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Multi-criteria decision support system of the photovoltaic and solar thermal energy systems using the multi-objective optimization algorithm

机译:使用多目标优化算法的光伏和太阳能热能系统多标准决策支持系统

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When the photovoltaic (PV) and solar thermal energy (STE) systems, which share the rooftop area, are installed in the same building, a trade-off problem occurs in terms of the energy, economic, and environmental aspects, and thus, steps need to solve this problem. Therefore, this study aimed to develop a multi-criteria decision support system of the PV and STE systems using the multi-objective optimization algorithm. This system was developed in the following six steps: (i) database establishment; (ii) designing the variables of the PV and STE systems; (iii) development of the analysis engine of the PV and STE systems; (iv) environmental and economic assessment from the life cycle perspective; (v) integrated multi-objective optimization (iMOO) with a genetic algorithm; and (vi) establishment of a multi-criteria decision support system. To verify the robustness and reliability of the developed model, an analysis of "D" City Hall and "I" Airport as target facilities was performed. The optimal PV and STE systems that consider the energy, economic, and environmental aspects at the same time were determined with respect to the 1.23 x10(15) and 1.05 x 10(16) installation scenarios, respectively, in terms of effectiveness. The iMOO scores of the existing PV and STE systems installed in "D" City Hall and "I" Airport were 0.358 and 0.346, respectively, whereas those of the optimal solutions were 0.249 and 0.280, showing score improvements. In terms of efficiency, the times required for determining the optimal solutions were 20 and 30min, respectively. The developed model makes the final decision-maker to find the optimal solution in introducing the PV and STE systems in the early design phase at the same time. (c) 2018 Elsevier B.V. All rights reserved.
机译:当共享屋顶区域的光伏(PV)和太阳能热能(STE)系统安装在同一建筑物中时,会在能源,经济和环境方面(因此,在步骤上)出现权衡问题需要解决这个问题。因此,本研究旨在使用多目标优化算法开发PV和STE系统的多准则决策支持系统。该系统是通过以下六个步骤开发的:(i)建立数据库; (ii)设计PV和STE系统的变量; (iii)开发PV和STE系统的分析引擎; (iv)从生命周期的角度进行环境和经济评估; (v)采用遗传算法的集成多目标优化(iMOO); (vi)建立多标准决策支持系统。为了验证所开发模型的鲁棒性和可靠性,对“ D”市政厅和“ I”机场作为目标设施进行了分析。在有效性方面,分别针对1.23 x10(15)和1.05 x 10(16)安装方案确定了同时考虑能源,经济和环境方面的最佳PV和STE系统。安装在“ D”市政厅和“ I”机场的现有PV和STE系统的iM​​OO得分分别为0.358和0.346,而最佳解决方案的iMOO得分为0.249和0.280,显示得分有所提高。在效率方面,确定最佳解决方案所需的时间分别为20分钟和30分钟。开发的模型使最终决策者能够在早期设计阶段同时引入PV和STE系统时找到最佳解决方案。 (c)2018 Elsevier B.V.保留所有权利。

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