Abstract
Multi-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, Fuzzified Coulomb’s and Franklin’s Laws Behaved Optimization (FCFLBO) approach is proposed to solve the MAMFED problem. Coulomb’s and Franklin’s Laws Behaved Optimization (CFLBO) approach is developed from Coulomb’s and Franklin’s theories, which encompass fascination/aversion, ionization, and contact stages. The suggested approach considers the line losses, valve point loading impacts, multi-fuel alternatives, and tie-line limits of the power system. Because of the contradicting nature of fuel cost and pollutant emission objectives, weighted sum approach and price penalty factor are used to transfer the bi-objective function into single objective function. Furthermore, a fuzzy decision strategy is introduced to find one of the Pareto optimal fronts as the best comprised solution. The feasibility of the FCFLBO algorithm is tested on a three-area test system for both the single-area multi-fuel economic dispatch and MAMFED problems. The results of FCFLBO algorithm are compared with those of the krill herd algorithm, exchange market algorithm and other heuristic approaches surfaced in the literature. To show the effectiveness of FCFLBO algorithm, multi-objective performance indicators such as generational distance, spacing metric and ratio of non-dominated individuals are evaluated. The results divulge that the FCFLBO is a promising approach to solve the MAMFED problem as it furnishes better compromised solution in comparison with the other heuristic approaches.
Highlights
The goal of Multi-Area Multi-Fuel Economic Dispatch (MAMFED) problem is to decide the power delivered by every generator in various areas and the power stream between the areas in order to lessen the total production cost and pollutants outflows of the interconnected power system considering multi-fuel alternatives of each generating unit
The approach was tested on 3 different systems and the results revealed that the presented approach had the ability to provide better solutions and exhibited greater robustness than Differential Evolution (DE), Evolutionary Programming (EP), and Real-Coded Genetic Algorithm (RCGA)
The aim of the MAMFED problem is to find the amount of power that can be efficiently generated in one area and transferred to another area, and to determine the economic fuel choice for each unit
Summary
The goal of MAMFED problem is to decide the power delivered by every generator in various areas and the power stream between the areas in order to lessen the total production cost and pollutants outflows of the interconnected power system considering multi-fuel alternatives of each generating unit. Basu proposed artificial bee colony (ABC) optimization [13] to solve a MAED problem with tie-line constraints, transmission losses, multiple fuels, and valve point effects Evolutionary approaches such as DE, EP, and RCGA were applied to analyze the efficiency of the ABC approach. A novel swarm intelligence approach using salp swarm algorithm for the solution of multi-area generation scheduling with wind integration was presented [26] These improved and hybrid forms of heuristic approaches involve complicated computation owing to the use of many control parameters. The FCFLBO algorithm successfully solves the Single Area Multi-Fuel ED (SAMFED) such that the fuel costs and pollutant emissions are simultaneously minimized while fulfilling the power balance and generation limits.
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