Moved TDR from Model Concept to User Guide; Moved Multistage and main…

…tenance from Model_concept to Model Reference
lbonaldo · Mar 5, 2024 · 6c277d2 · 6c277d2
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Showing 7 changed files with 8 additions and 18 deletions.
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -2,3 +2,4 @@
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 GenX = "5d317b1e-30ec-4ed6-a8ce-8d2d88d7cfac"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
diff --git a/docs/make.jl b/docs/make.jl
@@ -40,9 +40,6 @@ pages = OrderedDict(
         "Objective Function" => "Model_Concept_Overview/objective_function.md",
         "Power Balance" => "Model_Concept_Overview/power_balance.md",
         "Slack Variables for Policies" => "Model_Concept_Overview/slack_variables_overview.md",
-        "Maintenance" => "Model_Concept_Overview/maintenance_overview.md",
-        "Time Domain Reduction" => "Model_Concept_Overview/TDR_overview.md",
-        "Multi-Stage Modeling" => "Model_Concept_Overview/multi_stage_overview.md",
     ],
     "Model Reference" => [
         "Core" => "Model_Reference/core.md",
@@ -75,12 +72,14 @@ pages = OrderedDict(
             "Scheduled maintenance for various resources" => "Model_Reference/Resources/maintenance.md",
             "Resource types" => "Model_Reference/Resources/resource.md"
         ],
+        "Maintenance" => "Model_Reference/maintenance_overview.md",
         "Policies" => "Model_Reference/policies.md",
         "Solver Configurations" => "Model_Reference/solver_configuration_api.md",
         "Inputs Functions" => "Model_Reference/load_inputs.md",
         "Utility Functions" => "Model_Reference/utility_functions.md",
         "TDR" => "Model_Reference/TDR.md",
         "Multi-stage" => [
+            "Multi-Stage Modeling Introduction" => "Model_Reference/Multi_Stage/multi_stage_overview.md",
             "Configure multi-stage inputs" => "Model_Reference/Multi_Stage/configure_multi_stage_inputs.md",
             "Model multi stage: Dual Dynamic Programming Algorithm" => "Model_Reference/Multi_Stage/dual_dynamic_programming.md",
             "Endogenous Retirement" => "Model_Reference/Multi_Stage/endogenous_retirement.md"

diff --git a/docs/src/Model_Concept_Overview/TDR_overview.md b/docs/src/Model_Concept_Overview/TDR_overview.md
diff --git a/..._Concept_Overview/multi_stage_overview.md → ...rence/Multi_Stage/multi_stage_overview.md b/..._Concept_Overview/multi_stage_overview.md → ...rence/Multi_Stage/multi_stage_overview.md
diff --git a/..._Concept_Overview/maintenance_overview.md → ...c/Model_Reference/maintenance_overview.md b/..._Concept_Overview/maintenance_overview.md → ...c/Model_Reference/maintenance_overview.md
diff --git a/docs/src/User_Guide/TDR_input.md b/docs/src/User_Guide/TDR_input.md
@@ -1,6 +1,8 @@
 # Time-domain reduction
 
-Modeling grid operations for each hour of the year can be computationally expensive for models with many zones and resources. Time-domain reduction is often employed in capacity expansion models as a way to balance model spatial and temporal resolution as well as representation of dispatch, while ensuring reasonable computational times. GenX allows the option of performing time-domain reduction on the user supplied time-series input data to produce a representative time series at the desired level of temporal resolution. The below table summarizes the list of parameters to be specified by the user to perform the time domain reduction implemented in GenX. These parameters are passed to GenX via the YAML file `time_domain_reduction_settings.yml`.
+Modeling grid operations for each hour of the year can be computationally expensive for models with many zones and resources. Rather than modeling and optimizing power grid operations at a high temporal resolution (e.g., hourly, over a full year) while evaluating new capacity investments, which can be computationally expensive for large-scale studies with several resources, it may be useful to consider a reduced temporal resolution to model annual grid operations. Time-domain reduction is often employed in capacity expansion models as a way to balance model spatial and temporal resolution as well as representation of dispatch, while ensuring reasonable computational times. Such a time-domain reduction is often employed in capacity expansion models as a way to balance model spatial and temporal resolution as well as representation of dispatch, while ensuring reasonable computational times. GenX allows the option of performing time-domain reduction on the user supplied time-series input data to produce a representative time series at the desired level of temporal resolution. The time-domain reduction method provided allows the user to automate these features while specifying the various parameters of the time-domain reduction 'clustering' algorithm to be used in formulating the resulting optimization model. The below table summarizes the list of parameters to be specified by the user to perform the time domain reduction implemented in GenX. These parameters are passed to GenX via the YAML file `time_domain_reduction_settings.yml`.
+
+It's also possible for GenX perform clustering separately from the optimization task. Check out the [Running the TDR](@ref) section for more information. 
 
 **Structure of the time\_domain\_reduction.yml file**
 

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -1,5 +1,6 @@
 ```@raw html
-<img width="600" src="assets/title.svg" style="padding-left: 50px; padding-top: 20px; display: block; border: none;"/>
+<img class="display-light-only" width="600" src="assets/title.svg" style="padding-left: 50px; padding-top: 20px; display: block; border: none;"/>
+<img class="display-dark-only" width="600" src="assets/title_white_text.svg" style="padding-left: 50px; padding-top: 20px; display: block; border: none;"/>
 ```
 
 ### Welcome to the GenX documentation!