minor grammar updates to osier chapter

docs/3-osier/31-inputs.tex

@@ -80,8 +80,8 @@ \subsubsection{Per-unit-energy}
 
 Some quantities of interest depend on the \textit{amount of energy produced} by
 each technology. For example, carbon emissions only occur when a coal or natural
-gas plant burns fuel. A general energy density may be in $\text{MWh} /
-\text{unit}$. The objective function for these quantities reads
+gas plant burns fuel. A general energy density may be in $\text{unit}/\text{MWh}$. 
+The objective function for these quantities reads
 \begin{align}
     \mathcal{E} &= \sum_g^G \xi_g \sum_t^T x_{g,t},
     \intertext{where}

docs/3-osier/33-dispatch-model.tex

@@ -81,12 +81,12 @@ \subsection{Hierarchical dispatch}
 \begin{align}
     x_{g,t} &= \text{max}\left(0, \text{min}\left(D_t, \textbf{CAP}_g\right)\right)\label{eq:std_tech_output}.
 \end{align}
-ß
+
 \noindent
 This equation guarantees that a standard technology will have a power output between
 zero and its rated capacity. In addition to Equation \ref{eq:std_tech_output},
 a ``ramping'' technology will calculate the maximum and minimum attainable power
-levels given its ramp rates and the problem's time resolution. The power output
+levels given its ramp rates, rated capacity, and the problem's time resolution. The power output
 is given by
 
 \begin{align}
@@ -96,14 +96,14 @@ \subsection{Hierarchical dispatch}
          P_{max} & x_{g,t-1} \leq \textbf{CAP}_g \leq D_t
      \end{cases}
      \intertext{where}
-     P_{min} &= \text{max}\left(0, \left(x_{g,t-1}-\rho_g^{down}\Delta \tau\right)\right),\nonumber\\
-     P_{max} &= \text{min}\left(\left(x_{g,t-1}+\rho_g^{up}\Delta \tau\right), \textbf{CAP}_g\right).\nonumber
+     P_{min} &= \text{max}\left(0, \left(x_{g,t-1}-\left(\rho_g^{down}\textbf{CAP}_g\right)\Delta \tau\right)\right),\nonumber\\
+     P_{max} &= \text{min}\left(\left(x_{g,t-1}+\left(\rho_g^{up}\textbf{CAP}_g\right)\Delta \tau\right), \textbf{CAP}_g\right).\nonumber
 \end{align}
 
-\textcolor{red}{$\rho_g$ is not the same $\rho_g$ as in the LP formulation! Maybe
-choose another variable and explain its meaning... It should be the "ramp up/down"
-which is the ramp rate times the capacity.}
-
+% \textcolor{red}{$\rho_g$ is not the same $\rho_g$ as in the LP formulation! Maybe
+% choose another variable and explain its meaning... It should be the "ramp up/down"
+% which is the ramp rate times the capacity.}
+\noindent
 Finally, a storage technology has a charging and discharging mode, depending on
 whether the current demand level is positive or negative. A storage technology
 extends Equation \ref{eq:std_tech_output} by checking that the storage unit has enough
@@ -137,7 +137,7 @@ \subsection{Hierarchical dispatch}
             \node (1) [lbblock]{\textbf{Sort technologies by marginal cost}}; 
             \node(2) [lbblock, below of =1] {\textbf{Start dispatch loop}};
             \node(3) [lbblock, below of=2] {\textbf{Calculate power output for
-            current technology}};
+            next technology}};
             \node(4) [lbblock, below of=3] {\textbf{Decrement current demand
             value \\ by power output}};
             \node(5) [lbblock, below of=4] {\textbf{Reached last technology?}};

docs/3-osier/34-mga.tex

@@ -38,7 +38,7 @@ \section{\acs{mga} with \acl{moo}}
 \end{enumerate}
 \noindent
 Figure \ref{fig:nd-mga} and Figure \ref{fig:3d-mga} show ``near-feasible
-fronts'' and interior points with 10 percent slack for a 2-D and 3-D Pareto
+fronts'' and interior points with 20 percent slack for a 2-D and 3-D Pareto
 front, respectively. Figure \ref{fig:nd-mga} shows clearly that only points
 within the near-optimal space (gray) are considered. Illustrating this behavior
 in three dimensions (and above) is considerably more difficult. The 3-D interior
@@ -68,7 +68,7 @@ \section{\acs{mga} with \acl{moo}}
 \end{figure}
 
 \subsection{Farthest First Traversal}
-Previous studies emphasized that a key benefit of \ac{mga} with \ac{hsj} is
+Previous studies emphasized that a key benefit of \ac{mga} is
 obtaining a set of near-optimal solutions that are maximally different in design
 space \cite{decarolis_modelling_2016, yue_review_2018-1}. Instead of
 constraining a linear program to guarantee a maximally-different solution set.
@@ -86,7 +86,7 @@ \subsection{Farthest First Traversal}
 Figure \ref{fig:mga-fft} demonstrates \ac{mga} with
 ``farthest-first-traversal.'' The left plot in Figure \ref{fig:mga-fft} shows
 the objective space for the same problem as in Figure \ref{fig:nd-mga}. The plot
-on the right shows the design space for same problem. Both plots show the Pareto
+on the right shows the corresponding design space. Both plots show the Pareto
 front as red dots. The colored dots represent the points selected by the ``farthest-first-traversal''
 algorithm. These points are connected by similarly colored arrows in the design space plot. The arrow
 color corresponds to the color of the next selected point (i.e., the next farthest point).

docs/3-osier/35-limitations.tex

@@ -9,8 +9,8 @@ \section{Limitations of \ac{osier}}
     optimize multiple decades into the future.
     \item \ac{osier} does not model interactions between the environment and the
     energy system. Therefore, temperature feedbacks and geoengineering
-    technologies cannot be modeled adequately. Although, \ac{osier} could handle
-    a negative emissions technology.
+    technologies cannot be modeled adequately. 
+    % Although, \ac{osier} could handle a negative emissions technology.
     \item Currently, \ac{osier}'s dispatch models can only model one energy carrier. That is, technologies
     could produce heat (measured in MW$_{th}$) or electricity. But there is no method
     to convert between the two endogenously.

docs/acros.tex

@@ -5,7 +5,7 @@
 \acro{eroi}[EROI]{energy return on investment}
 \acro{milp}[MILP]{mixed-integer linear programming}
 \acrodefplural{milp}[MILPs]{mixed-integer linear programs}
-\acro{osier}[\texttt{Osier}]{Open source multi-objective energy system framework}
+\acro{osier}[\texttt{Osier}]{Open-source multi-objective energy system framework}
 \acro{dapl}[DAPL]{Dakota Access Pipeline}
 \acro{temoa}[\texttt{Temoa}]{Tools for Energy Model Optimization and Analysis}
 \acro{pygen}[\texttt{PyGenesys}]{Python for Generating Energy Systems}