并网光伏发电置信容量评估  

Capacity credit evaluation of grid-connected photovoltaic generation

作　　者：余志强[1] 王淳[1] 胡奕涛[1] 钟云[1] 汪硕承 

机构地区：[1]南昌大学电气与自动化系,江西南昌330031

出　　处：《电力系统保护与控制》2016年第7期122-127,共6页Power System Protection and Control

基　　金：国家自然科学基金资助项目(51167012;51467012);江西省研究生创新专项资金项目(YC2014-S066)~~

摘　　要：提出了一种应用含衰老和竞争机制的粒子群算法(Particle Swarm Optimization with Aging and Challenging Mechanism,ACM-PSO),分别从负荷侧和电源侧求解并网光伏发电置信容量。在构建了以常规机组类型数为系统状态变量的基础上,将ACM-PSO算法作为一种系统状态扫描及分类工具筛选出对发电可靠性指标有贡献的系统故障状态集。定义了负荷比例增加方式,以光伏发电接入前后系统电力不足期望(loss of load expectation,LOLE)保持不变为原则,分别从负荷侧和电源侧构建了目标函数,应用ACM-PSO算法求解光伏发电的有效荷载能力和等效常规机组容量。应用改进的IEEE-RTS79测试系统验证了所提方法的有效性。A particle swarm optimization with aging and challenging mechanism（ACM-PSO） is proposed for evaluating the capacity credit of photovoltaic（PV） generation from load side and generation side respectively. Firstly, on the basis of system state variables constructed by the number of types of conventional unit, ACM-PSO is adopted as a scan and classification tool to screen out the system failure state set which contributes to generation reliability indices. Secondly, proportional load increase mode is defined, and with the loss of load expectation remaining unchanged as the principle before and after the PV access, objection functions are constructed both from load side and generation side, and application of ACM-PSO for evaluating the effective load carrying capacity and equivalent conventional unit capacity of PV is executed. Finally, the proposed method is applied to an improved IEEE-RTS79 system to verify its effectiveness.

关 键 词：光伏发电 发电可靠性 有效荷载能力 等效常规机组容量 含衰老和竞争机制的粒子群算法 

分 类 号：TM615[电气工程—电力系统及自动化]