【摘要】 针对三相不平衡配电网状态估计问题,设计了带约束整合项的多智能体协同智能水滴优化方法。首先,对三相不平衡配电网数学模型进行研究,并结合协同进化算特点,设计带约束整合项的状态估计适应函数,从而实现算法的无约束运行;其次,利用多智能体协同进化方式对智能水滴算法(IWD)进行改进,每个智能体(Agent)负责一个群体优化,不断引入各子Agent进化结果对全局最优解进行维度更新,实现高维优化问题的协同均衡分解。最后,通过在IEEE 57-bus和123-bus标准算例上的状态估计对比实验,显示所提方法在状态估计误差指标上具有更高的估计精度,并且给出不同网络规模下对比情况,均显示所提算法具有较高计算效率。更多还原

【Abstract】 According to the problem of power state estimation of three phase unbalanced distribution network, the multi-agent based IWD power state estimation algorithm for unbalanced grid with integrated constraints is presented. Firstly, the three-phase unbalanced distribution network mathematical model is researched, and combined with the co-evolutionary algorithm, the integration constraints for the fitness function of power state estimation is designed, so as to realize the unconstrained operation of the algorithm; Secondly, the multi agent collaborative evolution is used for the intelligent water droplets(IWD) algorithm improvement, each agent is responsible for a group optimization, the sub agent evolution results are continuously introduced to the management agent, which achieves high dimensional optimization of collaborative equilibrium decomposition; Finally, by comparing the experimental results with the IEEE 57-bus and 123-bus standard, it is shown that the proposed method has higher estimation accuracy. The comparison of different network scale is given, and the results show that the proposed algorithm has higher computational efficiency.更多还原