基于万有引力搜索算法的含分布式电源配电网无功优化研究

Research on Reactive Power Optimization of Distribution Network with Distributed Generation Using GSA Method

文章研究了含有分布式电源的配电网多目标无功优化问题。为在提高电网运行经济性的同时增强电压稳定性,以配电网的有功网损最低和负荷节点电压偏差最小为目标构建多目标优化模型,利用随机数学模型描述分布式电源有功出力的不确定性,使用一种新型的启发式算法万有引力搜索算法对FACTS补偿装置的无功补偿容量以及安装位置进行优化求解。同时利用IEEE 33节点测试系统对文章所提方法的有效性进行仿真验证,算例仿真结果表明,所提出方法在有效降低了系统网损的同时,也有效提高了系统的稳定性,具有很强的实用性。

This paper focuses on the multi-objective reactive power optimization with distributed generation. In order to enhance the voltage stability while improving the operation economy of the power grid, a multi-objective optimization model is constructed with the goal of minimizing the active power loss of the power grid and the voltage deviation of the load nodes. The idea of probability statistics is applied to solve the uncertain output of the distributed power sources. Besides, a novel metaheuristic search algorithm Gravitational Search Algorithm （GSA） is used to optimize the compensation capacity and installation location of flexible alternative current transmission systems （FACTS） devices. The IEEE 33-bus system is used to verify the simulation results. The simulation results show that the proposed method can effectively reduce the system loss and improve the system stability effectively.