Optimal allocation of flexible AC transmission system (FACTS) for wind turbines integrated power system

Author:

Awad Ayman1,Kamel Salah1ORCID,Hassan Mohamed H.2,Zeinoddini‐Meymand Hamed3ORCID

Affiliation:

1. Department of Electrical Engineering, Faculty of Engineering Aswan University Aswan Egypt

2. Ministry of Electricity and Renewable Energy Cairo Egypt

3. Department of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran

Abstract

AbstractThe importance of flexible alternating current transmission system (FACTS) devices is increasing day by day as they provide compensation for power systems. The installation of such devices solves many issues regarding the stability and power transferability of power systems. However, for optimizing the performance of FACTS devices, the location and sizes of FACTS devices must be selected very carefully. On the other side, the utilization of optimization techniques is increasing daily, as it is capable of solving nonlinear, random problems by its stochastic nature. As a result, it became a reliable tactic for solving stochastic problems almost in every aspect of our lives. Therefore, it is adopted for solving power system problems, like, FACTS devices allocation, distributed generators allocation, determining component's parameters, and more. In this paper, the optimal size and location of several FACTS devices are selected to achieve the following single objective functions separately: fuel cost minimization and power losses minimization, then combining the mentioned objective function into one multiobjective function for gross cost minimization. The power system optimized is the Institute of Electrical and Electronics Engineers 30‐bus standard system, and the FACTS devices installed are static VAR compensator, thyristor control series compensator, and thyristor‐controlled phase shifter, while the optimization is performed using different conventional and recent optimization algorithms, including a newly developed algorithm, typically Leader Walrus Optimization Algorithm “LWaOA,” making a comparison among such algorithms to investigate the algorithm that possesses the best performance. The results of the optimization processes show the superiority of LWaOA.

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

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