. +In global |MESSAGEix| models the time horizon of 2010 to 2110 is generally subdivided into 5 or 10-year periods, using 2010 or 2015 as the base year. The 2020 period is partly calibrated so far, some recent trends are included in this time period, but some flexibility remains. The reporting years are the final years of periods which implies that investments that lead to the capacities in the reporting year are the average annual investments over the entire period the reporting year belongs to. In recent model versions, the model has been calibrated to 2015 running with 5-year modeling periods until the middle of the century (2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060) and 10-year periods between 2060 and 2110. -MESSAGE can both operate perfect foresight over the entire time horizon, limited foresight (e.g., two or three periods into the future) or myopically, optimizing one period at a time (Keppo and Strubegger, 2010 :cite:`keppo_short_2010`) (see `Mathematical Specification `_ for more details). Most frequently MESSAGE is run with perfect foresight, but for specific applications such as delayed participation in a global climate regime without anticipation (Krey and Riahi, 2009 :cite:`krey_implications_2009`; O'Neill et al., 2010 :cite:`oneill_mitigation_2010`) limited foresight is used. +|MESSAGEix| can both operate perfect foresight over the entire time horizon, limited foresight (e.g., two or three periods into the future) or myopically, optimizing one period at a time (Keppo and Strubegger, 2010 :cite:`keppo_short_2010`) (see `Mathematical Specification `_ for more details). Most frequently |MESSAGEix| is run with perfect foresight, but for specific applications such as delayed participation in a global climate regime without anticipation (Krey and Riahi, 2009 :cite:`krey_implications_2009`; O'Neill et al., 2010 :cite:`oneill_mitigation_2010`) limited foresight is used. -GLOBIOM models the time horizon 2000 to 2100 in 10 year time steps (2000, 2010, 2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100) with the year 2000 being the base year of the model. The model is recursive-dynamic, i.e. it is solved for each period individually and then passes on results to the subsequent periods. The linkage between MESSAGE and GLOBIOM relies on the model results of the periods 2020 to 2100. +GLOBIOM models the time horizon 2000 to 2100 in 10 year time steps (2000, 2010, 2020, 2030, 2040, 2050, 2060, 2070, 2080, 2090, 2100) with the year 2000 being the base year of the model. The model is recursive-dynamic, i.e. it is solved for each period individually and then passes on results to the subsequent periods. The linkage between |MESSAGEix| and GLOBIOM relies on the model results of the periods 2020 to 2100. diff --git a/socio_econ/narratives.rst b/socio_econ/narratives.rst index 927af07..9518821 100755 --- a/socio_econ/narratives.rst +++ b/socio_econ/narratives.rst @@ -3,7 +3,7 @@ SSP narratives ============== -Narratives have been developed for the Shared Socioeconomic Pathways (SSPs) (O’Neill et al., 2015 :cite:`oneill_roads_2015`). These descriptions of alternative futures of societal development span a range of possible worlds that stretch along two climate-change-related dimensions: mitigation and adaptation challenges. The SSPs reflect five different developments of the world that are characterized by varying levels of global challenges (see `Riahi et al., 2017 `_ :cite:`riahi_shared_2017` for an overview). In the following, the three narratives that have been translated into quantitative scenarios with MESSAGE-GLOBIOM are presented (Fricko et al., 2017 :cite:`fricko_marker_2017`): +Narratives have been developed for the Shared Socioeconomic Pathways (SSPs) (O’Neill et al., 2015 :cite:`oneill_roads_2015`). These descriptions of alternative futures of societal development span a range of possible worlds that stretch along two climate-change-related dimensions: mitigation and adaptation challenges. The SSPs reflect five different developments of the world that are characterized by varying levels of global challenges (see Riahi et al., 2017 :cite:`riahi_shared_2017` for an overview). In the following, the three narratives that have been translated into quantitative scenarios with MESSAGE-GLOBIOM are presented (Fricko et al., 2017 :cite:`fricko_marker_2017`): SSP1 Narrative: Sustainability — Taking the green road ------------------------------------------------------ diff --git a/z_bibliography.rst b/z_bibliography.rst index 5bf74d6..8476a9f 100644 --- a/z_bibliography.rst +++ b/z_bibliography.rst @@ -1,13 +1,8 @@ -References -********** +.. only:: html or text + + Bibliography + ************ .. bibliography:: /bibs/main.bib :style: plain :cited: - -Further reading -=============== - -.. bibliography:: /bibs/main.bib - :list: enumerated - :notcited: