摘要
随着风机大规模投入运行,多维风电场之间风速的相关性会影响电力系统的稳定性。考虑相关性的概率潮流计算有助于合理地调控电力系统运行方式以及优化调度,从而提升系统的稳定性。文中针对多维风电场之间的相关性,提出了一种基于贝叶斯理论的最大期望算法及Rosenblatt变换的概率潮流三点估计法,该算法能够很好地捕捉风电场之间的非线性相关性,计算多维风电场风速的联合分布函数并应用于概率潮流计算。最后,通过IEEE 118节点系统对算法进行验证,并与蒙特卡洛模拟法及Nataf变换作横向对比,结果表明所提算法兼具精度高、收敛速度快等优势。
With the large-scale integration and operation of wind turbines,the correlation of wind speed between multi-dimensional wind farms will affect the stability of the power system.Probabilistic power flow calculation considering correlation is helpful for reasonably regulating power system operation modes and optimal dispatching,so as to improve the system stability.Aiming at the correlation between multi-dimensional wind farms,a three-point estimation method based on the maximum expectation algorithm of Bayesian theory and Rosenblatt transform is proposed.This algorithm can well capture the nonlinear correlation between wind farms,calculate the joint distribution function of wind speed in multi-dimensional wind farms,and apply it to probabilistic power flow calculation.Finally,the algorithm is verified by the IEEE 118-node system,and compared with Monte Carlo simulation method and Nataf transform.The results show that the proposed algorithm has the advantages of high accuracy and fast convergence speed.
作者
苏晨博
刘崇茹
李至峪
周明
SU Chenbo;LIU Chongru;LI Zhiyu;ZHOU Ming(School of Electrical and Electronic Engineering,North China Electric Power University,Beijing 102206,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2021年第3期157-165,共9页
Automation of Electric Power Systems
基金
国家自然科学基金委员会-国家电网公司智能电网联合基金资助项目(U1866204)。
关键词
贝叶斯理论
最大期望算法
Rosenblatt变换
三点估计法
概率潮流
Bayesian theory
maximum expectation algorithm
Rosenblatt transform
three-point estimation method
probabilistic power flow
