多形态冷热负荷平抑风电不确定性的鲁棒优化方法

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英文篇名：Research on robust optimization method for stabilizing wind power uncertainty based on multi-type cooling and heating loads 作者：沈方 ; 邓鑫阳 ; 张明理 ; 刘岩 ; 梁毅 ; 杨博 英文作者：Shen Fang;Deng Xinyang;Zhang Mingli;Liu Yan;Liang Yi;Yang Bo;Economic and Technological Research Institute of State Grid Liaoning Electric Power Co. Ltd; 关键词：冷热负荷 ; 风电不确定性 ; 鲁棒优化 英文关键词：cooling and heating loads;;wind power uncertainty;;robust optimization 中文刊名：NCNY 英文刊名：Renewable Energy Resources 机构：国网辽宁省电力有限公司经济技术研究院; 出版日期：2019-01-14 出版单位：可再生能源 年：2019 期：v.37;No.245 基金：国家自然科学基金(61304069) 语种：中文; 页：NCNY201901014 页数：7 CN：01 ISSN：21-1469/TK 分类号：89-95

摘要

风电不确定性所引起的弃风和功率波动,成为限制风电大规模并网的关键因素。针对冷热负荷响应速度快且聚合容量大的特点,分析了包含分散式冷热负荷和集群式冷热负荷的多形态冷热负荷模型。为研究多形态冷热负荷平抑风电不确定性的鲁棒优化方法,以消纳风电和平抑风电功率波动为目标,对分散式冷热负荷功率和集群式冷热负荷功率进行优化,建立多形态冷热负荷两阶段鲁棒优化模型,并利用CCG算法对模型求解。最后,以IEEE39节点系统建立仿真模型,对鲁棒优化方法进行仿真分析。结果表明,多形态冷热负荷两阶段鲁棒优化方法能够有效平抑风电不确定性。
        Wind curtailment and fluctuation caused by wind power uncertainty have become a key factor to limit the large-scale grid connection of wind power. Due to the fast response and large polymerization capacity of cooling and heating loads(CHLs), a multi-type CHLs model including decentralized CHLs and clustered CHLs was studied. In order to study using the multi-type CHLs to stabilize the wind power uncertainty, the wind power accommodations and fluctuations are taken as the objective function, a two-stage robust optimization model of CHLs is established by optimizing decentralized CHLs power and clustered CHLs power. The model was solved by CCG algorithm. Finally, the simulation model is established by IEEE39 node system, and the robust optimization method is simulated. The results show that the two-stage robust optimization method of multi-type CHLs can effectively suppress wind power uncertainty.

引文

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