2013Unpublished venueRequires access

Building Energy Use Prediction Using Time Series Analysis

Ruijin Zhou, Yiqun Pan, Zhizhong Huang, Qiujian Wang

Open publisher page 18 citations

Abstract

This paper proposes a data-driven modeling method for building energy consumption prediction and applies it to two actual commercial buildings. Time series analysis is adopted as a main methodology to produce the data-driven model based on monthly actual energy consumption data. The models can be used to predict building future energy consumption, after being modified and verified.

About this research paper

What this paper is about

This paper proposes a data-driven modeling method for building energy consumption prediction and applies it to two actual commercial buildings. Time series analysis is adopted as a main methodology to produce the data-driven model based on monthly actual energy consumption data. The models can be used to predict building future energy consumption, after being modified and verified.

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OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper proposes a data-driven modeling method for building energy consumption prediction and applies it to two actual commercial buildings. Time series analysis is adopted as a main methodology to produce the data-driven model based on monthly actual energy consumption data. The models can be used to predict building future energy consumption, after being modified and verified.

Key concepts: Energy consumption, Computer science, Time series, Series (stratigraphy), Energy (signal processing), Data modeling, Consumption (sociology), Building management system

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