基于混合交叉连续蚁群优化的有效电力调度

Z. Hamid, I. Musirin, M. Rahim, N. A. M. Kamari
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摘要

本文提出了一种以电力调度为目的选择合适发电机的新方法——快速电压稳定指数发电跟踪(FVSI-GT)。与以往基于跟踪功率大小选择发电机的电力跟踪技术不同,该技术基于单个系统发电机贡献的稳定性指标进行发电机选择。在对贡献的稳定指标进行跟踪后,通过一种新的混合优化算法进行发电机待调度功率的确定过程;混合交叉连续蚁群优化(BX-CACO)。在IEEE 30总线可靠性测试系统(RTS)上的实验和验证表明,FVSI-GT方法具有良好的性能,可以通过BX-CACO快速优化,提高系统的静态稳定性、损耗和燃料成本最小化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective power scheduling via Blended Crossover Continuous Ant Colony Optimization
A new method to select suitable generators for the purpose of power scheduling has been proposed in this paper, namely Fast Voltage Stability Index Generation Tracing (FVSI-GT). Contrary to previous power tracing techniques which select the generators based on the magnitude of traced power, the proposed technique performs the generator selection based on the stability index contributed by individual system's generator. After tracing the contributed stability index, the sizing process of generators' power to be dispatched has been performed via a new hybrid optimization algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO). From experiment and validation on IEEE 30 bus reliability test system (RTS), it is revealed that FVSI-GT exhibits great performance as the method capable to select exact generators with the enhancement of system's static stability, losses and fuel cost minimization with fast optimization via BX-CACO.
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