摘要
为衡量光伏出力与负荷的时序变化特性对电力系统运行状态的影响,基于模糊C-均值聚类算法提出一种时序概率潮流快速计算方法。将一天分为24个时段,采用自适应扩散核密度估计法分别建立光伏出力与负荷的概率密度分布模型,提高概率模型局部适应性,并通过Copula理论描述二者之间的相关关系;利用模糊C-均值聚类法划分光伏出力与负荷场景,利用场景聚类中心与场景发生概率代替蒙特卡洛模拟过程进行概率潮流计算,大幅减少计算次数。基于我国西北某地实际测量数据和IEEE 30节点系统进行仿真分析,结果表明所提方法能在保证准确性的前提下,提高时序概率潮流的计算速度。
In order to measure the influence of time sequence changing characteristics of photovoltaic output and load on the operation state of power system,a fast calculation method of time sequence probabilistic power flow is proposed based on fuzzy C-means clustering algorithm.A day is divided into 24 periods,and the adaptive diffusion kernel density estimation method is adopted to build the probability density distribution models of photovoltaic output and load respectively,which improves the local adaptability of the probability model,and the correlation between them is described by Copula theory.The fuzzy C-means clustering method is used to divide the photovoltaic output and load scenarios,and the scenario clustering center and scenario occurrence probability are used to substitute Monte Carlo simulation process for probabilistic power flow calculation,which greatly reduces the calculation times.The simulation and analysis are carried out based on the measured data of a certain place in Northwest China and IEEE 30-bus system,and the results show that the proposed method can improve the calculation speed of time sequence probabilistic power flow on the premise of ensuring accuracy.
作者
李国庆
陆为华
李赫
边竞
王振浩
LI Guoqing;LU Weihua;LI He;BIAN Jing;WANG Zhenhao(Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology,Ministry of Education,Northeast Electric Power University,Jilin 132012,China;Tongliao Power Supply Company of State Grid East Inner Mongolia Electric Power Company Limited,Tongliao 028000,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2021年第4期116-122,共7页
Electric Power Automation Equipment
基金
国网内蒙古东部电力有限公司重点科技项目(SGMDTL00YWJS2000669)。
关键词
扩散核
时序变化特性
模糊C-均值聚类
快速计算
概率潮流
diffusion kernel
time sequence changing characteristics
fuzzy C-means clustering
fast calculation
probabilistic power flow
