A Memetic Evolutionary Multi-Objective Optimization Method for Environmental Power Unit Commitment

A multi-objective power unit commitment problem is framed to consider simultaneously the objectives of minimizing the operation cost and minimizing the emissions from the generation units. To find the solution of the optimal schedule of the generation units, a memetic evolutionary algorithm is propo...

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Bibliographic Details
Published inIEEE transactions on power systems Vol. 28; no. 3; pp. 2660 - 2669
Main Authors Yan-Fu Li, Pedroni, Nicola, Zio, Enrico
Format Journal Article
LanguageEnglish
Published IEEE 01.08.2013
Subjects
Biological cells
Environmental/economic dispatch
evolutionary algorithm
lambda-iteration approach
Linear programming
local search
memetic algorithm
multi-objective optimization
non-dominated sorting genetic algorithm
Optimization
power unit commitment
Search problems
Sociology
Statistics
Vectors
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Summary:A multi-objective power unit commitment problem is framed to consider simultaneously the objectives of minimizing the operation cost and minimizing the emissions from the generation units. To find the solution of the optimal schedule of the generation units, a memetic evolutionary algorithm is proposed, which combines the non-dominated sorting genetic algorithm-II (NSGA-II) and a local search algorithm. The power dispatch sub-problem is solved by the weighed-sum lambda-iteration approach. The proposed method has been tested on systems composed by 10 and 100 generation units for a 24-hour demand horizon. The Pareto-optimal front obtained contains solutions of different trade off with respect to the two objectives of cost and emission, which are superior to those contained in the Pareto-front obtained by the pure NSGA-II. The solutions of minimum cost are shown to compare well with recent published results obtained by single-objective cost optimization algorithms.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2013.2241795