Optimal Location and Sizing of PV-UPQC-O in Distribution Feeders with Electric Vehicles Using Gazelle Optimization Algorithm.

Renewable energy systems (RESs) and electric vehicles (EVs) are critical components of current power systems for lowering greenhouse gas (GHG) emissions, combating climate change, and providing alternative energy sources. However, high initial costs and a lack of infrastructure, power storage, and power quality (PQ) are potential concerns for RESs and EVs in power systems. Among the numerous power quality (PQ) devices, the unified power quality conditioner (UPQC) can compensate for voltage and current-related PQ difficulties, correct the power factor, and is well suited for coordinative operation and control with RESs uncertainty. The position, size, and dynamic VAr control of UPQC, on the other hand, are key influencing variables for enhancing the performance and PQ of electrical distribution systems (EDSs). This paper describes an upgraded UPQC configuration known as open-UPQC (UPQCO) for reducing PQ difficulties caused by the inclusion of PVs and EVs. Further, an efficient gazelle optimization algorithm (GOA) is suggested to solve the multi-objective optimal allocation of the PV-UPQC-O issue with an emphasis on voltage quality, distribution losses, and voltage stability. Simulations were performed for various scenarios using a modified IEEE 33-bus test system. According to the comparison data, the PV-UPQC-O improved the feeder performance more effectively than the standard UPQC and UPQC-O. The proposed PV-UPQC-O results for total loss reduction of 76.15% when compared to base case without EV load penetration. On the other hand, it is around 76.52% reduction when compared to base case with EV load penetration. Furthermore, the proposed GOA outperforms the prairie dog optimization (PDO), pelican optimization algorithm (POA) and coati optimization algorithm (COA) in terms of global solution and convergence. [ABSTRACT FROM AUTHOR]