A Multiobjective Artificial-Hummingbird-Algorithm-Based Framework for Optimal Reactive Power Dispatch Considering Renewable Energy Sources

Umar Waleed, Abdul Haseeb, Muhammad Mansoor Ashraf, Faisal Siddiq, Muhammad Rafiq () and Muhammad Shafique
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Umar Waleed: Faculty of Electrical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi 23460, Pakistan
Abdul Haseeb: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Muhammad Mansoor Ashraf: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Faisal Siddiq: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Muhammad Rafiq: Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan
Muhammad Shafique: Department of Civil and Environmental Engineering, Brunel University London, Uxbridge UB8 3PH, UK

Energies, 2022, vol. 15, issue 23, 1-23

Abstract: This paper proposes a new artificial hummingbird algorithm (AHA)-based framework to investigate the optimal reactive power dispatch (ORPD) problem which is a critical problem in the capacity of power systems. This paper aims to improve the performance of power systems by minimizing two distinct objective functions namely active power loss in the transmission network and total voltage deviation at the load buses subjected to various constraints within multiobjective framework. The proposed AHA-based framework maps the inherent flight and foraging capabilities exhibited by hummingbirds in nature to determine the best settings for the control variables (i.e., voltages at generation buses, the tap positions of on-load tap-changing transformers (OLTCs) and the size of switchable shunt VAR compensators) to minimize the overall objective functions. A multiobjective optimal reactive power dispatch framework (MO-ORPD) considering renewable energy sources (RES) and load uncertainties is also proposed to minimize the individual objectives simultaneously. The competency and robustness of the proposed AHA-based framework is validated and tested on IEEE 14 bus and IEEE 39 bus test systems to solve the ORPD problem. Eventually, the results are compared with other well-known optimization techniques in the literature. Box plots and statistical tests using SPSS are performed and validated to justify the effectiveness of the proposed framework.

Keywords: artificial hummingbird algorithm; artificial intelligence; optimal reactive power dispatch; optimal power flow; on-load tap-changing transformer (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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