基于改进磷虾群算法的主动配电网无功优化

Reactive Power Optimization of Active Distribution Network Based on Improved Krill Herd Algorithm

随着分布式电源的不断发展,配电网中负荷也呈现多样化的趋势,传统的配电网的无功调控策略和算法已经不能满足现代配电网无功补偿的需求,为此,提出一种基于改进磷虾群算法的主动配电网动态无功优化策略。首先将无功优化过程分为日前调控与日内动态补偿两部分,日前考虑离散型无功补偿设备的无功补偿能力,日内充分考虑风光出力及其他连续调节设备对系统进行补偿,构建基于主动配电网的日前-日内多时间尺度动态无功优化模型。其次提出一种基于余弦控制因子和柯西因子的改进磷虾群算法对该模型进行求解。最后通过修正的IEEE33节点系统的实验,验证了该策略的可行性和有效性,在保证主动配电网平稳运行的同时,实现经济效益最大化。

With the continuous development of distributed power supply, the load in distribution network presents a trend of diversification. The reactive power regulation strategy and traditional algorithm of traditional distribution network can not meet the demand of reactive power compensation of modern distribution network. Therefore, a dynamic reactive power optimization strategy of active distribution network based on improved krill swarm algorithm is proposed to solve the above problems. First of all, the reactive power optimization process is divided into two parts, the dynamic compensation regulation and days before recently considered discrete reactive compensation devices of reactive power compensation capacity, days after fully considering scenery output to compensate the system and other continuous adjusting equipment, active power distribution network based-days before dynamic reactive power optimization model of multiple time scales. Secondly, an improved krill colony algorithm based on cosine control factor and Cauchy factor is proposed to solve the model. Finally, the feasibility and effectiveness of this strategy are verified by the modified IEEE33 node system experiment, which can ensure the smooth operation of active distribution network and realize the maximum economic benefit.