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Applications of optimal building energy system selection and operation

机译:最佳建筑能源系统选择与运行的应用

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Berkeley Lab has been developing the Distributed Energy Resources Customer Adoption Model for several years. Given load curves for energy services requirements in a building microgrid (μ·grid), fuel costs and other economic inputs, and a menu of available technologies, the model finds the optimum equipment fleet and operating schedule. This capability is being applied using a Software as a Service (SaaS) model. The evolution of this approach is demonstrated by description of four past and present projects: (1) a public access web site focused on solar photovoltaic generation and battery viability for large non-residential customers; (2) a building CO_2 emissions reduction operations problem for a university dining hall with potential investments considered; (3) a battery and rolling operating schedule problem for a large county jail; and (4) the direct control of the solar-assisted heating ventilation and air conditioning system of a university building by providing optimised daily schedules that are automatically implemented in the building's energy management and control system. Together these examples show that optimisation of building μ·grid design and operation can be effectively achieved using SaaS.
机译:伯克利实验室多年来一直在开发分布式能源客户采用模型。给定建筑物微电网(μ·grid)的能源服务要求的负荷曲线,燃料成本和其他经济投入,以及可用技术的菜单,该模型可以找到最佳的设备数量和运行时间表。正在使用软件即服务(SaaS)模型来应用此功能。通过描述四个过去和现在的项目,证明了这种方法的发展:(1)一个公共访问网站,主要面向大型非住宅客户的太阳能光伏发电和电池生存能力; (2)考虑到潜在投资的大学食堂的建筑物二氧化碳减排操作问题; (3)大型县监狱的电池和滚动运行时间表问题; (4)通过提供优化的日程安排来直接控制大学建筑物的太阳能辅助采暖通风和空调系统,这些日程安排将自动在建筑物的能源管理和控制系统中实施。这些示例共同表明,使用SaaS可以有效地实现建筑物μ·grid设计和操作的优化。

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