A Memetic Evolutionary Multi-Objective Optimization Method for Environmental Power Unit Commitment
作者： Yan-Fu Li , Nicola Pedroni , Enrico Zio
DOI: 10.1109/TPWRS.2013.2241795
关键词:
摘要: A multi-objective power unit commitment problem is framed to consider simultaneously the objectives of minimizing operation cost and emissions from generation units. To find solution optimal schedule units, a memetic evolutionary algorithm proposed, which combines non-dominated sorting genetic algorithm-II (NSGA-II) local search algorithm. The dispatch sub-problem solved by weighed-sum lambda-iteration approach. proposed method has been tested on systems composed 10 100 units for 24-hour demand horizon. Pareto-optimal front obtained contains solutions different trade off with respect two emission, are superior those contained in Pareto-front pure NSGA-II. minimum shown compare well recent published results single-objective optimization algorithms.
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