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Satisfying the Energy Demand of a Rural Area by Considering the Investment on Renewable Energy Alternatives and Depreciation Costs

机译:通过考虑对可再生能源替代品和折旧成本的投资来满足农村地区的能源需求

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摘要

In this paper, a fuzzy multiobjective model which chooses the best mix of renewable energy options and determines the optimal amount of energy to be transferred from each resource to each end use is proposed. The depreciation of equipment along with time value of money has been taken into account in the first objective function while the second and the third objective functions minimize the greenhouse gas emissions and water consumption, respectively. Also, this study is one of the pioneer works that has considered demand-side management (DSM) as a competitive option against supply-side alternatives for making apt energy planning decisions. Moreover, the intrinsic uncertainty of demand parameter is considered and modeled by fuzzy numbers. To convert the proposed fuzzy multiobjective formulation to a crisp single-objective formulation the well-known fuzzy goal programming approach together with Jimenez defuzzifying technique is employed. The model is validated through setting up a diversity of datasets whose data were mostly derived from the literature. The obtained results show that DSM programs have greatly contributed to cost reductions in the network. Also, it is concluded that the model is capable of solving even large-scaled instances of problems in negligible central processing unit (CPU) times using Lingo 8.0 software.
机译:在本文中,提出了一种模糊多目标模型,其选择可再生能源选项的最佳组合,并确定了从每个资源转移到每个最终用途的最佳能量。在第一个目标函数中,已经考虑了设备的折旧以及金钱时间价值,而第二个目标职能分别最大限度地减少了温室气体排放量和耗水量。此外,本研究是先驱工作之一,考虑了需求侧管理(DSM)作为对供应侧替代品的竞争选项,用于制作APT能源规划决策。此外,通过模糊数字考虑和建模需求参数的内在不确定性。为了将建议的模糊多目标配方转换为清晰的单目标制定,采用了众所周知的模糊目标编程方法与Jimenez Defuzzizing技术一起使用。通过建立数据集的多样性,该模型验证,其数据主要来自文献。所获得的结果表明,DSM程序极大地促进了网络的成本削减。此外,结论是,该模型能够使用Lingo 8.0软件解决甚至可以在可忽略的中央处理单元(CPU)次中解决甚至是大规模的问题。

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