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Micro-sources design of an intelligent building integrated with micro-grid^

机译:集成了微电网的智能建筑的微源设计^

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Intelligent buildings are the trend of future buildings, as well as, micro-grids are important scenarios of smart grid under going. An intelligent building integrated with micro-grid can fit the much comfort and low energy consumption targets better. However, the output power of micro-sources in the micro-grid for intelligent building application is stochastic, uncertain and uncontrollable. Thus, micro-sources design of an intelligent building integrated with micro-grid is a significant issue. Therefore, a mathematical model is proposed to optimize the capacities of micro-resources, which can harvest green energy from renewable energy resources (RERs) as much as possible. In the presented model, energy cost coefficient (ECC) is set as the minimization objective function, F, which is defined as the ratio between energy cost of intelligent building and the output energy of RESs. It is should be noted that ECC is different from conventional optimum objective to minimize the cost of whole project, C As a result, a multi-objective model associated with F and C is also discussed to satisfy different requirements and targets of numerous users. A numerical example is utilized to validate the feasibility of the proposed approach. Simultaneously, the Pareto fronts of the multi-objective model are obtained using Linear INteractive and General Optimizer (LINGO).
机译:智能建筑是未来建筑的趋势,微电网是正在发展的智能电网的重要场景。集成了微电网的智能建筑可以更好地适应舒适度和低能耗目标。然而,用于智能建筑应用的微电网中的微源的输出功率是随机的,不确定的且不可控制的。因此,与微电网集成的智能建筑的微源设计是一个重要的问题。因此,提出了一个数学模型来优化微资源的容量,微资源可以尽可能多地从可再生能源(RER)中获取绿色能源。在提出的模型中,将能源成本系数(ECC)设置为最小目标函数F,F定义为智能建筑的能源成本与RES的输出能量之比。应该注意的是,ECC与常规最佳目标不同,是为了最大程度地降低整个项目C的成本。结果,还讨论了与F和C相关的多目标模型,以满足众多用户的不同要求和目标。数值例子验证了所提方法的可行性。同时,使用线性交互式和通用优化器(LINGO)获得多目标模型的Pareto前沿。

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