摘要
为了使微电网在运行中能够按照经济效益和环境效益最优化进行调度,同时要求满足负荷的出力需求,建立了包括风力发电机、光伏发电系统、柴油机、微燃机、燃料电池和蓄电池的独立微电网多目标运行优化模型。使用传统智能算法来解决关于微电网的的多目标优化调度问题容易陷入局部最优,难以找到全局最优解,因此提出基于分组思想的混合天牛群算法(beetle swarm optimization,BSO),使用BSO算法作全局搜索、TS算法作局部搜索,并加入Kent混沌机制,对该算法进行了验证,并与粒子群算法进行了对比,结果证明该方法能具有较好的全局收敛性和局部搜索能力。
In order to make the micro grid operation process can get ideal scheduling and optimize the economic and environmental benefits under the condition of the premise of meet the load demand, the multi-objective operation optimization model of independent micro-grid is established, including wind turbine, photovoltaic power generation system, micro-gas turbine, fuel cell, diesel engine and battery.For micro power grid operation optimization scheduling problem, using the traditional intelligent algorithm is easy to fall into local optimum and is difficult to find the global optimal solution, therefore, a hybrid beetle swarm optimization(BSO) algorithm based on the grouping idea is proposed, which uses beetle swarm optimization algorithm for global search and tabu search algorithm for local search, and adds Kent chaos mechanism. The algorithm is verified and compared with particle swarm optimization algorithm. The results show that the algorithm has better global convergence and local search ability.
作者
王怡云
吴雷
Wang Yiyun;Wu Lei(School of Internet of things engineering,Jiangnan University,Wuxi 214122,China)
出处
《电子测量技术》
2020年第16期76-81,共6页
Electronic Measurement Technology
关键词
微电网
多目标优化
经济调度
天牛群算法
micro-grid
multi-objective optimization
economic dispatch
beetle swarm optimization algorithm
