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A modified hybrid particle swarm optimization approach for unit commitment

机译:改进的混合粒子群算法用于机组承诺

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This paper presents a new solution to thermal unit-commitment (UC) problem based on a modified hybrid particle swarm optimization (MHPSO). Hybrid real and binary PSO is coupled with the proposed heuristic based constraint satisfaction strategy that makes the solutions/particles feasible for PSO. The velocity equation of particle is also modified to prevent particle stagnation. Unit commitment priority is used to enhance the performance of binary PSO. The proposed algorithm is tested for 10, 20, 40 and 60 unit systems and the results are reported for 10 different runs. Statistical results and their comparison show a good performance of MHPSO over other existing optimization methods.
机译:本文提出了一种基于改进的混合粒子群算法(MHPSO)的热机组承诺(UC)问题的新解决方案。混合的实数和二进制PSO结合提出的基于启发式的约束满足策略,使解决方案/粒子对于PSO可行。还修改了粒子的速度方程,以防止粒子停滞。单元承诺优先级用于增强二进制PSO的性能。该算法针对10、20、40和60个单位的系统进行了测试,并报告了10次不同运行的结果。统计结果和它们的比较表明,MHPSO优于其他现有的优化方法。

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