Novel COVID-19 Based Optimization Algorithm (C-19BOA) for Performance Improvement of Power Systems

Sheikh Safiullah, Asadur Rahman (), Shameem Ahmad Lone, S. M. Suhail Hussain and Taha Selim Ustun ()
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Sheikh Safiullah: Electrical Engineering Department, National Institute of Technology Srinagar, Srinagar 190006, Jammu and Kashmir, India
Asadur Rahman: Electrical Engineering Department, National Institute of Technology Srinagar, Srinagar 190006, Jammu and Kashmir, India
Shameem Ahmad Lone: Electrical Engineering Department, National Institute of Technology Srinagar, Srinagar 190006, Jammu and Kashmir, India
S. M. Suhail Hussain: Electrical Engineering Department, King Fahad University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Taha Selim Ustun: Fukushima Renewable Energy Institute, National Institute of Advanced Science and Technology (AIST), Koriyama 963-0215, Japan

Sustainability, 2022, vol. 14, issue 21, 1-27

Abstract: The ongoing pandemic due to novel coronavirus disease-2019 (COVID-19) has rapidly unsettled the health sector with a considerable fatality rate. The main factors that help minimize the spread of this deadly virus are the proper use of masks, social distancing and antibody growth rate in a person. Based on these factors, we propose a new nature-inspired meta-heuristic algorithm named COVID-19 Based Optimization Algorithm (C-19BOA). The proposed C-19BOA mimics the spread and control behavior of coronavirus disease centered on three containment factors: (1) social distancing, (2) use of masks, and (3) antibody rate. Initially, the mathematical models of containment factors are presented, and further, the proposed C-19BOA is developed. To ascertain the effectiveness of the developed C-19BOA, its performance is verified on standard IEEE mathematical benchmark functions for the minimization of these benchmark functions and convergence to the optimal values. These performances are compared with established bio-inspired optimization algorithms available in the literature. Finally, the developed C-19BOA is applied on an electrical power system load–frequency–control model to test its effectiveness in optimizing the power system parameters and to check its applicability in solving modern engineering problems. A performance comparison of the proposed C-19BOA and other optimization algorithms is validated based on optimizing the controller gains for reducing the steady-state errors by comparing the effective frequency and tie-line power regulation ability of an industrially applied Proportional–Integral–Derivative controller (PID) and Active Disturbance Rejection controller (ADRC). Moreover, the robustness of C-19BOA optimized PID and ADRC gains is tested by varying the system parameters from their nominal values.

Keywords: nature-inspired algorithms; population-based methods; coronavirus disease-2019 (COVID-19); standard benchmark functions; power system control and optimization; Active Disturbance Rejection controller (ADRC) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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