摘要
针对目前风电消纳能力的评估研究方法不能全面考虑电力系统随机性因素对风电消纳能力影响的不足,从电力系统中的不确定因素出发,考虑系统负荷的随机性,提出一种风电消纳能力的概率评估方法。首先采用加权高斯混合分布对负荷进行概率建模,然后采用切片采样算法对负荷的概率模型进行采样并获得其样本空间,最后将样本值依次代入潮流方程进行潮流计算,确定每组样本值在满足系统安全运行前提下所对应的最大风电接入功率,并统计其概率指标。对含有风电接入的IEEE 39节点系统进行仿真计算,当采样规模为3000次时,基于切片采样算法的马尔科夫链蒙特卡洛模拟法(S-MCMC)的标准差仅为0.08%,由此验证了该研究方法相比于传统研究方法的准确性和有效性。
According to the insufficient of the wind power accommodation assessment,this paper proposed a new probabilistic assessment method. In the method,the randomness of the system load is considered. Firstly,the Gaussian mixture model of the power load is constructed. Secondly,the sample space of the load power is obtained by slice sampling from the probability model of load power. Finally,the sample values are substituted into the power flow equation to calculate the power flow and the value of the maximum wind power is determined under the condition of system safety operation constraints. The results of traditional research methods and the proposed method are compared in the reconstructive IEEE 39-bus system. When the sample size is 3000,the standard deviation of S-MCMC(Markov chain Monte Carlo with slice sampling)is only 0.08%,which shows that the proposed method has high accuracy and effectiveness.
作者
张晓英
汪彬
王琨
王晓兰
陈伟
Zhang Xiaoying;Wang Bin;Wang Kun;Wang Xiaolan;Chen Wei(College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China;State Grid Gansu Electric Power Company Electric Power Research Institute,Lanzhou 730050,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2019年第2期341-347,共7页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51867015
51767017)
甘肃省基础研究创新群体项目(18JR3RA133)
甘肃省高校协同创新团队项目
关键词
风电消纳
概率评估
高斯混合模型
切片采样
wind power accommodation
probabilistic assessment
weighted Gaussian mixture model
slice sampling
