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Hierarchical Model Predictive Control for Building Energy Management of Hybrid Systems

机译:混合系统建筑能量管理的层次模型预测控制

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In this paper a two-layer controller is proposed to tackle the building energy management problem for hybrid systems at different levels of abstraction and different time scales. In the upper layer a relaxed long term energy allocation problem with a large decision time step is defined, taking into account the energy prices, the comfort requirements, and a global power constraint. The discrete decision variables are considered only in the lower layer, where the continuous global solution computed by the first optimization is projected into local mixed-integer programming (MIP) tracking problems with a shorter prediction horizon and a higher sampling rate. To fulfill the building global power constraint each load has a specific priority to access the available power, following a non-iterative priority algorithm.
机译:本文提出了一种两层控制器来解决混合系统在不同抽象级别和不同时间尺度下的建筑能源管理问题。在上层,考虑到能源价格,舒适性要求和全局功率约束,定义了一个宽松的长期能源分配问题,该问题具有较大的决策时间步长。离散决策变量仅在较低层中考虑,在较低层中,将由第一次优化计算的连续全局解投影到具有较短预测范围和较高采样率的局部混合整数规划(MIP)跟踪问题中。为了满足建筑物的总体功率约束,每个负载都有一个特定的优先级,可以使用非迭代优先级算法来访问可用功率。

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