V. Tejaswini’s research while affiliated with Sathyabama Institute of Science and Technology and other places

This paper presents a study on the optimal localization and sizing of a Distribution Static Compensator (D-STATCOM) in power distribution systems using a novel Hybrid Algorithm. The objective is to enhance power quality and minimize total power losses in 33-bus and 69-bus distribution networks. The proposed Hybrid Algorithm, named Bird Swarm Operated Exploitation of Elephant Herd (BSOEEH), is tested under four different scenarios to determine its effectiveness compared to traditional optimization methods. In the 33-bus system at hour 14, the BSOEEH model achieved optimal results, surpassing established methods by significant margins: 1.06% superior to Grey Wolf Optimizer (GWO), 1.02% superior to Whale Optimization Algorithm (WOA), 1.02% superior to the GWO-WOA hybrid model, 0.13% superior to Elephant Herding Optimization (EHO), and 0.93% superior to Backtracking Search Algorithm (BSA). For the 69-bus system at hour 14, the proposed model exhibited even greater improvements, outperforming GWO by 6.16%, WOA by 87.53%, GWO-WOA by 93.72%, EHO by 6.83%, and BSA by 18.55%. These results demonstrate the BSOEEH model’s capability to optimally position and size the D-STATCOM, thereby significantly improving power quality and reducing energy losses in distribution networks. The findings suggest that the proposed Hybrid Algorithm is a robust and efficient solution for modern power distribution systems.

In power systems, parameters such as outage of components and continual load growth may pave the way to problems like dynamic and static inconsistencies like adequacy and security consequences of disturbances. For dealing with such predicaments, deployment of Custom Power Devices is the major widely adopted approach. Anyhow, these devices must be positioned in an optimal location with setting for extracting the most possible benefits. Hence, this paper introduces an Adaptive Step vector based Dragonfly Optimisation (ASDA) to solve the location and sizing issues of D-STATCOM focusing on reactive power compensation. Moreover, the solutions are encoded with two bound constraints to deal with both the localising and sizing issues like minimisation of power loss and Voltage Stability Index (VSI).

This paper intends to propose a power quality design model for the distributed system through nonlinear functions, and hence the prerequisite of power quality enhancements can be precisely quantified. As the model is adaptable, it needs a robust optimization algorithm for estimating the optimal location and compensation of the D-STATCOM. Hence, this paper develops a hybrid meta-heuristic optimization algorithm based on the prey targeting behavior of whales. The proposed hybrid whale optimization, Whale with Grey Wolf Optimization (WG), is used for determining the optimal placing and sizing of D-STATCOM by solving the power quality model. The solutions will be reactive power-encoded with two bound constraints to address both the localizing and sizing problems. Besides, along with the renowned literature, we determine the Mean Voltage Stability Index. The updating algorithm of the whale optimization will be hybridized with the hunting behavior of grey wolves so that the location and sizing of D-STATCOM can be estimated precisely. The proposed WG algorithm compares its performance over other conventional methods such as GA, ABC, PSO, GWO, and WOA in terms of convergence analysis, cost analysis, and total loss and determines the effectiveness of the proposed power quality model.

Power loss reduction, improvement of voltage profile, system reliability and system security are the important objectives that motivated researchers to use custom power devices/FACTS devices in power systems. The existing power quality problems such as power losses, voltage instability, voltage profile problem, load ability issues, energy losses, reliability problems etc. are caused due to continuous load growth and outage of components. The significant qualities of custom power devices /FACTS devices such as power loss reduction, improvement of voltage profile, system reliability and system security have motivated researchers in this area and to implement these devices in power system. The optimal placement and sizing of these devices are determined based on economical viability, required quality, reliability and availability. In published literatures, different algorithms are implemented for optimal placement of these devices based on different conditions. In this paper, the published literatures on this field are comprehensively reviewed and elaborate comparison of various algorithms is compared. The inference of this extensive comparative analysis is presented. In this research, Meta heuristic methods and sensitive index methods are used for determining the optimal location and sizing of custom power devices/FACTS devices. The combination of these two methods are also implemented and presented.