Solving the environmental/economic dispatch problem using the hybrid FA-GA multi-objective algorithm. (November 2022)

• Record Type: Journal Article
• Authors: Dashtdar, Masoud; Flah, Aymen; Hosseinimoghadam, Seyed Mohammad Sadegh; Reddy, Ch. Rami; Kotb, Hossam; AboRas, Kareem M.; Jasińska, Elżbieta; Jasiński, Michał
• Is Part Of: Energy reports. Volume 8(2022)
• Page Start: 13766
• Page End: 13779
• Publication Date: 2022-11
• Subjects: Economic dispatch -- Optimization -- Operating costs -- Emission of pollution -- FA-GA algorithm; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2022.10.054
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: The emissions of polluting gases due to the consumption of fossil fuels in power plants have caused that in addition to operating costs, minimizing the amount of pollution in power plants is also given special attention. In this study, the hybrid firefly algorithm (FA) and genetic algorithm are used to solve the problem of environmental economic dispatch (EED) of power between thermal power plants in order to reduce operating costs and environmental pollution while accounting for the nonlinear constraints of power plants such as the effect of a steam valve, prohibited zones of generation, and generation change rate of plants (GA). Basing on the advantageous of these two optimization algorithms, the proposed application have make a combination between these algorithms and have concluded to have a hybrid FA-GA multi-objective algorithm, which can resolve this complicate optimization problem. The algorithm starts with a set of fireflies that are randomly distributed in the problem space, and these particles converge to the optimal solution of the problem during the evolutionary stages. Then a local search plan is presented and implemented as a way to search the neighborhood to improve the quality of the answers. This part of the algorithm is used to search for sparsely populated areas to find the dominant answers. To improve the algorithm, changes have been made in the criteria for determining the best global optimum for each firefly, as well as the best local optimum. The use of this method has increased the uniformity of the Pareto curve Finally, the suggested algorithm is applied on the 39-bus IEEE system by specifying the indices of losses, voltage stability, and emission of pollutants in the multi-objective problem and its results show its proper performance in comparison with other methods. Actually, the proposed control application have conducted to observe the minimum cost and gaz emission face five other conventional used algorithms.