基于引力搜索算法的含分布式电源配电网重构

分布式电源接入配电网将直接改变潮流分布,而网络重构通过改变开关的开合状态以提高供电的可靠性和经济性。以降低网损和缺供电量为目标,以可调度DG的有功输出和开关状态为优化变量,建立多目标协调优化的配电网络重构的数学模型。将引力搜索算法、Pareto最优解理论和模糊决策理论相结合,提出了求解上述模型的多目标混合优化方法,以实现配电网结构和DG出力的协同优化。通过对IEEE33节点测试系统的仿真结果,表明所提出方法能够实现DG出力和网络重构的综合优化和多目标优化,并且在全局寻优能力和收敛速度上表现出色。

Reconfiguration for the Distribution Network with Distributed Generations Based on Gravitational Search Algorithm

Optimal distributed generation injected power to distributed network may improve the flow distribution, and distribution network reconfiguration can improve the reliability and reduce the power loss by changing the state of network switches. In order to reduce network losses and the energy not supplied, this paper makes switch status and DG output as the optimization variables, and establishes a multiobjective optimization model. The paper puts forward a multi-objective mixed optimization method combining gravitational search algorithm and Pareto optimal solution theory with fuzzy decision maker theory, which realizes the collaborative optimization of distributed network structure and DG output. Simulation results show that the proposed method can complete integrated optimization of network reconfiguration and optimal output of DG, and achieve multi-objective optimization, and promise competitive performance not only in the convergence speed but also in the quality of solution.