An Artificial Rabbits’ Optimization to Allocate PVSTATCOM for Ancillary Service Provision in Distribution Systems

Mostafa Elshahed (), Mohamed A. Tolba, Ali M. El-Rifaie (), Ahmed Ginidi, Abdullah Shaheen and Shazly A. Mohamed
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Mostafa Elshahed: Electrical Engineering Department, Engineering and Information Technology College, Buraydah Private Colleges, Buraydah 51418, Saudi Arabia
Mohamed A. Tolba: Reactors Department, Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 11787, Egypt
Ali M. El-Rifaie: College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait
Ahmed Ginidi: Department of Electrical Power Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt
Abdullah Shaheen: Department of Electrical Power Engineering, Faculty of Engineering, Suez University, Suez 43533, Egypt
Shazly A. Mohamed: Electrical Engineering Department, Faculty of Engineering, South Valley University, Qena 83523, Egypt

Mathematics, 2023, vol. 11, issue 2, 1-19

Abstract: Attaining highly secure and safe operation of the grid with acceptable voltage levels has become a difficult issue for electricity companies that must adopt remedial actions. The usage of a PV solar farm inverter as a static synchronous compensator (or PVSTATCOM device) throughout the night has recently been proposed as a way to enhance the system performance. In this article, the novel artificial rabbits’ optimization algorithm (AROA) is developed for minimizing both the daily energy losses and the daily voltage profile considering different 24 h loadings. The novel AROA is inspired from the natural surviving strategies of rabbits. The novel AROA is tested on a typical IEEE 33-node distribution network including three scenarios. Different scenarios are implemented considering PV/STATCOM allocations throughout the day. The effectiveness of the proposed AROA is demonstrated in comparison to differential evolution (DE) algorithm and golden search optimization (GSO). The PVSTATCOM is adequately allocated based on the proposed AROA, where the energy losses are greatly reduced with 54.36% and the voltage deviations are greatly improved with 43.29%. Moreover, the proposed AROA provides no violations in all constraints while DE fails to achieve these limits. Therefore, the proposed AROA shows greater dependability than DE and GSO. Moreover, the voltage profiles at all distribution nodes all over the daytime hours are more than the minimum limit of 95%.

Keywords: artificial rabbits’ optimization; ancillary service provision; distribution systems; PVSTATCOM allocation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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