4.2 Article

Economic load dispatch using memetic sine cosine algorithm

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s12652-022-03731-1

Keywords

Economic load dispatch; Hybrid metaheuristics; Sine cosine algorithm; beta-hill climbing optimizer; Power systems

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This paper uses a hybrid sine cosine algorithm (SCA-beta HC) to solve the economic load dispatch (ELD) problem in electrical engineering. The experimental results show that this hybrid algorithm performs well in tackling the ELD problem.
In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. Therefore, beta-hill climbing optimizer, a recent local search algorithm, is hybridized as a new operator in SCA to empower its exploitation capability to tackle ELD. The proposed hybrid algorithm is abbreviated as SCA-beta HC which is evaluated using two sets of real-world generation cases: (i) 3-units, two versions of 13-units, and 40-units, with neglected Ramp Rate Limits and Prohibited Operating Zones constraints. (ii) 6-units and 15-units with Ramp Rate Limits and Prohibited Operating Zones constraints. The sensitivity analysis of the control parameters for SCA-beta HC is initially studied. The results show that the performance of the SCA-beta HC algorithm is increased by tuning its parameters in proper value. The comparative evaluation against several state-of-the-art methods show that the proposed method is able to produce new best results for some tested cases as well as the second-best for others. In a nutshell, hybridizing beta HC optimizer as a new operator for SCA is very powerful algorithm for tackling ELD problems.

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