A Modified Hybrid Particle Swarm Optimization With Bat Algorithm Parameter Inspired Acceleration Coefficients for Solving Eco-Friendly and Economic Dispatch Problems

• Published in: IEEE access Vol. 9; pp. 82169 - 82187
• Main Authors: Ellahi, Manzoor, Abbas, Ghulam, Satrya, Gandeva Bayu, Usman, M. Rehan, Gu, Jason
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biofuels; Computing time; Cost function; Economics; Electric power generation; Emission-economic dispatch (EED); Heuristic methods; HPSO-BAAC; Hybrid power systems; Load sharing; optimal economic dispatch (OED); Parameter modification; Particle swarm optimization; Power dispatch; Power system stability; Power systems; Prohibited operating zones; prohibited operating zones (POZs); ramp-rate limits (RRLs); regional load sharing dispatch (RLSD); Renewable energy sources; renewable energy sources (RESs); Thermal power plants; thermal power plants (TPPs); valve point loading (VPL); Wind power generation
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3085819

The paper presents a modified hybrid particle swarm optimization with bat algorithm parameter inspired acceleration coefficients (MHPSO-BAAC) without and with the constriction factor to find the optimal solution of the economic dispatch problems (EDPs) incorporating conventional as well as hybrid and renewable energy sources (RESs) based plants. The algorithm is designed by modifying the recently presented hybrid PSO and BA (HPSOBA) algorithm applied for the achievement of the optimal solution of the EDPs. The modified algorithm is implemented to solve EDPs of all RESs-based power systems for three scenarios, without constraints, with time-varying demand, and with the consideration of regional load sharing dispatch (RLSD). The performance of the algorithm is also verified through the implementation of various combinations of hybrid as well as thermal power plants (TPPs). The case of TPPs consists of three different scenarios: 1) a small-scale system with constraints like ramp-rate limits (RRLs), prohibited operating zones (POZs), and power losses; 2) a medium-scale power system with consideration of emission-economic dispatch (EED); 3) a large-scale power system with valve-point loading (VPL) effect. The results of the designed MHPSO-BAAC algorithm are compared with the various metaheuristic algorithms available in the literature and the comparative analysis shows the superior performance of the developed algorithm in terms of fuel cost reduction, fast convergence, and computational time.