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Application of multi-objective hybrid artificial bee colony with differential evolution algorithm for optimal placement of microprocessor based FACTS controllers
Microprocessors and Microsystems ( IF 1.9 ) Pub Date : 2021-03-02 , DOI: 10.1016/j.micpro.2021.104239
J. Mahadevan , R. Rengaraj , A. Bhuvanesh

Increasing electricity demand, financial concerns for building new power stations have resulted in overloading, extreme power transfer, huge losses, reduced power eminence, consistency issues and voltage contour issues. To overcome these issues Flexible AC Transmission System (FACTS) controllers can be integrated into the transmission systems. Subsequently, it improves stagnant and vigorous enactment. Conversely, site, type and capacity of FACTS controllers have to be optimized to attain the aforesaid objectives. In this study, multiple objectives such as minimization of voltage deviation, losses, cost, and line loading index have been optimized using hybrid Artificial Bee Colony-Differential Evolution (ABC-DE). Three microprocessor controlled FACTS controllers for instance thyristor controlled series compensator (TCSC), static VAR compensator (SVC) and unified power flow controller (UPFC) have been placed optimally on IEEE 30 bus system. The outcomes of hybrid ABC-DE have been validated with the outcomes of particle swarm optimization (PSO). It implies that hybrid ABC/DE outperformed PSO for allocating FACTS controllers by optimizing multiple objectives concurrently.



中文翻译:

基于差分进化算法的多目标杂交人工蜂群在基于微处理器的FACTS控制器最优布置中的应用

电力需求增加,建造新电站的财务问题导致了过载,极端的电力传输,巨大的损失,降低的电力知名度,一致性问题和电压轮廓问题。为了克服这些问题,可以将柔性AC传输系统(FACTS)控制器集成到传输系统中。随后,它改善了停滞和有力的制定。相反,必须对FACTS控制器的位置,类型和容量进行优化,以实现上述目标。在这项研究中,已使用混合人工蜂群-差分进化算法(ABC-DE)优化了多个目标,例如最小化电压偏差,损耗,成本和线路负载指数。三个微处理器控制的FACTS控制器,例如晶闸管控制的串联补偿器(TCSC),静态VAR补偿器(SVC)和统一潮流控制器(UPFC)已最佳放置在IEEE 30总线系统上。混合ABC-DE的结果已通过粒子群优化(PSO)的结果进行了验证。这意味着通过同时优化多个目标,混合ABC / DE在分配FACTS控制器方面要优于PSO。

更新日期:2021-03-02
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