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Prediction of energy consumption in buildings by system identification

机译：系统识别预测建筑物的能耗

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摘要

This paper presents modeling methodologies for predicting energy consumption using system identification. The models discussed will predict the systems performance using the measured input and output. To test and train the models, data was gathered from an existing building. State space, nonlinear, and polynomials models based mathematical functions and tested with different parameters such are temperature, time, and dew point. The results show that the proposed models can output similar energy results. The developed model can be used for energy assessment and diagnosis.

机译：本文介绍了使用系统识别预测能量消耗的建模方法。讨论的模型将使用测量的输入和输出预测系统性能。要测试和培训模型，数据从现有建筑收集。基于状态空间，非线性和多项式模型的数学函数，并用不同的参数测试，例如温度，时间和露点。结果表明，所提出的模型可以输出类似的能量结果。开发的模型可用于能量评估和诊断。

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来源
《Future Technologies Conference》|2016年|749p|共5页
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作者
Darrion Long; Nabil Nassif; Andrew Scott Ours;
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原文格式 PDF
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中图分类 TP3-53;
关键词
Mathematical model; Data models; Energy consumption; Buildings; Atmospheric modeling; Analytical models; Predictive models;

机译：数学模型;数据模型;能量消耗;建筑物;大气建模;分析模型;预测模型;

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Prediction of energy consumption in buildings by system identification

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