Optimal Solution of Environmental Economic Dispatch Problems Using QPGPSO-ω
Salaria U.A. Menhas M.I. Manzoor S. Butt F.M. Ellahi M. Ali N. Zhassulan O. Mohamed H.G.
June 2023MDPI
Applied Sciences (Switzerland)
2023#13Issue 12
The renewable energy sources (RESs)-based economic dispatch problem (EDP) is of vital importance for modern power systems. Environmental pollution, climatic degradation, and rapidly growing prices of continuously depleting fossil fuels have encouraged researchers to consider mechanisms for RES implementation and optimal operations. This paper presents a quasi-oppositional population-based global particle swarm optimizer with inertial weights (QPGPSO-ω) to solve environment friendly EDPs. The optimization technique is applied to solve the EDP under different scenarios including cases where only renewable energy sources (RESs) are used and the cases where combined emission–economic dispatch (CEED) problem is taken into account. The scenario for RESs includes a combination of six wind, five solar PV, and four biofuel systems for power generation. EDPs are considered without any constraints, and the variability of resources is depicted over time, along with the regional load-sharing dispatch (RLSD). The case of CEED considers ten thermal units with the valve point loading (VPL) effect and transmission losses. The results obtained by the proposed QPGPSO-ω algorithm are better than the reported results employing other optimization methods. This is shown by the lower costs achieved up to USD 8026.1439 for the case of only RES-based EDPs, USD 1346.8 for the case of RES-based EDPs with RLSD, and USD 111,533.59 for the case of CEED. Thus, the proposed QPGPSO-ω algorithm was effective in solving the various adopted power dispatch problems in power system.
economic dispatch problem (EDP) , quasi-oppositional population , renewable energy sources (RESs) , valve point loading (VPL)
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Department of Electrical Engineering, Mirpur University of Science & Technology (MUST), Azad Kashmir, Mirpur, 10250, Pakistan
Department of Electrical Engineering, University of Azad Jammu and Kashmir, Azad Kashmir, Muzaffarabad, 13100, Pakistan
Department of Electrical Engineering, The Superior University, Punjab, Lahore, 54000, Pakistan
Department of Software Engineering, Mirpur University of Science and Technology (MUST), Azad Kashmir, Mirpur, 10250, Pakistan
Department of Special Education, Abai Kazakh National Pedagogical University, Almaty, 050010, Kazakhstan
Department of Electrical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
Department of Electrical Engineering
Department of Electrical Engineering
Department of Electrical Engineering
Department of Software Engineering
Department of Special Education
Department of Electrical Engineering
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