International Journal of Advances in Electrical Engineering
2022, Vol. 3, Issue 1, Part A
Development of hybridized evolutionary algorithm for solving economic environmental dispatch problem in Nigerian power system
Author(s): Oyajide Depo O, Olanite Olanrewaju A and Omotayo Mayowa E
Abstract: Economic Pollution Dispatch (EED) has been the subject of several approaches in recent years. EED-based algorithms may be used in place of traditional optimization approaches. Many different types of modern power generation units include non-linear properties such as valve charging effects, ramp rate constraints, and polynomial estimates of fuel cost and pollution that these approaches haven't been proven to explain. All of this may lead to poor results and lengthy calculations. Because of the global optimum of functional EED problems, conventional techniques have found it difficult to produce a range of metaheuristic solutions in the last two decades. EP, PSO, DSO, self-adapting modified firefly algorithm, chaotic quantum genetic algorithm. Various methods for addressing the EED issue have been described in the literature. As a result, traditional approaches that rely on derivate are unable to provide large ranges of Pareto fronts since the real EED problem is significantly non-linear. Load scheduling becomes more difficult because of these constraints. Meta-heuristic optimization is becoming more popular among academics as a way to get around the limits of traditional approaches. Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and the Classification Based Surrogate Aided Algorithm (CSEA) were used in this work to solve the issue of convergence to a diverse assortment of Pareto front solutions for the EED problem. This method will handle convex and non-convex dispatch economic issues, as well as microgrid dispatch problems. With demand for the power system and operational limit limitations, the convex ED problem yields the quadratic cost structure. The non-convex ED problem explains the engine's nonlinearities, such as valve point loads, restricted working zones, and various power alternatives. This problem aims to find a strategy for distributing a generation of dedicated generators in order to meet demand while minimizing fuel costs and pollutant emissions while adhering to different fairness and inequality restrictions. Nonlinear and linear constraints are used in a multi-objective optimization problem with the purpose of reducing costs and pollution. This research will provide the groundwork for more efficient power generator dispatch, allowing power system managers to make more informed choices.
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How to cite this article:
Oyajide Depo O, Olanite Olanrewaju A, Omotayo Mayowa E. Development of hybridized evolutionary algorithm for solving economic environmental dispatch problem in Nigerian power system. Int J Adv Electr Eng 2022;3(1):09-17.