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。
【英文摘要】
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, a...
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