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A Decision-Guided Energy Framework for Optimal Power, Heating, and Cooling Capacity Investment

机译:决策能源框架,用于最佳功率,加热和冷却能力投资

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We propose a Decision-Guided Energy Investment (DGEI) Framework to optimize power, heating, and cooling capacity. The DGEI framework is designed to support energy managers to (1) use the analytical and graphical methodology to determine the best investment option that satisfies the designed evaluation parameters, such as return on investment (ROI) and greenhouse gas (GHG) emissions; (2) develop a DGEI optimization model to solve energy investment problems that the operating expenses are minimal in each considered investment option; (3) implement the DGEI optimization model using the IBM Optimization Programming Language (OPL) with historical and projected energy demand data, i.e., electricity, heating, and cooling, to solve energy investment optimization problems; and (4) conduct an experimental case study for a university campus microgrid and utilize the DGEI optimization model and its OPL implementations, as well as the analytical and graphical methodology to make an investment decision and to measure tradeoffs among cost savings, investment costs, maintenance expenditures, replacement charges, operating expenses, GHG emissions, and ROI for all the considered options.
机译:我们提出了一个决策能源投资(DGEI)框架,优化电力,加热和冷却能力。 DGEI框架旨在支持能源管理人员(1)使用分析和图形方法来确定满足设计评估参数的最佳投资选项,例如投资回报(ROI)和温室气体(GHG)排放; (2)制定DGEI优化模型,解决能源投资问题,即每次考虑投资选项中的运营费用最小; (3)利用IBM优化编程语言(OPL)实施DGEI优化模型,具有历史和投影能源需求数据,即电力,加热和冷却,解决能源投资优化问题; (4)对大学校园微电网进行实验案例研究,利用DGEI优化模型及其OPL实现,以及分析和图形方法,以进行投资决策,并衡量成本节约,投资成本,维护之间的权衡所有被考虑的选项的支出,替换费,营业费用,温室气体排放和投资回报率。

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