Heuristic Optimization of Virtual Inertia Control in Grid-Connected Wind Energy Conversion Systems for Frequency Support in a Restructured Environment

Anuoluwapo Oluwatobiloba Aluko, David George Dorrell, Rudiren Pillay Carpanen and Evan E. Ojo
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Anuoluwapo Oluwatobiloba Aluko: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, KwaZulu-Natal, South Africa
David George Dorrell: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, KwaZulu-Natal, South Africa
Rudiren Pillay Carpanen: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, KwaZulu-Natal, South Africa
Evan E. Ojo: Department of Electrical Power Engineering, Durban University of Technology, Durban 4000, KwaZulu-Natal, South Africa

Energies, 2020, vol. 13, issue 3, 1-28

Abstract: In the work reported in this paper, a novel application of the artificial bee colony algorithm is used to implement a virtual inertia control strategy for grid-connected wind energy conversion systems. The proposed control strategy introduces a new heuristic optimization technique that uses the artificial bee colony (ABC) algorithm to calculate the optimal gain value of an additional derivative control loop added to the control scheme of the machine side converter in a wind energy system to enable wind farms to participate in frequency control as specified by recent grid codes. This helps to minimize the frequency deviations, reduce active power deviation in the system, and increase the penetration level of wind energy in power systems. The study was performed in a restructured power system environment. The proposed control scheme and its robustness were evaluated using load–frequency analysis for three real-life transaction scenarios that can occur in an interconnected open-energy market and the validation was carried out using eigenvalue analysis. The results in this study show that the optimal gain of the proposed controller reduces the frequency deviations and improves stability and overall performance of the system.

Keywords: artificial bee colony algorithm; deregulation; load frequency control; heuristic optimization; power system stability; wind energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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