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METHODS AND SYSTEMS FOR HVAC INEFFICIENCY PREDICTION

机译:暖通空调效率低估的方法和系统

摘要

Systems and methods are provided for predicting inefficient HVAC operation, by obtaining first training data for HVACs in a training set of households during a first period of moderate weather; obtaining second training data for HVACs in the training set of households during a subsequent period of harsher weather; generating classification labels of the household locations of the training set according to the second training data; applying the first training data and the classification labels to train a supervised machine learning algorithm, to generate an HVAC classification model predictive of inefficiency during periods of harsher weather conditions; obtaining operational data pertaining to HVACs in an operational set of households during a second period of moderate weather; and applying the HVAC classification model to predict inefficiency of HVACs at individual households in the operational set during a second subsequent period of harsher weather.
机译:提供了一种系统和方法,用于通过在中等天气的第一时间段中获得训练家庭的HVAC的第一训练数据来预测HVAC运行效率低下;在随后的恶劣天气中,获取第二套培训数据,供家庭中的HVAC使用;根据第二训练数据生成训练集的住户位置的分类标签;应用第一训练数据和分类标签来训练有监督的机器学习算法,以生成HVAC分类模型,以预测恶劣天气条件下效率低下;在第二个适度天气期间,获取与某个运营家庭中的暖通空调有关的运营数据;并应用HVAC分类模型来预测在随后的第二个恶劣天气期间操作集中各个家庭的HVAC效率低下。

著录项

  • 公开/公告号US2020132327A1

    专利类型

  • 公开/公告日2020-04-30

    原文格式PDF

  • 申请/专利权人 GRID4C;

    申请/专利号US201816619604

  • 申请日2018-06-05

  • 分类号F24F11/52;G06Q50/06;F24F11/49;

  • 国家 US

  • 入库时间 2022-08-21 11:21:53

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