Matlab含新能源（风电光伏）和多类型电动汽车配电网风险评估软件：matpower+Matlab：关键词：蒙特卡洛、时序、
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Matlab含新能源（风电光伏）和多类型电动汽车配电网风险评估软件：matpower+Matlab：关键词：蒙特卡洛、时序、电网风险、风险评估、风光不确定性介绍：由于电动汽车负荷与风电光伏出力的不确定性，造成配电网运行风险，运用蒙特卡洛概率潮流计算分析电压和线路支路越限，并且风险指标考虑损失严重度放大系数函数。绘制电压和支路功率时空越限风险图，并给出风光出力曲线、电动汽车出力图、网损大小分布，在IEEE33配电网节点系统进行验证 <link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89766834/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89766834/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">标题<span class="ff2">：</span>基于蒙特卡洛和时序分析的<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>软件在新能源和多类型电动汽车配电网风险评估中的应用</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span>随着新能源<span class="ff2">（</span>风电光伏<span class="ff2">）</span>和多类型电动汽车的快速发展<span class="ff2">，</span>配电网运行面临着更多的不确定性和</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">风险<span class="ff4">。</span>本文基于<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>软件结合<span class="_ _0"> </span><span class="ff3">matpower<span class="_ _1"> </span></span>库<span class="ff2">，</span>运用蒙特卡洛概率潮流计算和时序分析方法<span class="ff2">，</span>对配</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">电网中的电压和线路支路越限进行风险评估<span class="ff2">，</span>并绘制了电压和支路功率时空越限风险图<span class="ff4">。</span>在<span class="_ _0"> </span><span class="ff3">IEEE33</span></div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">配电网节点系统的验证实验中<span class="ff2">，</span>通过考虑损失严重度放大系数函数<span class="ff2">，</span>我们还分析了风光出力曲线<span class="ff4">、</span>电</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">动汽车出力图和网损大小分布<span class="ff4">。</span>该研究为实现新能源和多类型电动汽车的可靠接入配电网提供了有力</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">的支持和参考<span class="ff4">。</span></div><div class="t m0 x1 h2 y8 ff3 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">引言</span></div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">随着对可再生能源的需求不断增加<span class="ff2">，</span>新能源<span class="ff2">（</span>风电光伏<span class="ff2">）</span>和电动汽车得到了迅速发展<span class="ff4">。</span>然而<span class="ff2">，</span>由于新</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">能源和电动汽车负荷的不确定性<span class="ff2">，</span>配电网运行面临着更多的风险<span class="ff4">。</span>因此<span class="ff2">，</span>进行精确的风险评估和预测</div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">对于保障配电网的稳定运行至关重要<span class="ff4">。</span></div><div class="t m0 x1 h2 yc ff3 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">蒙特卡洛概率潮流计算</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">蒙特卡洛概率潮流计算是一种常用的风险评估方法<span class="ff2">，</span>该方法可以对电压和线路支路越限进行可靠性分</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">析<span class="ff4">。</span>通过采样新能源和电动汽车负荷的不确定性<span class="ff2">，</span>结合潮流计算模型<span class="ff2">，</span>可以得到配电网的风险指标<span class="ff4">。</span></div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">本节将介绍蒙特卡洛概率潮流计算的原理和步骤<span class="ff2">，</span>并详细讨论了如何考虑损失严重度放大系数函数<span class="ff4">。</span></div><div class="t m0 x1 h2 y10 ff3 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">时序分析方法</span></div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">时序分析方法是一种针对时间序列数据的分析方法<span class="ff2">，</span>在配电网风险评估中具有重要作用<span class="ff4">。</span>本节将介绍</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">时序分析方法在配电网风险评估中的应用<span class="ff2">，</span>并通过风光出力曲线<span class="ff4">、</span>电动汽车出力图和网损大小分布等</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">指标展示其分析结果<span class="ff4">。</span></div><div class="t m0 x1 h2 y14 ff3 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span>Matlab<span class="_ _1"> </span><span class="ff1">软件和<span class="_ _0"> </span></span>matpower<span class="_ _1"> </span><span class="ff1">库</span></div><div class="t m0 x1 h2 y15 ff3 fs0 fc0 sc0 ls0 ws0">Matlab<span class="_ _1"> </span><span class="ff1">是一款功能强大的科学计算软件<span class="ff2">，</span>结合<span class="_ _0"> </span></span>matpower<span class="_ _1"> </span><span class="ff1">库可以方便地进行配电网风险评估分析<span class="ff4">。</span></span></div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">本节将介绍<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>软件和<span class="_ _0"> </span><span class="ff3">matpower<span class="_ _1"> </span></span>库的基本用法<span class="ff2">，</span>并详细说明如何使用这些工具实现配电网风险</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">评估的算法<span class="ff4">。</span></div><div class="t m0 x1 h2 y18 ff3 fs0 fc0 sc0 ls0 ws0">5.<span class="_ _2"> </span><span class="ff1">实验与验证</span></div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">本节将以<span class="_ _0"> </span><span class="ff3">IEEE33<span class="_ _1"> </span></span>配电网节点系统为例<span class="ff2">，</span>进行实验与验证<span class="ff4">。</span>通过对该节点系统进行风险评估<span class="ff2">，</span>并绘制</div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">电压和支路功率时空越限风险图<span class="ff2">，</span>验证了本文方法的有效性和可靠性<span class="ff4">。</span>同时<span class="ff2">，</span>通过分析风光出力曲线</div><div class="t m0 x1 h2 y1b ff4 fs0 fc0 sc0 ls0 ws0">、<span class="ff1">电动汽车出力图和网损大小分布<span class="ff2">，</span>进一步验证了本研究的实用性和准确性</span>。</div><div class="t m0 x1 h2 y1c ff3 fs0 fc0 sc0 ls0 ws0">6.<span class="_ _2"> </span><span class="ff1">结论</span></div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">本文基于<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>软件结合<span class="_ _0"> </span><span class="ff3">matpower<span class="_ _1"> </span></span>库<span class="ff2">，</span>运用蒙特卡洛概率潮流计算和时序分析方法<span class="ff2">，</span>实现了新能</div><div class="t m0 x1 h2 y1e ff1 fs0 fc0 sc0 ls0 ws0">源和多类型电动汽车配电网风险评估<span class="ff4">。</span>通过实验证明<span class="ff2">，</span>该方法能够有效评估配电网中的电压和线路支</div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>