基于混合粒子群优化和差分进化的安全约束无功优化调度

K. P. Nguyen, T. M. Dao
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引用次数: 1

摘要

电力系统在正常工况和应急工况下的优化运行对电力系统的运行具有重要意义。为了保证系统在这两种情况下都能安全运行,最优无功调度(ORPD)问题中应考虑最严重的情况。SCORPD问题的目标是解决正常和突发情况下的ORPD问题,使系统在满足所有单元和网络约束的情况下,总功率损耗、稳定指标或电压偏差最小。本文提出了一种混合粒子群优化与差分进化算法(HPSO-DE)来解决这一问题。该方法将粒子群算法和粒子群算法相结合,充分利用两者的优点,增强了算法的搜索能力。该方法已在IEEE 30总线系统上针对不同的目标和不同的场景进行了实现。结果表明,所提出的HPSO-DE方法对于处理复杂的大规模SCORPD问题是非常有效的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Security Constrained Optimal Reactive Power Dispatch Using Hybrid Particle Swarm Optimization and Differential Evolution
The optimal operation of a power system in both normal and contingency cases has a significant role in the power system operation. To guarantee a system to operate securely in both cases, the most severed case should be included in the optimal reactive power dispatch (ORPD) problem. The objective of the SCORPD problem is to solve the ORPD problem in both normal and contingency cases so that the total power loss, stability index, or voltage deviation is the system is minimized satisfying all unit and network constraints. In this article, a hybrid particle swarm optimization and differential evolution (HPSO-DE) is proposed to solve this SCORPD problem. The proposed method is a combination of PSO and DE methods to utilize their advantages so that the search ability of the method can be enhanced. The proposed method has been implemented on the IEEE 30-bus system for different objectives with different scenarios. The obtained results have been indicated that the proposed HPSO-DE method can be very effective for dealing with the complex and large-scale SCORPD problem
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