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

作　　者：梁双[1] 胡学浩[1] 张东霞[1] 王皓怀[1] 张宏宇[1] 

机构地区：[1]中国电力科学研究院,北京市100192

出　　处：《电力系统自动化》2012年第13期32-37,共6页Automation of Electric Power Systems

摘　　要：随着光伏发电在电网中穿透功率水平的不断提高,光伏发电的置信容量评估问题逐渐成为电网规划中关注的新热点。针对光伏发电与电网负荷的不确定性,文中在序贯小时确定性模型的基础上建立了光伏出力与电网负荷的随机模型,利用序贯小时确定性模型反映光伏出力与电网负荷以及光伏电站之间在长时间尺度上的相关性,采用秩相关系数来描述短时间尺度上的相关性,提出了一种可处理随机变量相关性的基于拉丁超立方采样的光伏发电置信容量评估方法。通过对IEEE-RTS 79系统进行评估,验证了所提出方法的有效性和准确性。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 

分 类 号：TM615[电气工程—电力系统及自动化]