基于鸟群算法的微电网多目标运行优化  

Multi-objective operation optimization of micro grid based on bird swarm algorithm

作　　者：曾嶒[1] 彭春华[1] 王奎[1] 张艳伟[1] 张明瀚[1] 

机构地区：[1]华东交通大学电气与电子工程学院,江西南昌330013

出　　处：《电力系统保护与控制》2016年第13期117-122,共6页Power System Protection and Control

摘　　要：为了在微电网的运行中寻找到最理想的调度策略,对于微电网的多目标优化问题,采用传统智能算法求解易陷入局部最优而难于找到全局最优解,因此采用一种生物启发式算法——鸟群算法,对以运行成本及环境污染度为目标的微电网多目标优化模型进行求解。该算法模仿鸟群觅食、警觉、迁移的习性,生成对应的种群更新策略,兼具粒子群算法搜索效率高和微分进化算法稳定性好的优点。通过与两者寻优结果比较,表明该算法具有较强的全局、局部搜索能力且收敛鲁棒性好的特点。In order to find the best scheduling strategy in the operation of the micro grid, it is easy to fall into local optimal and difficult to find the global optimal solution by using traditional intelligent algorithm to solve the micro grid optimization problem, thus using a bio-inspired method named Bird Swarm Algorithm to solve a multi-objective optimization model for micro grid taking operation cost and environmental pollution as objectives. The algorithm puts forward the corresponding strategies of population renewal imitating the birds＇ foraging behavior, vigilance behavior and flight behavior. It has the advantages in high efficiency as Particle Warm Optimization （PSO） and stability as Differential Evolution algorithm （DE）. It shows strong global and local search ability and high robustness when compared with PSO and DE.

关 键 词：鸟群算法 粒子群算法 微分进化算法 微电网 多目标优化 

分 类 号：TM732[电气工程—电力系统及自动化]