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<h1 class="title">PowerModelsDistribution.jl Transformer Modelling Tutorial</h1>
</div>
<div class="quarto-title-meta">
</div>
</header>
<section id="introduction" class="level1">
<h1>Introduction</h1>
<p>While <code>PowerModelsDistribution.jl</code> allows great flexibility modelling power transformers with any number of windings taking into account the loss models for each winding, it can be overwhelming for starting users especially the gap between the intuitive “ENGINEERING” (OpenDSS) definition and the “MATHEMATICAL” decomposition. Hence, this tutorial is to provide a simple introduction to power transformer models in <code>PowerModelsDistribution.jl</code>.</p>
<p>For transformer model implementation details refer to <em>S. Claeys, G. Deconinck and F. Geth, “Decomposition of n-winding transformers for unbalanced optimal power flow,” IET Generation, Transmission & Distribution, vol. 14, no. 24, pp. 5961-5969, 2020, DOI: 10.1049/iet-gtd.2020.0776.</em></p>
</section>
<section id="transformer-modelling-theory" class="level1">
<h1>Transformer Modelling Theory</h1>
<p>Starting with the simplest case of a two-winding, single-phase transformer, which will later serve as the fundamental building block for <span class="math inline">\(n\)</span>-winding, <span class="math inline">\(n\)</span>-phase transformers.</p>
<p>Without delving deeply into the electromagnetic theory of transformer operation, the functioning of a transformer can be simplified as follows: a primary coil (coil 1) and a secondary coil (coil 2) are wound on the same magnetic core. When a voltage <span class="math inline">\(U_1\)</span> is applied to the primary coil, it generates a magnetic flux <span class="math inline">\(\Phi_1\)</span>. Part of this flux links the primary coil with itself (not going through the core to the secondary coil), denoted as <span class="math inline">\(\Phi_{11}\)</span>, while another part, denoted as <span class="math inline">\(\Phi_{m}\)</span>, links the secondary coil. The magnetic flux <span class="math inline">\(\Phi_{m}\)</span> induces a voltage <span class="math inline">\(U_2\)</span> in the secondary coil, which can drive a current <span class="math inline">\(I_2\)</span> when a load is connected to the secondary coil.</p>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="PMD_Transformer_Tutorial_files/figure-html/aac7e3a2-1-Transformer_Fields.png" class="img-fluid figure-img"></p>
<figcaption>Transformer_Fields.png</figcaption>
</figure>
</div>
<p>Taking into account that each of the coils has a resistance <span class="math inline">\(R_1\)</span> and <span class="math inline">\(R_2\)</span> and modelling the leakage flux <span class="math inline">\(\Phi_{11}\)</span> and <span class="math inline">\(\Phi_{22}\)</span> the transformer equivalent circuit can be represented as follows using basic circuit elements and an ideal transformer:</p>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="PMD_Transformer_Tutorial_files/figure-html/aac7e3a2-2-circuit_ideal_transformer.png" class="img-fluid figure-img"></p>
<figcaption>circuit_ideal_transformer.png</figcaption>
</figure>
</div>
<p>For a simpler schematic representation, we use a standarized symbol for the ideal transformer, note the polarity dots indicating that the two coil ends with dots will have the same instantaneous polarity.</p>
<div class="quarto-figure quarto-figure-center">
<figure class="figure">
<p><img src="PMD_Transformer_Tutorial_files/figure-html/aac7e3a2-3-equivalent_circuit.png" class="img-fluid figure-img"></p>
<figcaption>equivalent_circuit.png</figcaption>
</figure>
</div>
<p>package_name = “PowerModelsDistribution” eval(Meta.parse(“using $package_name”))elsDistribution.jl ## Getting Started In order to understand how does <code>PowerModelsDistribution.jl</code> model transformers, first we activate a Julia project in the current directory and we define <a href="pmd_xfmr_modelling_helper_funs.jl">some helper functions</a> that we will need later on in this tutorial.</p>
<div id="ca22683d" class="cell">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb1"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">Pkg</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="bu">Pkg</span>.<span class="fu">activate</span>(<span class="st">"."</span>)</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="bu">Pkg</span>.<span class="fu">instantiate</span>()</span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a>dependencies <span class="op">=</span> [<span class="st">"PowerModelsDistribution"</span>, <span class="st">"Ipopt"</span>, <span class="st">"Makie"</span>, <span class="st">"CairoMakie"</span>]</span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> dependency <span class="kw">in</span> dependencies</span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a> <span class="cf">if</span> !(dependency <span class="kw">in</span> <span class="fu">keys</span>(<span class="bu">Pkg</span>.<span class="fu">project</span>().dependencies))</span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a> <span class="bu">Pkg</span>.<span class="fu">add</span>(dependency)</span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a> <span class="cf">end</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="cf">end</span></span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">PowerModelsDistribution</span></span>
<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">Ipopt</span></span>
<span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">Makie</span></span>
<span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">CairoMakie</span></span>
<span id="cb1-16"><a href="#cb1-16" aria-hidden="true" tabindex="-1"></a><span class="fu">include</span>(<span class="st">"pmd_xfmr_modelling_helper_funs.jl"</span>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-stderr">
<div class="ansi-escaped-output">
<pre><span class="ansi-green-fg ansi-bold"> Activating</span> project at `c:\Users\mnumair\OneDrive - KU Leuven\PhD Agenda\2025\12-25 December\PMD Transformer Model Tutorial`
<span class="ansi-yellow-fg ansi-bold">┌ </span><span class="ansi-yellow-fg ansi-bold">Pkg.API | Warning ] : </span>The project dependencies or compat requirements have changed since the manifest was last resolved.
<span class="ansi-yellow-fg ansi-bold">│ </span>It is recommended to `Pkg.resolve()` or consider `Pkg.update()` if necessary.
<span class="ansi-yellow-fg ansi-bold">└ </span><span class="ansi-bright-black-fg">@ Pkg.API C:\Users\mnumair\.julia\juliaup\julia-1.12.3+0.x64.w64.mingw32\share\julia\stdlib\v1.12\Pkg\src\API.jl:1280</span>
</pre>
</div>
</div>
<div class="cell-output cell-output-display">
<pre><code>analyze_vector_group</code></pre>
</div>
</div>
<section id="dss-transformer-definition" class="level2">
<h2 class="anchored" data-anchor-id="dss-transformer-definition">DSS transformer definition</h2>
<p>We then parse the <a href="trans_1ph_2w_yy.dss"><code>trans_1ph_2w_yy.dss</code></a> file which simply a single-phase source connected to a single-phase load through a two-winding, single-phase wye-wye transformer <code>TX1</code> which is defined as follows:</p>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb3"><pre class="sourceCode pascal code-with-copy"><code class="sourceCode pascal"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co">// ...</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="co">// Transformers</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="kw">New</span> Transformer.TX1 phases=<span class="dv">1</span> Buses=[<span class="dv">1</span> <span class="dv">2</span>] <span class="co">// (required) Define transformer named TX1 connecting buses 1 and 2</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a>~ windings=<span class="dv">2</span> <span class="co">// (optional) Number of windings in the transformer</span></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a>~ conns=[wye wye] <span class="co">// (optional) Connection type for each winding (default: wye)</span></span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a>~ kvs=[<span class="dv">11</span> <span class="dv">0.4</span>] <span class="co">// (required) Rated voltage in kV for each winding</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a>~ kvas=[<span class="dv">500</span> <span class="dv">500</span>] <span class="co">// (required) Rated power in kVA for each winding</span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a>~ xhl=<span class="dv">5</span> <span class="co">// (optional) Leakage reactance between primary and secondary in percent (default: 2)</span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a>~ %noloadloss=<span class="dv">5</span> <span class="co">// (optional) No-load loss as percentage of rated power (default: 0)</span></span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a>~ %imag=<span class="dv">11</span> <span class="co">// (optional) Magnetizing current as percentage of rated current (default: 0)</span></span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a>~ wdg=<span class="dv">1</span> %r=<span class="dv">1</span> <span class="co">// (optional) Resistance of winding 1 as percentage of rated power (default: 0.002)</span></span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a>~ wdg=<span class="dv">2</span> %r=<span class="dv">2</span> <span class="co">// (optional) Resistance of winding 2 as percentage of rated power (default: 0.002)</span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a><span class="co">// %r = [1 2] ! is also valid syntax</span></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a>~ taps=[<span class="dv">1.05</span> <span class="dv">0.95</span>] <span class="co">// (optional) Tap position for each winding as per-unit voltage (default: 1.0)</span></span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a>~ leadlag=lead <span class="co">// (optional) Phase shift direction for Dy/Yd transformers: lead or lag (default: lag)</span></span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a>~ bank=TX1 <span class="co">// (optional) Bank name for grouping transformers (default: transformer name)</span></span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a><span class="co">// ...</span></span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>While I have tried to add most used parameters, a lot of these parameters are optional and have default values. For a full list of parameters please refer to the <a href="https://opendss.epri.com/Properties16.html">OpenDSS documentation</a>.</p>
</section>
<section id="engineering-model-output" class="level2">
<h2 class="anchored" data-anchor-id="engineering-model-output">ENGINEERING model output</h2>
<p>Now we will parse this <code>dss</code> file to the <code>ENGINEERING</code> model in <code>PowerModelsDistribution.jl</code> and inspect the transformer model.</p>
<div id="1ea31ca4" class="cell" data-execution_count="903">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb4"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>eng_1ph_2w_yy <span class="op">=</span> <span class="fu">parse_file</span>(<span class="st">"trans_1ph_2w_yy.dss"</span>, transformations<span class="op">=</span>[transform_loops!] );</span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a>eng_1ph_2w_yy[<span class="st">"transformer"</span>][<span class="st">"tx1"</span>]</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 18 entries:
"polarity" => [1, 1]
"sm_nom" => [500.0, 500.0]
"connections" => [[1, 4], [1, 4]]
"tm_lb" => [[0.9], [0.9]]
"tm_set" => [[1.05], [0.95]]
"tm_step" => [[0.03125], [0.03125]]
"bus" => ["b1", "b2"]
"configuration" => ConnConfig[WYE, WYE]
"status" => ENABLED
"noloadloss" => 0.05
"xsc" => [0.05]
"cmag" => 0.11
"sm_ub" => 750.0
"source_id" => "transformer.tx1"
"rw" => [0.01, 0.02]
"tm_fix" => Vector{Bool}[[1], [1]]
"vm_nom" => [11.0, 0.4]
"tm_ub" => [[1.1], [1.1]]</code></pre>
</div>
</div>
<p>Note that all <code>TX1</code> transformer parameters defined in the dss file match the <code>ENGINEERING</code> model output. Only value difference you might notice is the loss model impedances being re-based from the transformer rating to the network base <a href="https://github.com/lanl-ansi/PowerModelsDistribution.jl/blob/79874bc491e9b2e71adb09bea79f227f33a99a72/src/data_model/transformations/dss2eng.jl#L554-L748">as detailed here</a>. Additionally <code>PowerModelsDistribution.jl</code> adds default values for upper and lower bounds for some parameters if not defined in the dss file.</p>
</section>
<section id="mathematical-model-output" class="level2">
<h2 class="anchored" data-anchor-id="mathematical-model-output">MATHEMATICAL model output</h2>
<p>Now we will transform the user-friendly <code>ENGINEERING</code> model into the optimization-ready <code>MATHEMATICAL</code> model in <code>PowerModelsDistribution.jl</code> and inspect the transformer model.</p>
<p>In <code>PowerModelsDistribution.jl</code>, the two-winding, single-phase transformer is modelled by decomposing it into two ideal transformers connected in series with the loss model virtual branches as shown below: <img src="PMD_Transformer_Tutorial_files/figure-html/2e848563-1-pmd_equiv_model_bases.png" class="img-fluid" alt="pmd_equiv_model_bases.png"> comparing to the generic equivalent circuit shown earlier, we can point out some key observations: - in the <code>MATHEMATICAL</code> model, a single transformer is decomposed into two ideal transformers, each representing one winding of the original transformer. - Due to this decomposition, there exists a third intermediate loss model at a voltage base of <span class="math inline">\(1~\text{kV}\)</span> between the two ideal transformers which are under their respective winding voltage bases. - Loss model components are implemented as virtual branches using the internal “branch” data structure in <code>PowerModelsDistribution.jl</code>. Consequently, the parallel core loss and magnetizing components are modeled as shunt conductance (<span class="math inline">\(G\)</span>) and susceptance (<span class="math inline">\(B\)</span>) within the first virtual branch of the equivalent circuit. - The series reactances (<span class="math inline">\(X_1\)</span>, <span class="math inline">\(X_2\)</span>) are added together in the middle (third) virtual branch of the <code>MATHEMATICAL</code> equivalent circuit. - The series resistances (<span class="math inline">\(R_1\)</span>, <span class="math inline">\(R_2\)</span>) are added to the respective virtual branches of each ideal transformer.</p>
<section id="single-phase-two-winding-wye-wye-transformer" class="level3">
<h3 class="anchored" data-anchor-id="single-phase-two-winding-wye-wye-transformer">Single-Phase Two-Winding Wye-Wye Transformer</h3>
<p>We can validate these observations by inspecting how <code>TX1</code> transformer has been modelled in the <code>MATHEMATICAL</code> model output of <code>PowerModelsDistribution.jl</code>.</p>
<div id="7c845cca" class="cell" data-execution_count="904">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb6"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>math_1ph_2w_yy <span class="op">=</span> <span class="fu">transform_data_model</span>(eng_1ph_2w_yy);</span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>math_1ph_2w_yy[<span class="st">"transformer"</span>]</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 2 entries:
"1" => Dict{String, Any}("source_id"=>"_virtual_transformer.transformer.tx1.1…
"2" => Dict{String, Any}("source_id"=>"_virtual_transformer.transformer.tx1.2…</code></pre>
</div>
</div>
<p>We already can notice that <code>TX1</code> transformer has been decomposed into two ideal transformers <code>tx1.1</code> and <code>tx1.2</code>.</p>
<div id="955f09f2" class="cell" data-execution_count="905">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb8"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>tx_components <span class="op">=</span> <span class="fu">show_transformer_math_components</span>(math_1ph_2w_yy);</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>"in the MATHEMATICAL model transformer tx1 was converted to: "</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================branch 3================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 22 entries:
"br_r" => [0.12;;]
"br_x" => [0.0;;]
"g_to" => [0.0;;]
"c_rating_a" => [Inf]
"vbase" => 0.57735
"source_id" => "_virtual_branch.transformer.tx1_2"
"br_status" => 1
"b_to" => [0.0;;]
"index" => 3
"tap" => [1.0]
"shift" => [0.0]
"f_connections" => [1]
"name" => "_virtual_branch.transformer.tx1_2"
"switch" => false
"g_fr" => [0.00833333;;]
"b_fr" => [-0.0183333;;]
"t_connections" => [1]
"f_bus" => 6
"t_bus" => 5
⋮ => ⋮</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================branch 4================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 22 entries:
"br_r" => [0.0;;]
"br_x" => [0.3;;]
"g_to" => [0.0;;]
"c_rating_a" => [Inf]
"vbase" => 0.57735
"source_id" => "_virtual_branch.transformer.tx1_3"
"br_status" => 1
"b_to" => [0.0;;]
"index" => 4
"tap" => [1.0]
"shift" => [0.0]
"f_connections" => [1]
"name" => "_virtual_branch.transformer.tx1_3"
"switch" => false
"g_fr" => [0.0;;]
"b_fr" => [0.0;;]
"t_connections" => [1]
"f_bus" => 7
"t_bus" => 5
⋮ => ⋮</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================branch 5================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 22 entries:
"br_r" => [0.06;;]
"br_x" => [0.0;;]
"g_to" => [0.0;;]
"c_rating_a" => [Inf]
"vbase" => 0.57735
"source_id" => "_virtual_branch.transformer.tx1_1"
"br_status" => 1
"b_to" => [0.0;;]
"index" => 5
"tap" => [1.0]
"shift" => [0.0]
"f_connections" => [1]
"name" => "_virtual_branch.transformer.tx1_1"
"switch" => false
"g_fr" => [0.0;;]
"b_fr" => [0.0;;]
"t_connections" => [1]
"f_bus" => 8
"t_bus" => 7
⋮ => ⋮</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================transformer 1================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 20 entries:
"source_id" => "_virtual_transformer.transformer.tx1.1"
"t_connections" => [1]
"f_bus" => 4
"polarity" => 1
"sm_ub" => 0.75
"cm_ub" => Inf
"tm_fix" => Bool[1]
"tm_lb" => [0.9]
"tm_set" => [1.05]
"t_vbase" => 0.57735
"tm_step" => [0.03125]
"t_bus" => 8
"f_connections" => [1]
"configuration" => WYE
"index" => 1
"name" => "_virtual_transformer.tx1.1"
"tm_nom" => 1.0
"status" => 1
"tm_ub" => [1.1]
"f_vbase" => 6.35085</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================transformer 2================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 20 entries:
"source_id" => "_virtual_transformer.transformer.tx1.2"
"t_connections" => [1]
"f_bus" => 3
"polarity" => 1
"sm_ub" => 0.75
"cm_ub" => Inf
"tm_fix" => Bool[1]
"tm_lb" => [0.9]
"tm_set" => [0.95]
"t_vbase" => 0.57735
"tm_step" => [0.03125]
"t_bus" => 6
"f_connections" => [1]
"configuration" => WYE
"index" => 2
"name" => "_virtual_transformer.tx1.2"
"tm_nom" => 1.0
"status" => 1
"tm_ub" => [1.1]
"f_vbase" => 0.23094</code></pre>
</div>
</div>
<p>From the above log of all the components that transformer <code>TX1</code> has been decomposed into, we can see that it fits the decomposition explained earlier as in the image below. Also, it can be shown that the parameters of the first ideal transformer includes the rating, tap, polarity and connection of a single winding (the HV winding in this case), while the second ideal transformer includes the parameters of the other winding (the LV winding in this case). The loss model parameters are now represented as series impedances connected to the ideal transformers. <img src="PMD_Transformer_Tutorial_files/figure-html/f0b575df-1-sphtr-2.png" class="img-fluid" alt="sphtr-2.png"></p>
<p>This function also returns a dictionary of the components that can be explored further.</p>
<div id="038819c3" class="cell" data-execution_count="906">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb20"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a>tx_components[<span class="st">"tx1"</span>]</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 3 entries:
"branches" => Dict{String, Any}("4"=>Dict{String, Any}("br_r"=>[0.0;;], "…
"buses" => Dict{String, Any}("5"=>Dict{String, Any}("vm_pair_lb"=>Tupl…
"transformers" => Dict{String, Any}("1"=>Dict{String, Any}("source_id"=>"_vir…</code></pre>
</div>
</div>
<p>This decomposition approach was chosen to simplify the modelling for the optimization model to reuse the existing network elements and their mathematical formulations for any <span class="math inline">\(n\)</span>-winding transformer.</p>
</section>
<section id="three-phase-two-winding-delta-wye-transformer" class="level3">
<h3 class="anchored" data-anchor-id="three-phase-two-winding-delta-wye-transformer">Three-Phase Two-Winding Delta-Wye Transformer</h3>
<p>As mentioned earlier, the two-winding, single-phase transformer model serves as the fundamental building block for <span class="math inline">\(n\)</span>-winding, <span class="math inline">\(n\)</span>-phase transformers. Hence, we can extend the same understanding to a more complex transformer such as a three-phase, two-winding delta-wye transformer. as defined in the <a href="trans_3ph_2w_dy_en.dss"><code>trans_3ph_2w_dy_en.dss</code></a> file. In which the transformer <code>TX1</code> is defined as follows:</p>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb22"><pre class="sourceCode pascal code-with-copy"><code class="sourceCode pascal"><span id="cb22-1"><a href="#cb22-1" aria-hidden="true" tabindex="-1"></a><span class="co">// ...</span></span>
<span id="cb22-2"><a href="#cb22-2" aria-hidden="true" tabindex="-1"></a><span class="kw">New</span> Transformer.TX1 phases=<span class="dv">3</span> Buses=[b1.<span class="dv">1</span>.<span class="dv">2.3</span> b2.<span class="dv">1</span>.<span class="dv">2</span>.<span class="dv">3.4</span>]</span>
<span id="cb22-3"><a href="#cb22-3" aria-hidden="true" tabindex="-1"></a>~ Windings=<span class="dv">2</span></span>
<span id="cb22-4"><a href="#cb22-4" aria-hidden="true" tabindex="-1"></a>~ Conns=[Delta Wye]</span>
<span id="cb22-5"><a href="#cb22-5" aria-hidden="true" tabindex="-1"></a>~ kVs=[<span class="dv">11</span> <span class="dv">0.4</span>]</span>
<span id="cb22-6"><a href="#cb22-6" aria-hidden="true" tabindex="-1"></a>~ kVAs=[<span class="dv">500</span> <span class="dv">500</span>]</span>
<span id="cb22-7"><a href="#cb22-7" aria-hidden="true" tabindex="-1"></a>~ %Rs=[<span class="dv">1</span> <span class="dv">2</span>]</span>
<span id="cb22-8"><a href="#cb22-8" aria-hidden="true" tabindex="-1"></a>~ xhl=<span class="dv">5</span></span>
<span id="cb22-9"><a href="#cb22-9" aria-hidden="true" tabindex="-1"></a>~ %noloadloss=<span class="dv">5</span></span>
<span id="cb22-10"><a href="#cb22-10" aria-hidden="true" tabindex="-1"></a>~ %imag=<span class="dv">11</span></span>
<span id="cb22-11"><a href="#cb22-11" aria-hidden="true" tabindex="-1"></a>~ leadlag=lag</span>
<span id="cb22-12"><a href="#cb22-12" aria-hidden="true" tabindex="-1"></a>~ taps=[<span class="dv">1.0</span> <span class="dv">1.0</span>]</span>
<span id="cb22-13"><a href="#cb22-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb22-14"><a href="#cb22-14" aria-hidden="true" tabindex="-1"></a><span class="kw">New</span> Reactor.Grounding phases=<span class="dv">1</span> bus1=b2<span class="dv">.4</span> bus2=b2<span class="dv">.0</span> R=<span class="dv">0</span> X=<span class="dv">1E-6</span> <span class="co">// Grounding reactor for wye neutral</span></span>
<span id="cb22-15"><a href="#cb22-15" aria-hidden="true" tabindex="-1"></a><span class="co">// ...</span></span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>We can notice that in the three phase transformer definition, we have an additional parameter <code>phases=3</code> and we define the connection points for each winding in the <code>Buses</code> parameter as <code>b1.1.2.3</code> for the delta primary winding and <code>b2.1.2.3.4</code> for the wye secondary winding with the fourth point being the neutral point which is grounded through a the <code>Grounding</code> reactor defined later.</p>
<div id="e4a56ca8" class="cell" data-execution_count="907">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb23"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb23-1"><a href="#cb23-1" aria-hidden="true" tabindex="-1"></a>eng_3ph_2w_dy <span class="op">=</span> <span class="fu">parse_file</span>(<span class="st">"trans_3ph_2w_dy_en.dss"</span>, transformations<span class="op">=</span>[transform_loops!] );</span>
<span id="cb23-2"><a href="#cb23-2" aria-hidden="true" tabindex="-1"></a>eng_3ph_2w_dy[<span class="st">"transformer"</span>][<span class="st">"tx1"</span>]</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 19 entries:
"polarity" => [1, -1]
"sm_nom" => [500.0, 500.0]
"tm_lb" => [[0.9, 0.9, 0.9], [0.9, 0.9, 0.9]]
"connections" => [[1, 2, 3], [2, 3, 1, 4]]
"tm_set" => [[1.0, 1.0, 1.0], [1.0, 1.0, 1.0]]
"tm_step" => [[0.03125, 0.03125, 0.03125], [0.03125, 0.03125, 0.03125]]
"bus" => ["b1", "b2"]
"configuration" => ConnConfig[DELTA, WYE]
"name" => "tx1"
"status" => ENABLED
"noloadloss" => 0.05
"cmag" => 0.11
"xsc" => [0.05]
"source_id" => "transformer.tx1"
"sm_ub" => 750.0
"rw" => [0.01, 0.02]
"tm_fix" => Vector{Bool}[[1, 1, 1], [1, 1, 1]]
"vm_nom" => [11.0, 0.4]
"tm_ub" => [[1.1, 1.1, 1.1], [1.1, 1.1, 1.1]]</code></pre>
</div>
</div>
<p>As in the single-phase case, we can validate that the parameters have been parsed correctly in the <code>ENGINEERING</code> model output. And now we can inspect how has the three-phase, two-winding delta-wye transformer <code>TX1</code> been modelled in the <code>MATHEMATICAL</code> model output of <code>PowerModelsDistribution.jl</code>.</p>
<div id="621a2612" class="cell" data-execution_count="908">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb25"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb25-1"><a href="#cb25-1" aria-hidden="true" tabindex="-1"></a>math_3ph_2w_dy <span class="op">=</span> <span class="fu">transform_data_model</span>(eng_3ph_2w_dy, kron_reduce<span class="op">=</span><span class="cn">false</span>, phase_project<span class="op">=</span><span class="cn">false</span>);</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
</div>
<p>Note that in this conversion we set the options <code>kron_reduce=false</code> and <code>phase_project=false</code> to keep all phases and neutral in the mathematical model for inspection purposes. However, it is possible to apply Kron reduction and phase projection during the transformation to eliminate the neutral and reduce the model.</p>
<p>Now if we inpsect the components that transformer <code>TX1</code> has been decomposed into, we can see that it exactly matches that for the single-phase case but now with full matrices for the loss model’s virtual branches parameters as shown below:</p>
<div id="21bb4a1d" class="cell" data-execution_count="909">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb26"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb26-1"><a href="#cb26-1" aria-hidden="true" tabindex="-1"></a>tx_components <span class="op">=</span> <span class="fu">show_transformer_math_components</span>(math_3ph_2w_dy);</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>"in the MATHEMATICAL model transformer tx1 was converted to: "</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================branch 3================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 22 entries:
"br_r" => [0.024 0.0 0.0; 0.0 0.024 0.0; 0.0 0.0 0.024]
"br_x" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"g_to" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"c_rating_a" => [Inf, Inf, Inf]
"vbase" => 0.57735
"source_id" => "_virtual_branch.transformer.tx1_2"
"br_status" => 1
"b_to" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"index" => 3
"tap" => [1.0, 1.0, 1.0]
"shift" => [0.0, 0.0, 0.0]
"f_connections" => [1, 2, 3]
"name" => "_virtual_branch.transformer.tx1_2"
"switch" => false
"g_fr" => [0.0416667 0.0 0.0; 0.0 0.0416667 0.0; 0.0 0.0 0.0416667]
"b_fr" => [-0.0916667 0.0 0.0; 0.0 -0.0916667 0.0; 0.0 0.0 -0.091666…
"t_connections" => [1, 2, 3]
"f_bus" => 6
"t_bus" => 5
⋮ => ⋮</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================branch 4================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 22 entries:
"br_r" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"br_x" => [0.06 0.0 0.0; 0.0 0.06 0.0; 0.0 0.0 0.06]
"g_to" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"c_rating_a" => [Inf, Inf, Inf]
"vbase" => 0.57735
"source_id" => "_virtual_branch.transformer.tx1_3"
"br_status" => 1
"b_to" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"index" => 4
"tap" => [1.0, 1.0, 1.0]
"shift" => [0.0, 0.0, 0.0]
"f_connections" => [1, 2, 3]
"name" => "_virtual_branch.transformer.tx1_3"
"switch" => false
"g_fr" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"b_fr" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"t_connections" => [1, 2, 3]
"f_bus" => 7
"t_bus" => 5
⋮ => ⋮</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================branch 5================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 22 entries:
"br_r" => [0.012 0.0 0.0; 0.0 0.012 0.0; 0.0 0.0 0.012]
"br_x" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"g_to" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"c_rating_a" => [Inf, Inf, Inf]
"vbase" => 0.57735
"source_id" => "_virtual_branch.transformer.tx1_1"
"br_status" => 1
"b_to" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"index" => 5
"tap" => [1.0, 1.0, 1.0]
"shift" => [0.0, 0.0, 0.0]
"f_connections" => [1, 2, 3]
"name" => "_virtual_branch.transformer.tx1_1"
"switch" => false
"g_fr" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"b_fr" => [0.0 0.0 0.0; 0.0 0.0 0.0; 0.0 0.0 0.0]
"t_connections" => [1, 2, 3]
"f_bus" => 8
"t_bus" => 7
⋮ => ⋮</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================transformer 1================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 20 entries:
"source_id" => "_virtual_transformer.transformer.tx1.1"
"t_connections" => [1, 2, 3, 4]
"f_bus" => 4
"polarity" => 1
"sm_ub" => 3.75
"cm_ub" => Inf
"tm_fix" => Bool[1, 1, 1]
"tm_lb" => [0.9, 0.9, 0.9]
"tm_set" => [1.0, 1.0, 1.0]
"t_vbase" => 0.57735
"tm_step" => [0.03125, 0.03125, 0.03125]
"t_bus" => 8
"f_connections" => [1, 2, 3]
"configuration" => DELTA
"index" => 1
"name" => "_virtual_transformer.tx1.1"
"tm_nom" => 1.73205
"status" => 1
"tm_ub" => [1.1, 1.1, 1.1]
"f_vbase" => 6.35085</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>"================================transformer 2================================"</code></pre>
</div>
<div class="cell-output cell-output-display">
<pre><code>Dict{String, Any} with 20 entries:
"source_id" => "_virtual_transformer.transformer.tx1.2"
"t_connections" => [1, 2, 3, 4]
"f_bus" => 3
"polarity" => -1
"sm_ub" => 3.75
"cm_ub" => Inf
"tm_fix" => Bool[1, 1, 1]
"tm_lb" => [0.9, 0.9, 0.9]
"tm_set" => [1.0, 1.0, 1.0]
"t_vbase" => 0.57735
"tm_step" => [0.03125, 0.03125, 0.03125]
"t_bus" => 6
"f_connections" => [2, 3, 1, 4]
"configuration" => WYE
"index" => 2
"name" => "_virtual_transformer.tx1.2"
"tm_nom" => 1.0
"status" => 1
"tm_ub" => [1.1, 1.1, 1.1]
"f_vbase" => 0.23094</code></pre>
</div>
</div>
<p>Additionally, we can see that each ideal transformer has a <code>"configuration"</code> parameter indicating the connection type of that winding (delta or wye), which is used alongside the <code>"polarity"</code> and <code>"f_connection"</code> and <code>"t_connection"</code> parameters to achieve the correct phase shift (vector group) and connection type in the mathematical model as will be discussed in the next section.</p>
</section>
</section>
</section>
<section id="transformer-vector-groups" class="level1">
<h1>Transformer Vector Groups</h1>
<p>In three-phase power systems, transformers can connect the primary and secondary windings in different configurations (Wye, Delta, Zigzag, etc.). The combination of connection types and the resulting phase shift between the high-voltage (HV) and low-voltage (LV) sides is described by the <strong>Vector Group</strong>.</p>
<section id="the-clock-notation" class="level2">
<h2 class="anchored" data-anchor-id="the-clock-notation">The “Clock” Notation</h2>
<p>The vector group is usually denoted by a code such as <strong>Dyn11</strong>. This acts like a clock face: * <strong>D</strong>: Capital letter indicates the High Voltage (HV) winding connection (D = Delta, Y = Wye, Z = Zigzag). * <strong>y</strong>: Lowercase letter indicates the Low Voltage (LV) winding connection (d = Delta, y = Wye, z = Zigzag). * <strong>n</strong>: Indicates if the Neutral is brought out. * <strong>11</strong>: The “Clock Number” representing the phase shift.</p>
<p>The phase shift is measured in units of 30 degrees (the angle between hours on a clock). <strong>The HV phasor is always the reference at 12 o’clock (0°).</strong></p>
<table class="caption-top table">
<thead>
<tr class="header">
<th style="text-align: left;">Clock</th>
<th style="text-align: left;">Angle</th>
<th style="text-align: left;">Description</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;"><strong>0</strong></td>
<td style="text-align: left;"><span class="math inline">\(0^\circ\)</span></td>
<td style="text-align: left;">In-phase</td>
</tr>
<tr class="even">
<td style="text-align: left;"><strong>1</strong></td>
<td style="text-align: left;"><span class="math inline">\(-30^\circ\)</span></td>
<td style="text-align: left;">Lagging by 30°</td>
</tr>
<tr class="odd">
<td style="text-align: left;"><strong>6</strong></td>
<td style="text-align: left;"><span class="math inline">\(180^\circ\)</span></td>
<td style="text-align: left;">Opposite</td>
</tr>
<tr class="even">
<td style="text-align: left;"><strong>11</strong></td>
<td style="text-align: left;"><span class="math inline">\(+30^\circ\)</span></td>
<td style="text-align: left;">Leading by 30°</td>
</tr>
</tbody>
</table>
<section id="achieving-different-vector-groups" class="level3">
<h3 class="anchored" data-anchor-id="achieving-different-vector-groups">Achieving Different Vector Groups</h3>
<p>In physical transformers (and <code>PowerModelsDistribution.jl</code>), different vector groups are achieved by: 1. <strong>Connection Type</strong>: Delta or Wye. 2. <strong>Polarity</strong>: Reversing the winding polarity (adds 180° shift). 3. <strong>Phase Sequence (Permutation)</strong>: Swapping how the phases (A, B, C) are connected to the terminals. For example, connecting phase A to terminal C and C to A on a Delta winding effectively reverses the sequence, turning a Lag into a Lead.</p>
<p>We will now explore this interactively. You can change the connections and wiring permutations below and see the <strong>actual phase shift</strong> produced by the math model.</p>
<div id="0613d3d9" class="cell" data-execution_count="910">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb38"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb38-1"><a href="#cb38-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Configuration Options</span></span>
<span id="cb38-2"><a href="#cb38-2" aria-hidden="true" tabindex="-1"></a>primary_perms <span class="op">=</span> [</span>
<span id="cb38-3"><a href="#cb38-3" aria-hidden="true" tabindex="-1"></a> [<span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span>], [<span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">2</span>], [<span class="fl">2</span>, <span class="fl">1</span>, <span class="fl">3</span>], </span>
<span id="cb38-4"><a href="#cb38-4" aria-hidden="true" tabindex="-1"></a> [<span class="fl">2</span>, <span class="fl">3</span>, <span class="fl">1</span>], [<span class="fl">3</span>, <span class="fl">1</span>, <span class="fl">2</span>], [<span class="fl">3</span>, <span class="fl">2</span>, <span class="fl">1</span>]</span>
<span id="cb38-5"><a href="#cb38-5" aria-hidden="true" tabindex="-1"></a>]</span>
<span id="cb38-6"><a href="#cb38-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb38-7"><a href="#cb38-7" aria-hidden="true" tabindex="-1"></a>secondary_perms <span class="op">=</span> [</span>
<span id="cb38-8"><a href="#cb38-8" aria-hidden="true" tabindex="-1"></a> [<span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span>], [<span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">2</span>], [<span class="fl">2</span>, <span class="fl">1</span>, <span class="fl">3</span>], </span>
<span id="cb38-9"><a href="#cb38-9" aria-hidden="true" tabindex="-1"></a> [<span class="fl">2</span>, <span class="fl">3</span>, <span class="fl">1</span>], [<span class="fl">3</span>, <span class="fl">1</span>, <span class="fl">2</span>], [<span class="fl">3</span>, <span class="fl">2</span>, <span class="fl">1</span>]</span>
<span id="cb38-10"><a href="#cb38-10" aria-hidden="true" tabindex="-1"></a>]</span>
<span id="cb38-11"><a href="#cb38-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb38-12"><a href="#cb38-12" aria-hidden="true" tabindex="-1"></a>lead_lag_opts <span class="op">=</span> [<span class="st">"Lead"</span>, <span class="st">"Lag"</span>]</span>
<span id="cb38-13"><a href="#cb38-13" aria-hidden="true" tabindex="-1"></a>conn_opts <span class="op">=</span> [</span>
<span id="cb38-14"><a href="#cb38-14" aria-hidden="true" tabindex="-1"></a> (<span class="st">"Delta"</span>, <span class="st">"Wye"</span>), </span>
<span id="cb38-15"><a href="#cb38-15" aria-hidden="true" tabindex="-1"></a> (<span class="st">"Wye"</span>, <span class="st">"Wye"</span>), </span>
<span id="cb38-16"><a href="#cb38-16" aria-hidden="true" tabindex="-1"></a> (<span class="st">"Wye"</span>, <span class="st">"Delta"</span>), </span>
<span id="cb38-17"><a href="#cb38-17" aria-hidden="true" tabindex="-1"></a> (<span class="st">"Delta"</span>, <span class="st">"Delta"</span>)</span>
<span id="cb38-18"><a href="#cb38-18" aria-hidden="true" tabindex="-1"></a>]</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<pre><code>4-element Vector{Tuple{String, String}}:
("Delta", "Wye")
("Wye", "Wye")
("Wye", "Delta")
("Delta", "Delta")</code></pre>
</div>
</div>
<div id="867900f8" class="cell" data-execution_count="911">
<div class="code-copy-outer-scaffold"><div class="sourceCode cell-code" id="cb40"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb40-1"><a href="#cb40-1" aria-hidden="true" tabindex="-1"></a><span class="co"># INTERACTIVE: Change these values and Run this cell!</span></span>
<span id="cb40-2"><a href="#cb40-2" aria-hidden="true" tabindex="-1"></a><span class="co"># =======================================================</span></span>
<span id="cb40-3"><a href="#cb40-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-4"><a href="#cb40-4" aria-hidden="true" tabindex="-1"></a><span class="co"># 1. Choose Connection Pair (Primary, Secondary)</span></span>
<span id="cb40-5"><a href="#cb40-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Options: ("Delta", "Wye"), ("Wye", "Wye"), ("Wye", "Delta"), ("Delta", "Delta")</span></span>
<span id="cb40-6"><a href="#cb40-6" aria-hidden="true" tabindex="-1"></a>selected_conn <span class="op">=</span> (<span class="st">"Delta"</span>, <span class="st">"Wye"</span>) </span>
<span id="cb40-7"><a href="#cb40-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-8"><a href="#cb40-8" aria-hidden="true" tabindex="-1"></a><span class="co"># 2. Choose Wira Permutations [1, 2, 3] is standard A-B-C</span></span>
<span id="cb40-9"><a href="#cb40-9" aria-hidden="true" tabindex="-1"></a><span class="co"># Try [1, 3, 2] to swap B and C phases!</span></span>
<span id="cb40-10"><a href="#cb40-10" aria-hidden="true" tabindex="-1"></a>sel_prim_perm <span class="op">=</span> [<span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span>] </span>
<span id="cb40-11"><a href="#cb40-11" aria-hidden="true" tabindex="-1"></a>sel_sec_perm <span class="op">=</span> [<span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span>]</span>
<span id="cb40-12"><a href="#cb40-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-13"><a href="#cb40-13" aria-hidden="true" tabindex="-1"></a><span class="co"># 3. OpenDSS Lead/Lag setting (Only affects D-y or Y-d)</span></span>
<span id="cb40-14"><a href="#cb40-14" aria-hidden="true" tabindex="-1"></a><span class="co"># Options: "Lead", "Lag"</span></span>
<span id="cb40-15"><a href="#cb40-15" aria-hidden="true" tabindex="-1"></a>sel_lead_lag <span class="op">=</span> <span class="st">"Lead"</span></span>
<span id="cb40-16"><a href="#cb40-16" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-17"><a href="#cb40-17" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-18"><a href="#cb40-18" aria-hidden="true" tabindex="-1"></a><span class="co"># 4. Choose Taps [Primary, Secondary] (p.u.)</span></span>
<span id="cb40-19"><a href="#cb40-19" aria-hidden="true" tabindex="-1"></a>selected_taps <span class="op">=</span> [<span class="fl">1.0</span>, <span class="fl">1.0</span>]</span>
<span id="cb40-20"><a href="#cb40-20" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-21"><a href="#cb40-21" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-22"><a href="#cb40-22" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb40-23"><a href="#cb40-23" aria-hidden="true" tabindex="-1"></a><span class="co"># =======================================================</span></span>
<span id="cb40-24"><a href="#cb40-24" aria-hidden="true" tabindex="-1"></a><span class="co"># Run Simulation</span></span>
<span id="cb40-25"><a href="#cb40-25" aria-hidden="true" tabindex="-1"></a><span class="fu">analyze_vector_group</span>(</span>
<span id="cb40-26"><a href="#cb40-26" aria-hidden="true" tabindex="-1"></a> selected_conn[<span class="fl">1</span>], selected_conn[<span class="fl">2</span>], </span>
<span id="cb40-27"><a href="#cb40-27" aria-hidden="true" tabindex="-1"></a> sel_prim_perm, sel_sec_perm, </span>
<span id="cb40-28"><a href="#cb40-28" aria-hidden="true" tabindex="-1"></a> sel_lead_lag, selected_taps</span>
<span id="cb40-29"><a href="#cb40-29" aria-hidden="true" tabindex="-1"></a>);</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<div class="cell-output cell-output-display">
<img width="800" height="800" style="object-fit: contain; height: auto;" src="data:image/png;base64, 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">
</div>
</div>
</section>
</section>
<section id="summary-of-reachable-groups" class="level2">
<h2 class="anchored" data-anchor-id="summary-of-reachable-groups">5. Summary of Reachable Groups</h2>
<p>By changing the connection permutation (cyclic rotation) of the terminals 1, 2, 3:</p>
<ol type="1">
<li><strong>Group 0 (0, 4, 8):</strong> Obtained from <strong>Dd / Yy</strong> types.</li>
<li><strong>Group 1 (1, 5, 9):</strong> Obtained from <strong>Dy / Yd</strong> types (lagging connection).</li>
<li><strong>Group 11 (11, 3, 7):</strong> Obtained from <strong>Dy / Yd</strong> types (leading connection).</li>
<li><strong>Group 6 (6, 10, 2):</strong> Obtained by reversing polarity of coils (Swapping ends of windings, e.g., connecting a’ to Neutral instead of n’).</li>
</ol>
<p>A list of all reachable vector groups is available in <a href="AppendixA_vector_groups.md">Appendix A</a> <em>Note: Currently PowerModelsDistribution has an issue with Delta winding as a secondary, I am trying to fix it.</em> <em>Note: In OpenDSS/PowerModelsDistribution, defining <code>Buses=[... 3.1.2]</code> performs these cyclic shifts that is simulated by the <code>leadlag</code> parameter in OpenDSS</em></p>
</section>
<section id="contribute-and-raise-issues" class="level2">
<h2 class="anchored" data-anchor-id="contribute-and-raise-issues">Contribute and raise issues</h2>
<p>While great care was put into validating the correctness of the tutorial content, there may still be mistakes or areas for improvement. If you find any issues or have suggestions, please feel free to raise them in the <a href="https://github.com/MohamedNumair/PMD-Transformer-Model-Tutorial/issues">Issues</a>.</p>
</section>
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