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首页> 外文期刊>Journal of The Institution of Engineers (India): Series B >Economic Load Dispatch Using Adaptive Social Acceleration Constant Based Particle Swarm Optimization
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Economic Load Dispatch Using Adaptive Social Acceleration Constant Based Particle Swarm Optimization

机译:基于自适应社会加速度常数的粒子群算法的经济负荷分配

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In this paper, an Adaptive Social Acceleration Constant based Particle Swarm Optimization (ASACPSO) has been developed which uses the best value of social acceleration constant (Csg). Three formulations of Csg have been used to search for the best value of Csg. These three formulations led to the development of three algorithms–ALDPSO, AELDPSO-I and AELDPSO-II which were implemented for Economic Load Dispatch of IEEE 5 bus, 14 bus and 30 bus systems. The best value of Csg was selected based on the minimum number of Kounts i.e. number of function evaluations required to minimize the function. This value of Csg was directly used in basic PSO algorithm which led to the development of ASACPSO algorithm. ASACPSO was found to converge faster and give more accurate results compared to BPSO for IEEE 5, 14 and 30 bus systems.
机译:在本文中,基于社会加速度常数(Csg)的最佳值的自适应社会加速度常数的粒子群优化(ASACPSO)已被开发。三种Csg配方已被用来寻找Csg的最佳价值。这三个公式导致开发了三种算法-ALDPSO,AELDPSO-I和AELDPSO-II,它们被实现用于IEEE 5总线,14总线和30总线系统的经济负荷分配。 Csg的最佳值是根据最小的Kounts(即最小化功能所需的功能评估次数)选择的。 Csg的这个值直接用于基本的PSO算法中,从而导致了ASACPSO算法的发展。与针对IEEE 5、14和30总线系统的BPSO相比,发现ASACPSO收敛更快,并且给出的结果更准确。

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