Abstract
This paper proposes an efficient and new modified differential evolution algorithm (ENMDE) for solving two short-term hydrothermal scheduling (STHTS) problems. The first is to take the available water constraint into account, and the second is to consider the reservoir volume constraints. The proposed method in this paper is a new, improved version of the conventional differential evolution (CDE) method to enhance solution quality and shorten the maximum number of iterations based on two new modifications. The first focuses on a self-tuned mutation operation to open the local search zone based on the evaluation of the quality of the solution, while the second focuses on a leading group selection technique to keep a set of dominant solutions. The contribution of each modification to the superiority of the proposed method over CDE is also investigated by implementing CDE with the self-tuned mutation (STMDE), CDE with the leading group selection technique (LGSDE), and CDE with the two modifications. In addition, particle swarm optimization (PSO), the bat algorithm (BA), and the flower pollination algorithm (FPA) methods are also implemented through four study cases for the first problem, and two study cases for the second problem. Through extensive numerical study cases, the effectiveness of the proposed approach is confirmed.
Highlights
An electrical power system is mainly composed of thermal and hydro power plants connected via transmission lines in order to supply electricity to loads such as industrial zones or manufacturers, etc
We propose a self-tuned mutation based on the four modified mutation versions consisting of rand./1, rand./2, best/1 and best/2, in which rand./1 and rand./2 are included in the first group, called rand group, and best/1 and best/2 are included in the second group, called best group
In order to satisfy the available water constraint and power balance constraint, the control variables included in solution d are comprised of the power generation of (N − 1) thermal units over all M subintervals and the water discharge from all hydropower plants over the first (M − 1) subintervals
Summary
An electrical power system is mainly composed of thermal and hydro power plants connected via transmission lines in order to supply electricity to loads such as industrial zones or manufacturers, etc. CDE has been considered a simple meta-heuristic algorithm with two main advantages when compared to GA, and has been applied to optimization problems such as fast convergence and few control parameters [39]. CDE; these methods have to cope with fundamental limitations such as spending a great deal of time tuning the crossover factor and several factors in the adaptive mutation operation, missing promising solutions of good quality, and keeping identical solutions in the current population. In order to test the performance of the proposed ENMDE, we implement the ENMDE and two other versions of DE, including DE with self-tuned mutation (STMDE) and DE with the leading group selection (LGSDE) to solve two different fixed-head, short-term hydrothermal scheduling problems with six study cases.
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