基于帝国竞争算法考虑运行风险的电力系统随机无功备用优化

Stochastic Optimal Reactive Power Reserve Dispatch Considering Operating Risk Based on Imperialist Competitive Algorithm

针对目前电力系统中的随机无功备用优化不能控制系统总无功备用风险,从而导致对系统的安全水平评估不准确的问题,首先建立考虑目标函数置信水平的随机无功备用优化模型,采用Nataf变换重构生成风速样本,然后采用蒙特卡洛法将原问题转化为多次的确定型优化运算,最后采用帝国竞争算法对问题进行求解。算例分析结果表明,相比于传统基于期望值目标函数的随机无功备用优化,所提方法可有效控制目标函数的风险;其中帝国竞争算法的采用是该算法效率提升的关键因素。

Owing to the problem that stochastic reactive power optimal reserve can not control the operating risk of the total reactive power reserve in power systems,it does not accurately evaluate the safety of system.A stochastic reactive power optimal reserve model is established considering the confidence level of the objective function.At first,uniform distributed sequences are generated and the Nataf transformation is utilized to reconstruct the samples of wind speed.Then Monte-Carlo simulation method is adopted to convert the stochastic optimization into deterministic ones.Finally,imperialist competitive algorithm（ICA）is employed to solve the problem.The results show that the proposed method is able to control the operating risk of objective function.The multi-group strategy employed in ICA proved to be the main reason for higher computational efficiency by comparison of other algorithms.