build based on 4d35a79

dev/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-10-29T06:56:50","documenter_version":"1.7.0"}}
+{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-10-29T08:09:46","documenter_version":"1.7.0"}}

dev/20-tutorials/index.html

@@ -6,17 +6,17 @@
 connection = DBInterface.connect(DuckDB.DB)
 read_csv_folder(connection, input_dir; schemas = TulipaEnergyModel.schema_per_table_name)
 energy_problem = run_scenario(connection)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnergyProblem:
-  - Time creating internal structures (in seconds): 8.477514402
-  - Time computing constraints partitions (in seconds): 4.29620603
-  - Time creating dataframes (in seconds): 1.516605841
-  - Time creating variables indices (in seconds): 1.653e-6
+  - Time creating internal structures (in seconds): 8.928622023
+  - Time computing constraints partitions (in seconds): 4.490356425
+  - Time creating dataframes (in seconds): 1.455075528
+  - Time creating variables indices (in seconds): 1.983e-6
   - Model created!
-    - Time for  creating the model (in seconds): 15.651206269
+    - Time for  creating the model (in seconds): 16.137012815
     - Number of variables: 368
     - Number of constraints for variable bounds: 368
     - Number of structural constraints: 432
   - Model solved! 
-    - Time for  solving the model (in seconds): 2.497279289
+    - Time for  solving the model (in seconds): 2.60770982
     - Termination status: OPTIMAL
     - Objective value: 269238.4382375954
 </code></pre><p>The <code>energy_problem</code> variable is of type <code>EnergyProblem</code>. For more details, see the <a href="../95-reference/#TulipaEnergyModel.EnergyProblem">documentation for that type</a> or the section <a href="../10-how-to-use/#structures">Structures</a>.</p><p>That&#39;s all it takes to run a scenario! To learn about the data required to run your own scenario, see the <a href="../10-how-to-use/#input">Input section</a> of <a href="../10-how-to-use/#how-to-use">How to Use</a>.</p><h3 id="Manually-running-each-step"><a class="docs-heading-anchor" href="#Manually-running-each-step">Manually running each step</a><a id="Manually-running-each-step-1"></a><a class="docs-heading-anchor-permalink" href="#Manually-running-each-step" title="Permalink"></a></h3><p>If we need more control, we can create the energy problem first, then the optimization model inside it, and finally ask for it to be solved.</p><pre><code class="language-julia hljs">using DuckDB, TulipaIO, TulipaEnergyModel
@@ -25,10 +25,10 @@
 connection = DBInterface.connect(DuckDB.DB)
 read_csv_folder(connection, input_dir; schemas = TulipaEnergyModel.schema_per_table_name)
 energy_problem = EnergyProblem(connection)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnergyProblem:
-  - Time creating internal structures (in seconds): 0.13342404
-  - Time computing constraints partitions (in seconds): 0.00018746
-  - Time creating dataframes (in seconds): 0.005203897
-  - Time creating variables indices (in seconds): 1.683e-6
+  - Time creating internal structures (in seconds): 0.136561249
+  - Time computing constraints partitions (in seconds): 0.000190425
+  - Time creating dataframes (in seconds): 0.00638123
+  - Time creating variables indices (in seconds): 1.794e-6
   - Model not created!
   - Model not solved!
 </code></pre><p>The energy problem does not have a model yet:</p><pre><code class="language-julia hljs">energy_problem.model === nothing</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">true</code></pre><p>To create the internal model, we call the function <a href="../95-reference/#TulipaEnergyModel.create_model!-Tuple{Any}"><code>create_model!</code></a>.</p><pre><code class="language-julia hljs">create_model!(energy_problem)
@@ -82,7 +82,7 @@
   :max_energy_inter_rp    =&gt; <span class="sgr1">0×4 DataFrame</span>…
   :storage_level_intra_rp =&gt; <span class="sgr1">0×5 DataFrame</span>…
   :highest_in             =&gt; <span class="sgr1">0×5 DataFrame</span>…
-  :units_on               =&gt; <span class="sgr1">0×1 DataFrame</span>…
+  :units_on               =&gt; <span class="sgr1">0×7 DataFrame</span>…
   :highest_in_out         =&gt; <span class="sgr1">72×7 DataFrame</span>…
   :flows                  =&gt; <span class="sgr1">360×9 DataFrame</span>…
   :lowest                 =&gt; <span class="sgr1">360×5 DataFrame</span>…
@@ -93,7 +93,7 @@
 variables = compute_variables_indices(dataframes)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">Dict{Symbol, TulipaVariable} with 5 entries:
   :is_charging            =&gt; TulipaVariable(<span class="sgr1">0×5 DataFrame</span>…
   :flow                   =&gt; TulipaVariable(<span class="sgr1">360×9 DataFrame</span>…
-  :units_on               =&gt; TulipaVariable(<span class="sgr1">0×1 DataFrame</span>…
+  :units_on               =&gt; TulipaVariable(<span class="sgr1">0×7 DataFrame</span>…
   :storage_level_inter_rp =&gt; TulipaVariable(<span class="sgr1">0×4 DataFrame</span>…
   :storage_level_intra_rp =&gt; TulipaVariable(<span class="sgr1">0×5 DataFrame</span>…</code></pre><p>Now we can compute the model.</p><pre><code class="language-julia hljs">model = create_model(graph, sets, variables, representative_periods, dataframes, years, timeframe, groups, model_parameters)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">A JuMP Model
 ├ solver: none
@@ -112,17 +112,17 @@
 connection = DBInterface.connect(DuckDB.DB)
 read_csv_folder(connection, input_dir; schemas = TulipaEnergyModel.schema_per_table_name)
 energy_problem = run_scenario(connection, optimizer = GLPK.Optimizer)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnergyProblem:
-  - Time creating internal structures (in seconds): 0.136411911
-  - Time computing constraints partitions (in seconds): 0.000185927
-  - Time creating dataframes (in seconds): 0.00583825
-  - Time creating variables indices (in seconds): 1.623e-6
+  - Time creating internal structures (in seconds): 0.137979912
+  - Time computing constraints partitions (in seconds): 0.000174967
+  - Time creating dataframes (in seconds): 0.006570406
+  - Time creating variables indices (in seconds): 1.904e-6
   - Model created!
-    - Time for  creating the model (in seconds): 0.006936498
+    - Time for  creating the model (in seconds): 0.006729089
     - Number of variables: 368
     - Number of constraints for variable bounds: 368
     - Number of structural constraints: 432
   - Model solved! 
-    - Time for  solving the model (in seconds): 2.046274089
+    - Time for  solving the model (in seconds): 2.122235957
     - Termination status: OPTIMAL
     - Objective value: 269238.4382417078
 </code></pre><p>or</p><pre><code class="language-julia hljs">using GLPK
@@ -492,4 +492,4 @@
  54777.52475361511
  52128.801264625705
  46907.046645223265</code></pre><p>Here <code>value.</code> (i.e., broadcasting) was used instead of the vector comprehension from previous examples just to show that it also works.</p><p>The value of the constraint is obtained by looking only at the part with variables. So a constraint like <code>2x + 3y - 1 &lt;= 4</code> would return the value of <code>2x + 3y</code>.</p><h3 id="Writing-the-output-to-CSV"><a class="docs-heading-anchor" href="#Writing-the-output-to-CSV">Writing the output to CSV</a><a id="Writing-the-output-to-CSV-1"></a><a class="docs-heading-anchor-permalink" href="#Writing-the-output-to-CSV" title="Permalink"></a></h3><p>To save the solution to CSV files, you can use <a href="../95-reference/#TulipaEnergyModel.save_solution_to_file-NTuple{4, Any}"><code>save_solution_to_file</code></a>:</p><pre><code class="language-julia hljs">mkdir(&quot;outputs&quot;)
-save_solution_to_file(&quot;outputs&quot;, energy_problem)</code></pre><h3 id="Plotting"><a class="docs-heading-anchor" href="#Plotting">Plotting</a><a id="Plotting-1"></a><a class="docs-heading-anchor-permalink" href="#Plotting" title="Permalink"></a></h3><p>In the previous sections, we have shown how to create vectors such as the one for flows. If you want simple plots, you can plot the vectors directly using any package you like.</p><p>If you would like more custom plots, check out <a href="https://github.com/TulipaEnergy/TulipaPlots.jl">TulipaPlots.jl</a>, under development, which provides tailor-made plots for <em>TulipaEnergyModel.jl</em>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../10-how-to-use/">« How to Use</a><a class="docs-footer-nextpage" href="../30-concepts/">Concepts »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Tuesday 29 October 2024 06:56">Tuesday 29 October 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+save_solution_to_file(&quot;outputs&quot;, energy_problem)</code></pre><h3 id="Plotting"><a class="docs-heading-anchor" href="#Plotting">Plotting</a><a id="Plotting-1"></a><a class="docs-heading-anchor-permalink" href="#Plotting" title="Permalink"></a></h3><p>In the previous sections, we have shown how to create vectors such as the one for flows. If you want simple plots, you can plot the vectors directly using any package you like.</p><p>If you would like more custom plots, check out <a href="https://github.com/TulipaEnergy/TulipaPlots.jl">TulipaPlots.jl</a>, under development, which provides tailor-made plots for <em>TulipaEnergyModel.jl</em>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../10-how-to-use/">« How to Use</a><a class="docs-footer-nextpage" href="../30-concepts/">Concepts »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Tuesday 29 October 2024 08:09">Tuesday 29 October 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/30-concepts/index.html

@@ -66,17 +66,17 @@
 connection = DBInterface.connect(DuckDB.DB)
 read_csv_folder(connection, input_dir; schemas = TulipaEnergyModel.schema_per_table_name)
 energy_problem = run_scenario(connection)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnergyProblem:
-  - Time creating internal structures (in seconds): 0.16852234
-  - Time computing constraints partitions (in seconds): 0.000248794
-  - Time creating dataframes (in seconds): 0.005003489
-  - Time creating variables indices (in seconds): 2.014e-6
+  - Time creating internal structures (in seconds): 0.178616774
+  - Time computing constraints partitions (in seconds): 0.00025679
+  - Time creating dataframes (in seconds): 0.006399288
+  - Time creating variables indices (in seconds): 1.683e-6
   - Model created!
-    - Time for  creating the model (in seconds): 3.399579548
+    - Time for  creating the model (in seconds): 3.543088927
     - Number of variables: 727
     - Number of constraints for variable bounds: 727
     - Number of structural constraints: 957
   - Model solved! 
-    - Time for  solving the model (in seconds): 0.029106612
+    - Time for  solving the model (in seconds): 0.029591687
     - Termination status: OPTIMAL
     - Objective value: 2409.3840293440285
-</code></pre><p>Since the <code>battery</code> is not seasonal, it only has results for the intra-storage level of each representative period, as shown in the following figure:</p><p><img src="../figs/intra-storage-level.png" alt="Battery-intra-storage-level"/></p><p>Since the <code>phs</code> is defined as seasonal, it has results for only the inter-storage level. Since we defined the period partition as 1, we get results for each period (i.e., day). We can see that the inter-temporal constraints in the model keep track of the storage level through the whole timeframe definition (i.e., week).</p><p><img src="../figs/inter-storage-level.png" alt="PHS-inter-storage-level"/></p><p>In this example, we have demonstrated how to partially recover the chronological information of a storage asset with a longer discharge duration (such as 48 hours) than the representative period length (24 hours). This feature enables us to model both short- and long-term storage in <em>TulipaEnergyModel.jl</em>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../20-tutorials/">« Tutorials</a><a class="docs-footer-nextpage" href="../40-formulation/">Mathematical Formulation »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Tuesday 29 October 2024 06:56">Tuesday 29 October 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+</code></pre><p>Since the <code>battery</code> is not seasonal, it only has results for the intra-storage level of each representative period, as shown in the following figure:</p><p><img src="../figs/intra-storage-level.png" alt="Battery-intra-storage-level"/></p><p>Since the <code>phs</code> is defined as seasonal, it has results for only the inter-storage level. Since we defined the period partition as 1, we get results for each period (i.e., day). We can see that the inter-temporal constraints in the model keep track of the storage level through the whole timeframe definition (i.e., week).</p><p><img src="../figs/inter-storage-level.png" alt="PHS-inter-storage-level"/></p><p>In this example, we have demonstrated how to partially recover the chronological information of a storage asset with a longer discharge duration (such as 48 hours) than the representative period length (24 hours). This feature enables us to model both short- and long-term storage in <em>TulipaEnergyModel.jl</em>.</p></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../20-tutorials/">« Tutorials</a><a class="docs-footer-nextpage" href="../40-formulation/">Mathematical Formulation »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.7.0 on <span class="colophon-date" title="Tuesday 29 October 2024 08:09">Tuesday 29 October 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>