A hybrid swarm intelligence approach for resolving reactive power dispatch issues in power system: Optimal placement and sizing of UPFC. (August 2022) - Sharma, Sudhir; Sabitha, B.; Prabhakaran, Anush; Chavan, Meena; Srivastava, Rajat
Highlights: The highlights of the article are given below for your kind perusal. Kindly, consider and forward my article for further processes. . This paper solves the ORPD problem under unbalanced conditions by determining the optimal location and size of UPFC. A scenario of multiple objectives like LSI, VDI, ATC and CUPFC is considered, which is determined optimally for placing the UPFC. This optimal placement is accomplished via a new BAEHO model, which is the conceptual hybridization of EHO and BSA. The BAEHO was implemented in the IEEE 30 and IEEE 57 test bus systems. The BAEHO was tested in terms of LSI, VDI, CUPFC and ATC to validate the efficiency of the BAEHO in achieving the objective F The proposed multi-objectives based proposed optimal UPFC location and sizing model is compare over the existing models like GA-PSO, GA-FF, EHO and BSA, respectively. Abstract: The most critical feature of current energy management systems is ORPD, which is used to maintain safe and reliable working conditions for power networks. Currently, due to their economic and technological advantages, HVDC transmission systems are commonly used in modern electrical power systems. The incorporation of DC link introduces more complexity in ORPD computation. Therefore, an attempt is made to optimally place and size the UPFC. In the transmission network, the UPFC is an efficient multi-purpose FACTS controller for handling the reactive as well as the physical power individually in a rapid manner. This paper plans to develop a new hybrid approach referred as Backtraping Assisted Elephant Herding Optimization (BAEHO), to address the RPD issues in a power system under unbalanced conditions. The introduced hybridized approach further determines the optimal position and size for placing the UPFC based on the constraints like the LSI, VDI, ATC, and CUPFC . Moreover, the proposed algorithm is proved for its performance in maintaining a better trade-off among multiple objectives, even under overloading conditions.