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基于时序电压灵敏度的ADN分布式光伏选址及定容评估
引用本文:王小仲,唐 明,林承钱,吴刚勇,黄继华,郭 营,陈丽娟.基于时序电压灵敏度的ADN分布式光伏选址及定容评估[J].电力需求侧管理,2021,23(6):57-62.
作者姓名:王小仲  唐 明  林承钱  吴刚勇  黄继华  郭 营  陈丽娟
作者单位:国网浙江省电力有限公司湖州供电公司,浙江湖州 313000;浙江泰仑电力集团有限责任公司,浙江湖州 313000;东南大学电气工程学院,南京210096
基金项目:国网浙江省电力有限公司集体企业科技项目(2018-HZJTKJ-02);国家自然科学基金资助项目(51877044)
摘    要:随着分布式光伏的快速发展,如何确定主动配电网中分布式光伏的安装位置及最大准入容量成为促进新能源消纳良性发展的研究热点.由于分布式光伏的接入会对配网电压产生很大影响,首先提出时序电压灵敏度指标,从电压角度得到分布式光伏的候选安装节点.其次,构建源荷不确定性时序场景集,建立计及不确定性的分布式光伏准入容量评估模型,并基于鲁棒线性化思想及对偶理论将模型转化为混合整数线性规划模型,以便模型的求解.通过Matlab搭建IEEE 33节点系统,仿真结果证明了所建模型的适应性及有效性.

关 键 词:主动配电网  分布式光伏发电  电压灵敏度  时序灵敏度  候选安装节点  准入容量  鲁棒线性化
收稿时间:2021/7/3 0:00:00
修稿时间:2021/9/4 0:00:00

Distributed photovoltaic generation site selection and hosting capacity assessment for active distribution network based on time series voltage sensitivity
WANG Xiaozhong,TANG Ming,LIN Chengqian,WU Gangyong,HUANG Jihu,GUO Ying,CHEN Lijuan.Distributed photovoltaic generation site selection and hosting capacity assessment for active distribution network based on time series voltage sensitivity[J].Power Demand Side Management,2021,23(6):57-62.
Authors:WANG Xiaozhong  TANG Ming  LIN Chengqian  WU Gangyong  HUANG Jihu  GUO Ying  CHEN Lijuan
Affiliation:Huzhou Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd., Huzhou 313000, China;Zhejiang Tailun Power Group Co., Ltd., Huzhou 313000, China;School of Electrical Engineering, Southeast University, Nanjing 210096, China
Abstract:With the rapid development of distributed photovoltaics, how to determine the maximum access capacity of distributed photovoltaics in active distribution networks has become a research hotspot to promote the healthy development of renewable energy consumption. Firstly, since the access of distributed photovoltaics will have a great impact on the distribution network voltage,the time series voltage sensitivity index is proposed to obtain the candidate nodes of distributed PV. Secondly, source- load uncertainty time series scenario set is established. Based on this, a distributed photovoltaic access capacity evaluation model that takes into account uncertainty is constructed. At last, the optimization modal is transformed to the mixed integer linear programming with the help of robust linearization and duality theory. The effectiveness of the proposed method is demonstrated using a modified IEEE 33-bus distribution system.
Keywords:
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