首页> 外文会议>2018 IEEE Data Science Workshop >OPTIMIZING THERMAL COMFORT AND ENERGY CONSUMPTION IN A LARGE BUILDING WITHOUT RENOVATION WORK
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OPTIMIZING THERMAL COMFORT AND ENERGY CONSUMPTION IN A LARGE BUILDING WITHOUT RENOVATION WORK

机译:无需翻新即可优化大型建筑中的热舒适和能源消耗

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This paper proposes a new methodology to reduce energy consumptions in large buildings while simultaneously optimizing thermal comfort. The model designed with an energy simulation program is calibrated by the Covariance Matrix Adaptation Evolutionary Strategy using observations including consumptions, inside temperatures and comfort measurements such as COn2nemissions obtained with sensors displayed in the building. The temperatures inside the building and the energy consumptions predicted by the calibrated model during a new time period are then compared to the corresponding observations. The model is then used to find a set of Pareto optimal schedulings and tunings of the building management system in terms of energy loads and thermal comfort using multi-objective optimization.
机译:本文提出了一种减少大型建筑物能耗同时优化热舒适性的新方法。通过协方差矩阵适应进化策略,使用包括能耗,内部温度和舒适度测量在内的观测值(例如,COn 2 使用建筑物中显示的传感器获得的排放量。然后,将建筑物内的温度和经过校准的模型在新的时间段内预测的能耗与相应的观察结果进行比较。然后,使用多目标优化,使用该模型在能源负荷和热舒适性方面找到一组Pareto最优调度和建筑物管理系统的调整。

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