双碳背景下综合能源系统低碳优化调度：基于Matlab+Yalmip+Cplex实现新能源消纳与成本最小化优化,双碳背景下综合能源系统低碳优化调度研究：Matlab结合Yalmip与Cplex实现方法探
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双碳背景下综合能源系统低碳优化调度：基于Matlab+Yalmip+Cplex实现新能源消纳与成本最小化优化,双碳背景下综合能源系统低碳优化调度研究：Matlab结合Yalmip与Cplex实现方法探索,双碳+24小时分时综合能源系统低碳优化调度（用Matlab+Yalmip＋Cplex）包含新能源消纳、热电联产、电锅炉、储能电池、天然气、碳捕集CCS、计及碳交易市场等综合元素，实现系统总运行成本最小 包括购电成本、购气成本、碳交易成本、运维成本。程序中均加入标注，适合基础入门，必学会 ,双碳; 24小时分时综合能源系统; 低碳优化调度; 新能源消纳; 热电联产; 电锅炉; 储能电池; 天然气; 碳捕集CCS; 碳交易市场; 运行成本最小化; 购电成本; 购气成本; 碳交易成本; 运维成本; Matlab; Yalmip; Cplex; 程序标注。,基于双碳目标的24小时分时综合能源系统低碳优化调度教程 <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/90426926/2/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/90426926/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">《综合能源系统优化调度：实现双碳目标的新途径》</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要：</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">本<span class="_ _0"></span>文<span class="_ _0"></span>以<span class="_ _0"></span>双<span class="_ _0"></span>碳<span class="_ _0"></span>目<span class="_ _0"></span>标<span class="_ _0"></span>为<span class="_ _0"></span>背<span class="_ _0"></span>景<span class="_ _0"></span>，<span class="_ _0"></span>探<span class="_ _0"></span>讨<span class="_ _0"></span>了<span class="_ _0"></span>一<span class="_ _0"></span>种<span class="_ _0"></span>基<span class="_ _0"></span>于<span class="_ _1"> </span><span class="ff2">24<span class="_"> </span></span>小<span class="_ _0"></span>时<span class="_ _0"></span>分<span class="_ _0"></span>时<span class="_ _0"></span>综<span class="_ _0"></span>合<span class="_ _0"></span>能<span class="_ _0"></span>源<span class="_ _0"></span>系<span class="_ _0"></span>统<span class="_ _0"></span>的<span class="_ _0"></span>低<span class="_ _0"></span>碳<span class="_ _0"></span>优<span class="_ _0"></span>化<span class="_ _0"></span>调<span class="_ _0"></span>度<span class="_ _0"></span>方<span class="_ _0"></span>案<span class="_ _0"></span>。</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">该方案结<span class="_ _0"></span>合了新<span class="_ _0"></span>能源消<span class="_ _0"></span>纳、热<span class="_ _0"></span>电联产、<span class="_ _0"></span>电锅炉<span class="_ _0"></span>、储能<span class="_ _0"></span>电池、天<span class="_ _0"></span>然气以<span class="_ _0"></span>及碳捕<span class="_ _0"></span>集<span class="_ _1"> </span><span class="ff2">CCS<span class="_ _2"> </span></span>等技术，</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">并考虑了计及碳交易市场的运行成本。<span class="_ _3"></span>本文将通过<span class="_ _2"> </span><span class="ff2">Matlab<span class="_"> </span></span>和<span class="_ _2"> </span><span class="ff2">Yalmip+Cplex<span class="_"> </span></span>工具进行模型构</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">建和求解，程序中将加入详细标注，以便基础入门者学习。</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">一、引言</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">在当今社会，<span class="_ _4"></span>实现双碳目标已经成为全球共识。<span class="_ _4"></span>而要实现这一目标，<span class="_ _4"></span>综合能源系统的优化调</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">度显得尤为重要。<span class="_ _5"></span>本文旨在探讨一种综合能源系统的优化调度方案，<span class="_ _5"></span>通过合理配置各种能源</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">资源，实现系统总运行成本的最小化。</div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">二、系统架构与元素</div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">本系统包括新能源消纳、<span class="_ _6"></span>热电联产、<span class="_ _6"></span>电锅炉、<span class="_ _6"></span>储能电池、<span class="_ _6"></span>天然气等多个元素。<span class="_ _6"></span>其中，<span class="_ _6"></span>新能源</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">消纳是降低碳排放的关键手段<span class="_ _7"></span>；<span class="_ _7"></span>热电联产则通过提高能源利用效率来减少能源消耗<span class="_ _7"></span>；<span class="_ _7"></span>电锅炉</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">和储能电池则能够在电力需求高峰时提供稳定的电力支持<span class="_ _5"></span>；<span class="_ _5"></span>天然气作为清洁能源，能够减少</div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">对化石能源的依赖；而碳捕集<span class="_ _2"> </span><span class="ff2">CCS<span class="_"> </span></span>技术则能够进一步降低碳排放。</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">三、模型构建与求解</div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">本文采用<span class="_ _1"> </span><span class="ff2">Matlab<span class="_ _2"> </span></span>和<span class="_ _1"> </span><span class="ff2">Yalmip+Cplex<span class="_ _2"> </span></span>工具进行<span class="_ _0"></span>模型构建和<span class="_ _0"></span>求解。首先，<span class="_ _0"></span>通过<span class="_ _1"> </span><span class="ff2">Matlab<span class="_ _2"> </span></span>建立综合</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">能源系统的数学<span class="_ _0"></span>模型，包括各<span class="_ _0"></span>个元素的运行特<span class="_ _0"></span>性、约束条件<span class="_ _0"></span>等。然后，利用<span class="_ _1"> </span><span class="ff2">Yalmip<span class="_ _2"> </span></span>进行模</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">型优化，<span class="_ _6"></span>通过<span class="_ _2"> </span><span class="ff2">Cplex<span class="_"> </span></span>求解器求解最优解。<span class="_ _7"></span>在程序中，<span class="_ _6"></span>我们将加入详细标注，<span class="_ _6"></span>以便初学者能够</div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">更好地理解和学习。</div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">四、优化调度策略</div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">在优化调度过程中，<span class="_ _7"></span>我们考虑了购电成本、<span class="_ _7"></span>购气成本、<span class="_ _7"></span>碳交易成本以及运维成本等因素。<span class="_ _7"></span>通</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">过合理配置各种能源资源，实现系统总运行成本的最小化。具体策略包括<span class="_ _5"></span>：<span class="_ _5"></span>在电力需求高峰</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">时，优先使用电锅炉和储能电池提供电力支持<span class="_ _5"></span>；<span class="_ _5"></span>在电力需求低谷时，则通过新能源消纳和热</div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">电联产<span class="_ _0"></span>等方式降<span class="_ _0"></span>低购电<span class="_ _0"></span>成本；<span class="_ _0"></span>同时，<span class="_ _0"></span>通过碳捕<span class="_ _0"></span>集<span class="_ _1"> </span><span class="ff2">CCS<span class="_ _2"> </span></span>技术进<span class="_ _0"></span>一步降<span class="_ _0"></span>低碳排<span class="_ _0"></span>放，并<span class="_ _0"></span>在碳交易</div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">市场中获取收益。</div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">五、案例分析</div><div class="t m0 x1 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0">以某地区为例，我们进行了综合能源系统的优化调度。通过模拟<span class="_ _2"> </span><span class="ff2">24<span class="_"> </span></span>小时内的电力需求和能</div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">源供应情况，<span class="_ _7"></span>我们发现，<span class="_ _7"></span>在采用上述优化调度策略后，<span class="_ _7"></span>系统总运行成本得到了显著降低。<span class="_ _7"></span>同</div><div class="t m0 x1 h2 y1e ff1 fs0 fc0 sc0 ls0 ws0">时，碳排放也得到了有效控制，实现了双碳目标。</div><div class="t m0 x1 h2 y1f ff1 fs0 fc0 sc0 ls0 ws0">六、结论</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div>