引用本文:周帆,陈龙,赵珺,王伟.计及多元不确定性的综合能源系统优化配置[J].控制理论与应用,2024,41(3):533~542.[点击复制]
ZHOU Fan,CHEN Long,ZHAO Jun,WANG Wei.Optimal configuration for integrated energy system considering multiple uncertainties[J].Control Theory and Technology,2024,41(3):533~542.[点击复制]
计及多元不确定性的综合能源系统优化配置
Optimal configuration for integrated energy system considering multiple uncertainties
摘要点击 3024  全文点击 230  投稿时间：2022-05-01  修订日期：2022-11-25
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DOI编号  10.7641/CTA.2023.20337
  2024,41(3):533-542
中文关键词  综合能源系统  不确定性  N-1故障  机会约束  多准则评价
英文关键词  integrated energy system  uncertainty  N-1 failure  chance constraint programming  multi-criteria evaluation
基金项目  国家重点研发计划项目(2017YFA0700300), 国家自然科学基金项目(61833003, U1908218, 62003072), 大连市优秀青年科技人才计划项目(20 18RJ01)资助.
作者单位E-mail
周帆 大连理工大学 控制科学与工程学院 zhouf_2011@mail.dlut.edu.cn 
陈龙 大连理工大学 控制科学与工程学院  
赵珺* 大连理工大学 控制科学与工程学院 zhaoj@dlut.edu.cn 
王伟 大连理工大学 控制科学与工程学院  
中文摘要
      综合能源系统的优化配置关键在于设备选型与数量配置, 而能源负荷负荷和可再生能源出力预测误差以 及故障发生的不确定性将直接影响配置方案的合理性以及经济性. 为此, 本文提出一种考虑源–网–荷多元不确定 性的综合能源系统多目标–机会约束规划方法. 考虑可再生能源出力与负荷需求预测误差引起的不确定性, 本文构 建了满足置信概率的能量供需平衡约束; 针对供能网络中设备N-1故障引起的不确定性, 提出调整裕度模型, 进而 构建了调整裕度与N-1设备能量缺额的机会约束. 对于获得的帕累托解集, 采用信息熵与逼近理想排序法构建多准 则评价模型, 以确定最优的系统配置. 将本文方法应用于某区域综合能源系统的最优结构设计, 实验结果表明, 本文 方法的有效性与可靠性.
英文摘要
      The key of achieving the optimal configuration of integrated energy system (IES) is the selection of equipment types and determination of their number, however, the forecasting errors of energy demand load and renewable energy output, and the failure of equipment, will directly affect the rationality and economy of the configuration scheme. Therefore, this paper proposes a multi-objective chance constraint programming method for the IES considering source-network-load multiple uncertainty. This one considers the uncertainty caused by the forecast error of renewable energy output and load demand, and constructs an energy supply and demand balance constraint that satisfies the confidence probability. Aiming at the uncertainty caused by the N-1 failure of equipment, we propose an adjustment margin model. On this basis, the chance constraint of adjusting margin and energy deficit of N-1 equipment is constructed. For the obtained Pareto solution set, a multi-criteria evaluation model is carried out by using the information entropy and technique for order preference by similarity to ideal solution (TOPSIS) methods to determine the optimal system energy supply structure. Finally, the proposed method is applied to the optimal configuration of a regional IES, and the effectiveness and reliability are illustrated via experimental results.