基于熵权理论和PSO-DE算法的含DG配电网重构

Reconfiguration of distribution network containing DG based on entropy theory and PSO-DE algorithm

随着分布式电源(Dustributed Geheration,DG)在配电网中的比例不断增加,配电自动化应加强对DG的优化调度以发挥其优势作用,而配电网重构是配电网优化运行的重要措施之一。针对高比例DG接入配电网后的重构问题,通过场景分析的方法来描述DG的随机性。结合配电网有功网损、电压偏移指数、开关操作次数代价以及分布式电源出力风险指标,建立含DG的配电网重构模型,采用基于熵权模型的主客观权重法对重构方案进行评估。将粒子群算法与差分进化算法有效融合,并对算法中的重要参数进行动态更新设置,采用改进后的粒子群-差分进化算法(PSO-DE)对配电网重构模型进行求解。以实际配电网为例,分析不同场景下的DG接入后对配电网重构的影响,结果表明提出的方法能够改善节点电压水平,有效降低配电网的有功功率损耗,提高供电质量和可靠性。

With the increasing proportion of distributed generation in distribution network, distribution automation should enhance the optimal dispatch of distributed generation to play its optimization role. The reconfiguration of distribution network is one of the important measures of distribution network optimization planning. Aiming at the problem of reconfiguration after the distribution of high proportion distributed power into the distribution network, the randomness of distributed generation is described by scenario analysis. A reconfiguration model combined with distribution network active power loss, voltage deviation index, switching operation times cost and distributed power output risk index is established. The subjective and objective weight method based on entropy weight model is used to evaluate the reconfiguration scheme. The particle swarm optimization(PSO) algorithm and the differential evolution algorithm are effectively fused. The important parameters of the algorithm are updated by setting up dynamic parameters. The improved PSO-DE is used to solve the distribution network reconstruction model. The actual distribution network as an example is taked to analyze the impact of renewable energy access on the distribution network reconfiguration under different scenarios. The results show that the method proposed in this paper can improve the node voltage level, effectively reduce the ac-tive power loss of the distribution network, and improve the quality and reliability of power supply.