电力系统自动化2012，Vol.36Issue(13)：32-37,6.
基于随机模型的光伏发电置信容量评估方法
Probabilistic Models Based Evaluation Method for Capacity Credit of Photovoltaic Generation
梁双 1胡学浩 1张东霞 1王皓怀 1张宏宇1
作者信息
摘要
Abstract
As the penetration level of photovoltaic （PV） generation increases rapidly in recent years, PV capacity credit evaluation is becoming one of the most important issues in the power system planning. Considering the uncertainties of PV output and network loads, a probabilistic model based on improved-sequential hour-deterministic method is established. The deterministic model reflects the long-time scale correlation between the PV output and the network load and also between different PV outputs. The rank correlation coefficients reflect the short-time ones. Based on Latin hypercube sampling （LHS） technique, a novel evaluation method for the PV capacity credit is proposed by considering the correlations between random variables. The effectiveness and accuracy of the method are proved by simulation tests on IEEE RTS 79 system.关键词
光伏发电/置信容量/有效载荷能力/随机模型/拉丁超立方采样/秩相关系数Key words
photovoltaic generation/capacity credit/effective load carrying capability (ELCC)/probabilistic model/Latin hypercube sampling (LHS)/rank correlation coefficient分类
信息技术与安全科学引用本文复制引用
梁双,胡学浩,张东霞,王皓怀,张宏宇..基于随机模型的光伏发电置信容量评估方法[J].电力系统自动化,2012,36(13):32-37,6.
