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作 者:殷凤媛 迟清 肖博文 陈汝科 杨凯帆 黄婧 柴涛 YIN Fengyuan;CHI Qing;XIAO Bowen;CHEN Ruke;YANG Kaifan;HUANG Jing;CHAI Tao(School of Mechanical and Electrical Engineering,Wuhan Qingchuan University,Wuhan,430204;State Grid Shaanxi Electric Power Company,Xian 710048,China;State Grid Jingmen Power Supply Company,Jingmen 448000,China;College of Electrical and New Energy,Three Gorges University,Yichang 443000,China)
机构地区:[1]武汉晴川学院机械与电气工程学院,湖北武汉430204 [2]国网陕西省电力公司,陕西西安710048 [3]国网湖北荆门供电公司,湖北荆门448000 [4]三峡大学电气与新能源学院,湖北宜昌443000
出 处:《智慧电力》2021年第2期7-14,共8页Smart Power
基 金:国家自然科学基金资助项目(61876097)。
摘 要:考虑增量配电网中的负荷电价变化等不确定性因素,将延迟期权理论融入到增量配电网源网规划模型之中,提出一种考虑延迟期权的增量配电网源网协调规划方法。首先在期望负荷增长率的基础上构建增量配电网分布式电源的选址定容模型,并通过序优化算法得到分布式电源规划可行方案的帕累托前沿;然后在此基础上通过蒙特卡洛模拟,得出增量配电网负荷及电价的变化路径,在此基础上构建考虑延迟期权的分布式电源最优投资时间决策模型,最终得到增量配电网最优投资规划策略。基于IEEE30节点系统的仿真验证了本文方法的有效性和可行性。The gradual liberalization of incremental distribution network business in China has brought a series of opportunities and challenges to China’s power grid planning.Considering the uncertain factors such as load price changes in the incremental distribution network,the paper proposes a coordinated planning of source and network in the incremental distribution network,by integrating delay option theory into the planning model of the source and network in the incremental distribution network.Firstly,the location and capacity model of distributed generation in the incremental distribution network is constructed on the basis of expected load growth rate,and the Pareto frontier of the feasible scheme for distributed generation planning is obtained by sequential optimization algorithm.Then on this basis,the change path of the load and price of the incremental distribution network is obtained with Monte Carlo simulation,and the decision model of the optimal investment time for the distributed generation with the delay option is constructed.Finally,the optimal investment planning strategy for the incremental distribution network is obtained.The simulation based on IEEE 30-bus system verifies the effectiveness and feasibility of the proposed method.
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