Abstract
Unit Commitment (UC) requires the optimization of the operation of generation units with varying loads, at every hour, under different technical and environmental constraints. Many solution techniques were developed for the UC problem, and the researchers are still working on improving the efficiency of these techniques. Particle swarm optimization (PSO) is an effective and efficient technique used for solving the UC problems, and it has gotten a considerable amount of attention in recent years. This study provides a state-of-the-art literature review on UC studies utilizing PSO or PSO-variant algorithms, by focusing on research articles published in the last decade. In this study, these algorithms/methods, objectives, constraints are reviewed, with focus on the UC problems that include at least one of the wind and solar technologies, along with thermal unit(s). Although, conventional PSO is one of the most effective techniques used in solving UC problem, other methods were also developed in literature to improve the convergence. In this study, these methods are grouped as extended PSO, modified PSO, and PSO with other techniques. This study shows that PSO with other techniques are utilized more than any other methods. In terms of constraints, it was observed that there are only few studies that considered Transmission Line (TL), Fuel (F), Emission (E), Storage (St) and Crew (Cr) constraints, while Power Balance (PB), Generation limit (GL), Unit minimum Up or Down Time (U/DT), Ramp Up or Ramp Down Time (R-U/DT) and system Spinning Reserve (SR) were the most utilized constraints in UC problems considering wind/solar as a renewable source. In addition, most of the studies are based on a single objective function (cost minimization) and, few of them are multi-objective (cost and emission minimization) based studies.
Highlights
To reduce the impact of climate change, it is vital to mitigate emissions caused by several industries.This can be achieved by utilizing renewable energy (RE)
This paper presents a state of the art review on Unit Commitment (UC) studies based on Particle swarm optimization (PSO) algorithms, by covering the research articles published in the last decade
A critical review that highlights PSO methods utilized in solving the UC problem was presented
Summary
To reduce the impact of climate change, it is vital to mitigate emissions caused by several industries This can be achieved by utilizing renewable energy (RE). [17,18], revealed that PSO is robust in solving non-differentiable, nonlinear, high dimensional and multiple-optima problems through a simple procedure with high convergence speed These advantages of PSO made it one of the most effective and efficient techniques for solving UC problems. Considering the described research trend, this study aims at reviewing the UC studies that utilized PSO as a solution method. In this context, studies that integrate thermal units with well-known Renewable Energy Sources (RES) (wind and solar) are presented.
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