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Multi-objective optimal design of hybrid renewable energy systems using evolutionary algorithms

机译:基于进化算法的混合可再生能源系统多目标优化设计

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On the design of a hybrid renewable energy system multiple objectives are in general required to be optimized simultaneously. This study presents a general multi-objective combinatorial model for optimizing the hybrid PV-wind-diesel-battery system configuration. The model considers four objectives, i.e., minimizing the lifetime system cost, lifetime CO and SO emissions and maximizing the system output power. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) approach is employed to obtain a set of Pareto optimal solutions to the problem. Each solution corresponds to a non-inferior design, i.e., a good combination of PV, wind, diesel and battery. By further considering the practical situation, a satisfied design could be selected.
机译:在设计混合可再生能源系统时,通常需要同时优化多个目标。这项研究提出了一个通用的多目标组合模型,用于优化混合光伏-风-柴油-电池系统的配置。该模型考虑了四个目标,即最大程度地降低系统的使用寿命成本,CO和SO的终身排放量,并最大程度地提高系统输出功率。采用基于分解的多目标进化算法(MOEA / D)获得了该问题的一组帕累托最优解。每个解决方案都对应一个非劣质的设计,即PV,风能,柴油和电池的良好组合。通过进一步考虑实际情况,可以选择满意的设计。

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