热网格系统数学规划与机器学习技术的混合方法

Yuya Morinaga, K. Sakakibara, Takuya Matsumoto, M. Ohara, Ittetsu Taniguchi, H. Tamaki
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引用次数: 0

摘要

我们专注于热网格系统,其目的是控制多个空调系统作为一个单元,以实现高能效建筑。为了实现对空调的实时控制,我们提出了一种混合系统,该系统采用人工神经网络,并利用数学规划技术对其进行训练,以确定空调机器在多时段的输出。通过热网格系统实际设置的数值实验,验证了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Approach Mixing Mathematical Programming and Machine Learning Techniques for Thermal Grid Systems
We focus on thermal grid systems which aim to control a number of air conditioning systems as a unit for achieving highly energy-efficient buildings. In order to realize real-time control of them, we propose hybrid systems in which artificial neural networks are involved and it is trained by using mathematical programming techniques determining the outputs of the air conditioning machines in multi-periods. Through some numerical experiments with the actual settings of the thermal grid systems, the potential of our proposed method is examined.
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