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考虑过电压风险的配电网光伏接纳能力评估方法 被引量:10

PV Hosting Capacity Evaluation Method in Distribution Network Considering Overvoltage Risk
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摘要 配电网中光伏渗透率的不断提高对配电网的安全稳定运行提出了很大挑战,研究配电网的光伏接纳能力已成为当前的学术热点,科学合理的光伏接纳能力评估方法有助于配电网规划人员更有针对性地进行光伏规划与建设。针对数学优化方法分析场景有限、随机场景模拟法评估较为保守等问题,引入过电压风险的概念,提出基于过电压风险的配电网光伏接纳能力评估方法,能够有效量化光伏配置方式的不确定性导致的配电网过电压风险。在此基础上,进一步考虑过电压发生的严重程度,通过引入修正系数改进过电压风险指标,由该方法得到的评估结果更能反映配电网真实的过电压风险水平,对于实际的光伏容量规划更具适应性和指导意义。最后,以中国某地区实际的55母线配电系统为例进行算例分析,验证所提方法的适应性和有效性。 The increasing penetration of photovoltaic(PV)in distribution network(DN)brings a tougher challenge for the safe and steady operation of DN.The research on PV hosting capacity(PVHC)of DN has become an academic hotspot at present.A scientific and reasonable PVHC evaluation method is helpful for DN planners to carry out PV planning and construction more pertinently.Aiming at limited analysis scenarios by the mathematical optimization method as well as conservative evaluation by the stochastic scenario analysis method,the concept of overvoltage risk is introduced in this paper,and an overvoltage risk based PVHC evaluation method is proposed,which can effectively quantify the overvoltage risk of DN caused by the uncertainty of PV configuration.On this basis,the overvoltage severity is further considered,and the index of overvoltage risk is improved by introducing a correction coefficient.The evaluation results obtained by this method can better reflect the real overvoltage risk level of DN,and have more adaptability and guiding significance for practical PV planning.In the end,a practical 55-bus distribution system in a certain area of China is used to illustrate adaptability and effectiveness of the proposed method.
作者 董逸超 王守相 高丽娟 王洋 DONG Yichao;WANG Shouxiang;GAO Lijuan;WANG Yang(Key Laboratory of Smart Grid of Ministry of Education(Tianjin University),Nankai District,Tianjin 300072,China;State Grid Hengshui Electric Power Supply Company,Hengshui 053000,Hebei Province,China)
出处 《分布式能源》 2019年第6期35-40,共6页 Distributed Energy
关键词 配电网 光伏接纳能力 随机场景模拟 过电压风险 distribution network photovoltaic(PV)hosting capacity stochastic scenario analysis overvoltage risk
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