Merge pull request #1343 from NREL/trg_update

Update Technical Reference Guide to Final Publication

.github/workflows/config.yml

@@ -364,6 +364,7 @@ jobs:
         with:
           working_directory: docs/technical_reference_guide
           root_file: ResStockTechnicalReferenceGuide.tex
+          args: -pdf -latexoption=-file-line-error -latexoption=-interaction=nonstopmode -output-directory=_build
 
       - name: Save documentation
         uses: actions/upload-artifact@v4

.gitignore

@@ -1,19 +1,5 @@
 /docs/technical_development_guide/_build
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.aux
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.bcf
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.lof
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.log
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.lot
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.out
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.pdf
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.run.xml
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.toc
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.upa
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.bbl
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.blg
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.fdb_latexmk
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.fls
-/docs/technical_reference_guide/ResStockTechnicalReferenceGuide.upb
+/docs/technical_reference_guide/_build
 /lib
 /measures/UpgradeCosts/tests/in*
 /measures/UpgradeCosts/tests/*.xml

docs/technical_reference_guide/1_Introduction.tex

@@ -12,7 +12,7 @@ \section{Overview and Primary Use Applications}
 
 ResStock answers two primary questions: (1) How and when is energy used in the U.S.~residential building stock? and (2) What are the impacts of technological and behavioral changes in U.S.~homes? Specifically, ResStock quantifies energy use across geographical locations, demographic groups, building types, fuels, end uses, and time of day. Additionally, it details the impact of efficiency, fuel changes, or flexibility measures: total changes in the amount of energy used by measure; where or in what use cases efficiency or technology change measures save energy; when or at what times of day savings occur; and which building stock or demographic segments have the biggest savings potential.
 
-This type of building stock energy model can be conducted using a range of approaches, varying on a spectrum from simple representation and fast execution or complex representation and slow execution. Each approach has benefits and trade-offs. The National Energy Modeling System used by the EIA is an example of a simple, fast method. This system models the entire U.S.~energy system at the census region level, and its results for the building stock have low spatial, temporal, and subsector granularity. On the other hand, modeling each individual building within the building stock is an example of a complex, slow method. This approach is impossible to implement in practice due to the lack of building-level data necessary to develop the model, and can lead to false confidence in results if not underpinned by appropriate data. Additionally, if appropriate data did exist and the model could be developed, this approach would offer a high granularity of results, but gives more detail than is needed for most applications and is highly impractical to update or run frequently.
+This type of building stock energy model can be conducted using a range of approaches, varying on a spectrum from simple representation and fast execution or complex representation and slow execution. Each approach has benefits and trade-offs. The National Energy Modeling System used by the EIA is an example of a simple, fast method. This system models the entire U.S.~energy system at the census region level, and its results for the building stock have low spatial, temporal, and subsector granularity. On the other hand, modeling each individual building within the building stock is an example of a complex, slow method. This approach is impossible to implement in practice due to the lack of building-level data necessary to develop the model, and can lead to false confidence in results if not underpinned by appropriate data. Additionally, if appropriate data did exist and the model could be developed, this approach would offer a high granularity of results, but would provide more detail than needed for most applications and would be highly impractical to update or run frequently.
 
 The ResStock approach is positioned between these two extremes, providing highly granular housing stock data to capture the diversity of housing and occupants while maintaining a usable execution speed. Three advantages of the ResStock approach are: (1) subhourly detail; (2) modeling of upgrade measure interaction, controls, and demand flexibility; and (3) the ability to post-process the data to slice results (e.g., by location, household income, fuel types, building size) and extract a wide array of insights from the simulations, including distributional impacts---how costs and benefits are distributed across different groups of households. This approach strikes a balance by presenting enough information to answer its two driving questions while remaining computationally tractable.