Social welfare maximization with thyristor-controlled series compensator using grey wolf optimization algorithm. Issue 2 (April 2021)

• Record Type: Journal Article
• Authors: Kumari Behera, Saswati; Kant Mohanty, Nalin
• Is Part Of: International journal of electrical engineering education. Volume 58:Issue 2(2021)
• Page Start: 209
• Page End: 222
• Publication Date: 2021-04
• Subjects: Deregulation -- grey wolf optimization -- genetic algorithm -- social welfare -- optimal power flow; Electrical engineering -- Study and teaching (Higher) -- Periodicals; Electrical engineering -- Periodicals; 621.30711
• DOI: 10.1177/0020720918822754
• Languages: English
• ISSNs: 0020-7209

Abstract

The present day power scenario is to improve the deregulated structure of power pool so as maximize the overall welfare of the electricity market. Hence, this paper presents a novel methodology to maximize the social welfare (i.e. the surplus of market participants) with thyristor-controlled series compensator using grey wolf optimization algorithm. Thyristor-controlled series compensator can redistribute the power flow in the network thereby aids mitigating congestion and improves the social welfare of the system. Optimal placement and sizing of thyristor-controlled series compensator is a complex combinatorial analysis, hence grey wolf optimization algorithm, which is a typical metaheuristic algorithm based on leadership and hunting of grey wolves in nature is applied to solve the test cases. An optimal power flow problem is proposed to maximize the social welfare using grey wolf optimization with and without thyristor-controlled series compensator. This model is tested with a modified IEEE 14 and IEEE 30 bus test systems. The results obtained using grey wolf optimization is compared with that obtained using genetic algorithm. Results indicate that grey wolf optimization outperforms genetic algorithm in maximizing social welfare either with thyristor-controlled series compensator or without thyristor-controlled series compensator.