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夏季尖峰电价启动条件优化研究

Research on optimizing configuration of critical peak pricing based demand response
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摘要 分时电价是电力系统开展需求响应、削减夏季空调负荷所造成负荷尖峰的重要手段。为协调各方利益、达成削峰填谷和压减电网尖峰负荷的目的,需要挖掘分析用户用电数据,优化分时电价的实施方案。提出基于余弦相似度的用户需求响应参与度的峰段负荷转移系数指标。应用该指标分行业地进行某省会电网峰段负荷转移评估,发现除充换电等行业响应积极外,大量行业用户因行业和负荷特性等原因难以参与需求响应。针对在整个夏季启动尖峰电价将会增大实体企业用电成本的问题,结合历史气象和负荷数据进行夏季尖峰电价日启动条件设置分析,发现将气温在35℃及以上的工作日设置为尖峰电价日,可在精准削减尖峰负荷的同时明显降低用户用能成本。 Time of use(ToU)price is an important means for power utilities to implement demand response.In order to shave peak load of the power grid based on coordination interests of all participants,it is necessary to analyze the electricity usage data of users and optimize the configuration of ToU price.The cosine similarity is employed to develop a peak load transfer evaluation coefficient index that can visually evaluate user responsiveness in a straightforward way.The index is employed to evaluate the users’response degree of a power utility by industry.It is uncovered that majority of industrial and commercial users of various industries cannot participate in demand response due to their industry and electricity usage characteristics.Once all days in the summer are set as day of peak electricity prices,these users suffer substantial economic loss inevitably.The meteorological data and load data are analyzed to find out the way to optimize configuration of day of peak electricity prices.It is uncovered that the peak load can be shaved effectively without causing unnecessary electricity bill of these users by setting work day with temperature over 35℃as day of electricity price.
作者 朱琛 王明茜 张阳 方兴 莫桢 苏盛 ZHU Chen;WANG Mingxi;ZHANG Yang;FANG Xing;MO Zhen;SU Sheng(Changsha Power Supply Company,State Grid Hunan Electric Power Co.,Ltd.,Changsha 410004,China;School of Electrical&Information Engineering,Changsha University of Science&Technology,Changsha 410014,China)
出处 《电力科学与技术学报》 CAS CSCD 北大核心 2024年第3期96-103,共8页 Journal of Electric Power Science And Technology
基金 国网湖南省电力有限公司科技项目(B616A1220006)。
关键词 分时电价 需求响应 尖峰负荷 尖峰电价日 time of use price demand response peak load day of peak electricity price
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