基于多策略差分进化算法的输电网规划

Transmission network planning based on multi-strategy differential evolution algorithm

差分进化(DE)算法是一类基于种群的、具有全局优化性能的、通过实数编码的启发式算法。但差分算法搜索策略过于单一,局部搜索能力差,因此通过增加多策略变异和局部寻优策略来提升全局和局部搜索能力,同时降低搜索时间,使其适应于求解大规模输电网规划问题。采用基于线路投资费用、网损费用、正常运行时的过负荷费用及输电走廊费用的输电网规划模型,通过对Garver-6系统和18节点系统的计算,不仅验证了算法及模型应用于输电网规划的正确性和有效性,而且验证了算法具有很高的计算速度和收敛性,为DE算法的进一步改进应用打下基础。

Differential evolution （DE） algorithm is a real number coding heuristic and global optimization of performance algorithm based on population. But the searching strategy of DE algorithm is too unitary and the local searching capability is very poor, so more mutation strategies and local optimization strategy can raise more global and local searching ability and reduce the searching time, which adapted to solving large-scale transmission network planning. Taking line investment costs, network loss cost, the over-load cost of normal operation and transmission corridor cost as objectives, and through the results of Garver- 6 system and 18 node system, it can not only prove the DE algorithm and model correctness and effectiveness in transmission network planning, but also can demonstrate that the algorithm has high computing speed and convergence, which lay the foundation to the further improving of DE algorithm.