基于MAPSO优化的智能配电网大面积断电供电恢复

当含分布式电源的智能配电网发生大规模停电事故时，必须尽快制定供电恢复计划，减少停电面积。在保证配电网安全运行的前提下，考虑以甩负荷最少及开关操作次数最少两方面因素建立含分布式电源的智能配电网供电恢复模型，提出采用多智能体粒子群优化算法快速恢复孤岛外非故障断电区域负荷供电。该算法在二进制粒子群优化算法基础上引入Multi-Agent概念，每一个Agent相当于一个粒子，通过粒子Agent之间的竞争与合作操作使其快速有效地收敛到全局最优解。算例结果证明了所提算法的可行性和有效性。

Service Restoration for Large Area Blackout of Smart Distribution System Based on MAPSO

In the event of a large blackout in smart distribution system with distributed generators, a service restoration plan must be devised quickly to reduce outage area. Under safe operation constraint, a service restoration model for smart distribution system with DGs is established with consideration of minimizing load shedding and number of switching operation. A Multi-Agent particle swarm optimization algorithm(MAPSO) is proposed for rapid service restoration of non-fault regions. The algorithm introduces Multi-Agent concept to binary particle swarm optimization algorithm. Each Agent is a particle which competes and cooperates with their neighbors, and MAPSO finds the minimum value of objective function with global knowledge. Example result indicates the feasibility and effectiveness of proposed method.