混合PSO-ACO算法解决小规模电力系统中存在传输损耗的经济负荷调度问题

D. Santra, A. Mukherjee, K. Sarker, D. Chatterjee
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引用次数: 13

摘要

本文提出了一种用混合软计算方法求解小型火电系统凸型和非凸型经济负荷调度问题的新方法。该算法将粒子群优化算法(PSO)与蚁群优化算法(ACO)相结合,利用蚁群优化算法对粒子群优化算法得到的解进行全局优化。该方法考虑了发电机容量限制、输电损耗、匝道速率限制、禁止操作区域和阀点负荷等因素,可用于3-发电机5母线系统的经济调度。在模拟环境中研究了六个测试用例。研究表明,采用PSO-ACO混合算法,可以以最小的发电成本和最小的传输损耗成功地满足300MW的电力需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid PSO-ACO algorithm to solve economic load dispatch problem with transmission loss for small scale power system
This paper presents a novel solution of convex and non-convex economic load dispatch (ELD) problem of small scale thermal power system using a hybrid soft computing approach. The solution method involves a combination of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms where the latter is used to tune the solution obtained by the former towards finding global optima. The proposed approach is found useful in finding economic dispatch in a 3-generator 5-bus system by considering generator capacity constraints, transmission loss, ramp rate limits, prohibited operating zones and valve point loading. Six test cases have been studied in a simulated environment. The paper shows that by applying the PSO-ACO hybrid algorithm 300MW power demand can be successfully met at minimum generation cost incurring minimum transmission loss.
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