引用本文: | 钱科军,刘 乙,张新松,等.考虑电动汽车充电负荷的配电系统场景概率潮流分析[J].电力系统保护与控制,2020,48(24):62-70.[点击复制] |
QIAN Kejun,LIU Yi,ZHANG Xinsong,et al.Scenario-based probabilistic power flow calculation of distribution systems withelectric vehicle charging loads[J].Power System Protection and Control,2020,48(24):62-70[点击复制] |
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摘要: |
提出了一种同时考虑分布式光伏出力和电动汽车充电负荷随机特性的配电系统场景概率潮流分析方法。首先,在考虑车主交通行为与充电模式随机特性的基础上,采用蒙特卡洛模法对充电站典型日内的充电负荷进行模拟,给出充电负荷曲线集。接着,采用K-means聚类分别对充电负荷曲线集和光伏历史出力曲线集进行聚类,给出充电负荷和光伏出力的概率场景集,并以此为基础构建潮流分析场景集。最后,采用前推回代法进行所有场景下的配电系统潮流分析。按场景概率对潮流结果进行汇总,给出概率潮流分析结果。基于IEEE 33节点配电系统的仿真计算验证了所提模型及方法的有效性。 |
关键词: 概率潮流 电动汽车充电 场景概率 K-means聚类 前推回代 |
DOI:DOI: 10.19783/j.cnki.pspc.200049 |
投稿时间:2020-01-12修订日期:2020-04-28 |
基金项目:国家电网有限公司科技项目资助(SGJSSZ00KJJS 1903295)“国网江苏苏州高渗透分布式能源接入背景下的电动汽车充电网络优化布局策略研究” |
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Scenario-based probabilistic power flow calculation of distribution systems withelectric vehicle charging loads |
QIAN Kejun,LIU Yi,ZHANG Xinsong,LI Yafei,XIE Ying,XU Yangyang,LU Shengnan |
(1. Suzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215000, China;
2. School of Electrical Engineering, Nantong University, Nantong 226019, China) |
Abstract: |
A scenario-based methodology is presented to investigate the probabilistic power flow of distribution systems with stochastic distributed PV outputs and Electric Vehicle (EV) charging loads. First, Monte Carlo simulation (MCS) technology is used to simulate daily EV charging load curves in an EV charging station considering random traffic behaviors and charging intentions of EV drivers. Secondly, EV charging load curves and historical PV output curves are respectively clustered by the K-means clustering method and subsequently the probabilistic scenarios of the EV charging load profile and the PV output profile are given. Then power flow calculation probabilistic scenarios are built based on the probabilistic scenarios of the EV charging load profile and the PV output profile. The forward-backward sweep method is adopted to investigate the power flow in each calculation scenario. The probabilistic power flow results can be obtained by gathering power flow results in each power flow calculation scenario according to scenario probabilities. Simulation results based on IEEE 33-bus distribution systems justify the proposed model and methodology.
This work is supported by Science and Technology Project of State Grid Corporation of China (No. SGJSSZ00KJJS 1903295). |
Key words: probabilistic power flow electric vehicle charging scenario probability K-means clustering forward- backward sweep method |