基于二进制自适应微分进化算法的机组组合问题  

A Binary Adaptive Differential Evolution Algorithm for Unit Commitment

作　　者：夏澍[1] 张建华[1] 刘自发[1] 葛晓琳[1] 

机构地区：[1]电力系统保护与动态安全监控教育部重点实验室(华北电力大学),北京市昌平区102206

出　　处：《电网技术》2010年第4期110-114,共5页Power System Technology

摘　　要：针对机组组合这一典型的非凸、非线性、高维、离散的优化问题,提出了一种二进制自适应微分进化算法。二进制微分进化算法鲁棒性好、搜索效率高,但对控制参数依赖性强,因此采用控制参数自适应调整策略,提高了算法的搜索能力。同时根据机组组合问题的特点,利用优先顺序法则对不满足约束条件的个体进行修正处理,使算法在可行解空间搜索,大大提高了寻优效率。经典算例计算分析结果表明,文中提出的方法稳定性好、寻优速度快、优化结果好,能较好地求解机组组合问题。To solve the unit commitment that is a typical non-convex, nonlinear, high-dimensional and discrete optimization problem, a binary adaptive differential evolution （BADE） algorithm is proposed. Binary differential evolution （BDE） algorithm possess good robustness and high searching efficiency, however it greatly depends on control parameters, therefore an adaptive adjusting strategy for control parameters is integrated with （BDE） algorithm to enhance its searching ability. Meanwhile, based on the characteristic of unit commitment, the individuals that do not conform to the constraint conditions are modified to make the algorithm searching in the space of feasible solution, thus the searching efficiency is greatly improved. Results of classical calculation example show that the proposed method possesses good stability, fast searching speed, good optimization result and can solve unit commitment problem well.

关 键 词：机组组合 二进制微分进化算法 自适应 约束 

分 类 号：TM711[电气工程—电力系统及自动化]