摘要
随着风能资源的广泛应用,机组组合问题求解愈显复杂。以减少煤耗费用提高系统经济性为目标,提出一种采用遗传萤火虫算法求解含风电电力系统机组组合问题的新方法。引入遗传算法双矩阵通路判断及约束修复策略,提高了初始解生成质量及产生速度;再利用萤火虫算法求解连续负荷经济优化分配,给出自适应交叉概率,从而提高了算法的收敛速度。应用所提算法对经典10机系统优化仿真表明,与其他算法相比,该方法能合理安排机组组合,提高系统供电的经济性,具有较好的实用价值。
With the continuous increasing utilization of wind energy resources in power system,the solution of unit commitment problems become more complicated.This paper proceeded from reducing coal costs and established an optimization model of unit commitment with wind power and a hybrid Genetic algorithm and Firefly algorithm was proposed. Genetic algorithm with double matrix judgment and constraint repair strategy were used to produce initial population, which improved the solution quality and generation speed.The continuous sub-problem of economic load dispatch was solved by Firefly algorithm based adaptive crossover probability,improving the algorithm's convergence speed.Simulation results of 10-unit system show that the hybrid algorithm has better global search capabilities,reasonable arrangements for thermal unit commitment and it also improves economy of power supply,which has good practical values.
作者
冀子臻
顾圣平
JI Zi-zhen;GU Sheng-ping(College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China)
出处
《水电能源科学》
北大核心
2018年第12期152-155,共4页
Water Resources and Power
关键词
电力系统
风力发电
机组组合
遗传算法
萤火虫算法
electric power system
wind power
unit commitment
Genetic algorithm
Firefly algorithm
