基于多智能体遗传算法并考虑分布式电源的配电网大面积断电供电恢复算法

Algorithm of Service Restoration for Large Area Blackout in Distribution Network With Distributed Generators

当配电网发生大面积断电事故后,针对含分布式电源的配电系统,提出采用多智能体遗传算法解决分布式发电条件下配电网大面积断电供电恢复问题。考虑孤岛运行的情况,研究了分布式电源在配电网大面积断电情况下的分层孤岛运行方式,能够充分利用分布式电源的发电能力,减少停电区域。提出的多智能体遗传算法构造了一个环形网格环境,所有智能体都固定在网格上。每个智能体相当于遗传算法中的一条染色体,它们通过与其邻域展开竞争操作和自学习行为来增加目标函数值。对于智能体竞争及自学习行为过程中产生的不可行解,采用改进的基于环路分解的方法消除闭环和孤岛,使其变为可行解。通过一个实际配电系统的仿真计算,仿真结果证明了文中所提方法具有较强的全局搜索能力和快速的收敛速度。

In the event of a large-scale blackout in a distribution network, a service restoration plan must be devised quickly. To remedy such a situation, a restoration method based on the multi-agent genetic algorithm is proposed for the distribution networks with distributed generators （DGs）. All agents in this algorithm which represent the restoration methods live in a lattice like environment, with each agent fixed on a lattice-point. In order to increase object function values, they compete with their neighbors, and they can also use knowledge. For the non-feasible solutions generated in the process of the algorithm, the method of the improved loop decomposition is proposed to eliminate the closed loops and islands. The operation method of DGs is the process of service restoration for large area blackout of distribution system with DGs is researched for making use of the capacity of DGs sufficiently and enhancing the power distribution reliability. Finally, the example results indicate the feasibility of the proposed method.