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Optimization based planning of urban energy systems: Retrofitting a Chinese industrial park as a case-study

机译:基于优化的城市能源系统规划:以中国工业园区改造为案例研究

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摘要

Optimization modeling is popular for evaluating the design of energy systems in a given urban area. This is largely because the design of urban energy systems requires to make complex decisions about the choice of technologies, their location, and the fuels they use. This study presents an approach for modeling and optimizing decisions for retrofitting urban energy systems, with a focus on the optimal configuration and operation of supply side and demand side technologies required to satisfy the energy requirements. A mixed integer nonlinear programming model is formulated in GAMS and solved using Lindo optimizer. A case study in urban China is presented to verify the model and to identify opportunities for systems integration. Three scenarios are analyzed and the results show that a potential reduction in space heating and CO2 emissions of up to 57.7% and 50% are possible by retrofitting building envelopes with photovoltaics, ground source heat pump and natural gas cogeneration systems. Sensitivity analysis and multi-objective optimization further indicate that CO2 emission plays the most important role in decision-making. This approach enables to identify design trade-offs of complex urban energy systems so as to evaluate the potential of alternative technology mix. (C) 2017 Elsevier Ltd. All rights reserved.
机译:优化模型在评估给定市区的能源系统设计方面很受欢迎。这主要是因为城市能源系统的设计需要对技术的选择,其位置和使用的燃料做出复杂的决定。这项研究提出了一种用于建模和优化改造城市能源系统的决策的方法,重点是满足能源需求所需的供方和需求方技术的最佳配置和操作。在GAMS中制定了混合整数非线性规划模型,并使用Lindo优化器对其进行了求解。本文以中国城市为例,验证了该模型并确定了系统集成的机会。分析了三种情况,结果表明,通过使用光伏电池,地源热泵和天然气热电联产系统改造建筑围护结构,可以将空间供暖和CO2排放量分别降低57.7%和50%。敏感性分析和多目标优化进一步表明,CO2排放在决策中起着最重要的作用。这种方法可以确定复杂的城市能源系统的设计折衷,从而评估替代技术组合的潜力。 (C)2017 Elsevier Ltd.保留所有权利。

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