基于差分进化生物地理学算法的经济负荷分配  

Hybrid Biogeography Constrained Optimization for Economic Dispatch

作　　者：闫顺林[1] 谷兵[1] 田东旭[1] 艾书剑 

机构地区：[1]华北电力大学能源动力与机械工程学院,河北保定071003

出　　处：《电力科学与工程》2016年第3期31-36,共6页Electric Power Science and Engineering

摘　　要：针对智能算法在解决经济负荷分配问题时全局搜索能力和局部寻优能力不平衡的缺陷,提出了差分进化生物地理学算法。通过融合生物地理学算法和差分进化算法,并改进了算法中变异操作和替换重复个体策略,实现了的局部利用能力和全局搜索能力的平衡。通过建立求解经济负荷分配模型,兼顾考虑了燃料成本、阀点效应、环境成本以及各种约束条件,对具体案例仿真计算,将优化结果与生物地理学算法、差分进化算法和粒子群算法比较分析。结果表明差分进化生物地理学算法在收敛速度和优化质量方面较优,进而体现了该算法在解决经济负荷分配问题时的有效性和优越性。In the light of the defect of intelligent algorithms that global search ability and local search capability are imbalance in solving the economic load dispatch problem, a hybrid biogeography based optimization with differential evolution was proposed. By combining biogeography algorithm and differential evolution algorithm and improving balance algorithm mutation as well as replacing duplicate individual strategies, the abilities of local exploitation and global exploration are balanced and improved. The algorithm is used to solve the economic load dispatch problem by taking into account fuel costs, valve point effect, environmental costs and various constraints. It shows that the con- vergence rate and convergence precision are preponderant through simulation of specific cases, comparing with biogeography based optimization, differential evolution and particle swarm optimization.

关 键 词：经济负荷分配 生物地理学算法 差分进化 约束优化 

分 类 号：TM73[电气工程—电力系统及自动化]