基于条件风险价值的合作型Stackerlberg博弈微网动态定价与优化参考文献：A cooperative Stackelberg game based energy management con
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基于条件风险价值的合作型Stackerlberg博弈微网动态定价与优化参考文献：《A cooperative Stackelberg game based energy management considering price discrimination and risk assessment》完美复现仿真平台：MATLAB yalmip+cplex+mosek注意运行环境安装，不会的可以问我[比心][比心][比心]代码产品不 不主要内容：代码主要做的是一个基于合作型Stackerlberg博弈的考虑差别定价和风险管理的微网动态定价与调度策略，提出了一个双层能源管理框架，实现多个微网间的P2P能源交易，上层为零商的动态定价模型，目标是社会福利最大化；下层是多个产消者的合作博弈模型，优化各产消者的能量管理策略。同时，采用纳什谈判法对多个产消者的合作剩余进行公平分配，还考虑了运行风险，采用条件风险价值（CVaR）随机规划方法来描述零商的预期损失。求解方面，双层模型被基于KKT条件转为单层模型。 <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/90239767/2/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/90239767/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">基于条件风险价值的合作型<span class="_ _0"> </span><span class="ff2">Stackelberg<span class="_ _1"> </span></span>博弈微网动态定价与优化</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff3">：</span>本文介绍了一个基于合作型<span class="_ _0"> </span><span class="ff2">Stackelberg<span class="_ _1"> </span></span>博弈的考虑差别定价和风险管理的微网动态定价与</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">调度策略<span class="ff4">。</span>本文提出了一个双层能源管理框架<span class="ff3">，</span>实现多个微网间的<span class="_ _0"> </span><span class="ff2">P2P<span class="_ _1"> </span></span>能源交易<span class="ff4">。</span>上层为零售商的动</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">态定价模型<span class="ff3">，</span>目标是社会福利最大化<span class="ff3">；</span>下层是多个产消者的合作博弈模型<span class="ff3">，</span>优化各产消者的能量管理</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">策略<span class="ff4">。</span>本文还采用纳什谈判法对多个产消者的合作剩余进行公平分配<span class="ff3">，</span>并考虑了运行风险<span class="ff3">，</span>使用条件</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">风险价值<span class="ff3">（<span class="ff2">CVaR</span>）</span>随机规划方法来描述零售商的预期损失<span class="ff4">。</span>最后<span class="ff3">，</span>本文将双层模型基于<span class="_ _0"> </span><span class="ff2">KKT<span class="_ _1"> </span></span>条件转</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">换为单层模型<span class="ff4">。</span></div><div class="t m0 x1 h2 y8 ff2 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">近年来<span class="ff3">，</span>微网技术的发展使得微网内部的能源交易变得更加灵活和高效<span class="ff4">。</span>然而<span class="ff3">，</span>微网内存在着能源供</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">给和需求之间的不平衡问题<span class="ff3">，</span>且价格和风险管理也是一个重要的考虑因素<span class="ff4">。</span>因此<span class="ff3">，</span>本文提出了基于条</div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">件风险价值的合作型<span class="_ _0"> </span><span class="ff2">Stackelberg<span class="_ _1"> </span></span>博弈微网动态定价与优化模型<span class="ff3">，</span>以解决这些问题<span class="ff4">。</span></div><div class="t m0 x1 h2 yc ff2 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">动态定价模型</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">为了实现社会福利最大化<span class="ff3">，</span>本文设计了一个零售商的动态定价模型<span class="ff4">。</span>该模型考虑了微网内部能源供需</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">的不平衡和能源价格的差异化<span class="ff3">，</span>以确保能源资源的合理利用和分配<span class="ff4">。</span>通过优化定价策略<span class="ff3">，</span>零售商可以</div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">通过引导消费者的能源消费行为来实现社会福利的最大化<span class="ff4">。</span></div><div class="t m0 x1 h2 y10 ff2 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">合作博弈模型</span></div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">针对多个产消者之间的能量管理策略问题<span class="ff3">，</span>本文提出了一个合作博弈模型<span class="ff4">。</span>产消者通过合作来优化能</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">量管理策略<span class="ff3">，</span>以最大化自身的经济利益<span class="ff4">。</span>通过纳什谈判法<span class="ff3">，</span>合作博弈模型能够公平地分配产消者之间</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">的合作剩余<span class="ff3">，</span>以确保所有参与者都能够获得一定的经济效益<span class="ff4">。</span></div><div class="t m0 x1 h2 y14 ff2 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span><span class="ff1">条件风险价值方法</span></div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">为了考虑运行风险<span class="ff3">，</span>本文采用条件风险价值<span class="ff3">（<span class="ff2">CVaR</span>）</span>随机规划方法来描述零售商的预期损失<span class="ff4">。<span class="ff2">CVaR</span></span></div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">方法可以在保证零售商损失不超过一定风险水平的同时<span class="ff3">，</span>最小化预期损失<span class="ff4">。</span>通过<span class="_ _0"> </span><span class="ff2">CVaR<span class="_ _1"> </span></span>方法<span class="ff3">，</span>零售商</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">可以更好地应对不确定性和风险<span class="ff3">，</span>从而提高微网的运行效率和稳定性<span class="ff4">。</span></div><div class="t m0 x1 h2 y18 ff2 fs0 fc0 sc0 ls0 ws0">5.<span class="_ _2"> </span><span class="ff1">模型求解</span></div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">本文将双层模型基于<span class="_ _0"> </span><span class="ff2">KKT<span class="_ _1"> </span></span>条件转换为单层模型<span class="ff3">，</span>通过<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">yalmip+cplex+mosek<span class="_ _1"> </span></span>仿真平台</div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">来求解<span class="ff4">。</span>通过求解单层模型<span class="ff3">，</span>可以得到最优的动态定价和能量管理策略<span class="ff3">，</span>从而实现微网内部资源的合</div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">理分配和利用<span class="ff4">。</span></div><div class="t m0 x1 h2 y1c ff2 fs0 fc0 sc0 ls0 ws0">6.<span class="_ _2"> </span><span class="ff1">结果分析</span></div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">通过仿真实验<span class="ff3">，</span>本文验证了基于条件风险价值的合作型<span class="_ _0"> </span><span class="ff2">Stackelberg<span class="_ _1"> </span></span>博弈微网动态定价与优化模型</div><div class="t m0 x1 h2 y1e ff1 fs0 fc0 sc0 ls0 ws0">的有效性和优越性<span class="ff4">。</span>实验结果表明<span class="ff3">，</span>通过定价差异化和合作博弈策略<span class="ff3">，</span>可以实现微网内部能源供需的</div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>