Solving Renewables-Integrated Economic Load Dispatch Problem by Variant of Metaheuristic Bat-Inspired Algorithm

Faisal Tariq, Salem Alelyani, Ghulam Abbas, Ayman Qahmash and Mohammad Rashid Hussain
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Faisal Tariq: Department of Electrical Engineering, The University of Lahore, Lahore 54000, Pakistan
Salem Alelyani: Center for Artificial Intelligence (CAI), King Khalid University, Abha 61421, Saudi Arabia
Ghulam Abbas: Department of Electrical Engineering, The University of Lahore, Lahore 54000, Pakistan
Ayman Qahmash: Center for Artificial Intelligence (CAI), King Khalid University, Abha 61421, Saudi Arabia
Mohammad Rashid Hussain: Center for Artificial Intelligence (CAI), King Khalid University, Abha 61421, Saudi Arabia

Energies, 2020, vol. 13, issue 23, 1-36

Abstract: One of the most important concerns in the planning and operation of an electric power generation system is the effective scheduling of all power generation facilities to meet growing power demand. Economic load dispatch (ELD) is a phenomenon where an optimal combination of power generating units is selected in such a way as to minimize the total fuel cost while satisfying the load demand, subject to operational constraints. Different numerical and metaheuristic optimization techniques have gained prominent importance and are widely used to solve the nonlinear problem. Although metaheuristic techniques have a good convergence rate than numerical techniques, however, their implementation seems difficult in the presence of nonlinear and dynamic parameters. This work is devoted to solving the ELD problem with the integration of variable energy resources using a modified directional bat algorithm (dBA). Then the proposed technique is validated via different realistic test cases consisting of thermal and renewable energy sources (RESs). From simulation results, it is observed that dBA reduces the operational cost with less computational time and has better convergence characteristics than that of standard BA and other popular techniques like particle swarm optimization (PSO) and genetic algorithm (GA).

Keywords: renewables incorporated ELD problem; directional bat algorithm (dBA); operational cost; convergence characteristics (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 (4)

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