An energy consumption prediction of large public buildings based on data-driven model

被引:1
|
作者
Guan, Yongbing [1 ]
Fang, Yebo [2 ]
机构
[1] Jinan Engn Polytech, Engn Management Coll, Jinan, Shandong, Peoples R China
[2] Shandong Urban Construct Vocat Coll, Dept Municipal Engn & Equipment, Jinan, Shandong, Peoples R China
关键词
data-driven model; large public buildings; energy consumption prediction; BP neural network; genetic algorithm;
D O I
10.1504/IJGEI.2023.130682
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Because the traditional energy consumption prediction method of large public buildings has the problems of large prediction error and long prediction time, an energy consumption prediction of large public buildings based on data-driven model is proposed. The process includes to build the energy consumption model of large public buildings through data driving, collect energy consumption data such as equipment capacity, load grade and equipment failure rate, pre-process the energy consumption data, take the pre-processed energy consumption data as training samples, input it into BP neural network for training, optimise BP neural network by genetic algorithm and build the energy consumption prediction model of large public buildings, and get the prediction results. The simulation results show that the energy consumption prediction method of large public buildings based on data-driven model has short time and good prediction effect.
引用
收藏
页码:207 / 219
页数:14
相关论文
共 50 条
  • [1] Data-Driven Based Prediction of the Energy Consumption of Residential Buildings in Oshawa
    Lin, Yaolin
    Liu, Jingye
    Gabriel, Kamiel
    Yang, Wei
    Li, Chun-Qing
    [J]. BUILDINGS, 2022, 12 (11)
  • [2] A data-driven model for the analysis of energy consumption in buildings
    Borgato, Nicola
    Prataviera, Enrico
    Bordignon, Sara
    Garay-Martinez, Roberto
    Zarrella, Angelo
    [J]. 53RD AICARR INTERNATIONAL CONFERENCE FROM NZEB TO ZEB: THE BUILDINGS OF THE NEXT DECADES FOR A HEALTHY AND SUSTAINABLE FUTURE, 2024, 523
  • [3] Developing a Data-Driven Framework for Lighting Energy Consumption Prediction in US Office Buildings
    Norouziasl, Seddigheh
    Jafari, Amirhosein
    [J]. COMPUTING IN CIVIL ENGINEERING 2021, 2022, : 287 - 294
  • [4] Electric energy consumption predictions for residential buildings: Impact of data-driven model and temporal resolution on prediction accuracy
    Kim, Jiwon
    Kwak, Younghoon
    Mun, Sun-Hye
    Huh, Jung-Ho
    [J]. JOURNAL OF BUILDING ENGINEERING, 2022, 62
  • [5] A Semantically Data-Driven Classification Framework for Energy Consumption in Buildings
    Popa, Angela
    Gonzalez, Alfonso P. Ramallo
    Jaglan, Gaurav
    Fensel, Anna
    [J]. ENERGIES, 2022, 15 (09)
  • [6] Data-Driven Building Energy Consumption Prediction Model Based on VMD-SA-DBN
    Qin, Yongrui
    Zhao, Meng
    Lin, Qingcheng
    Li, Xuefeng
    Ji, Jing
    [J]. MATHEMATICS, 2022, 10 (17)
  • [7] Data driven modeling for energy consumption prediction in smart buildings
    Gonzalez-Vidal, Aurora
    Ramallo-Gonzalez, Alfonso P.
    Terroso-Saenz, Fernando
    Skarmeta, Antonio
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2017, : 4562 - 4569
  • [8] Explicit data-driven prediction model of annual energy consumed by elevators in residential buildings
    Zubair, Muhammad Umer
    Zhang, Xueqing
    [J]. JOURNAL OF BUILDING ENGINEERING, 2020, 31
  • [9] Energy Consumption Prediction Model of Public Buildings Based on PSO-RBF
    Cao, Ling
    Huang, Nian-yan
    [J]. INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE (AICS 2016), 2016, : 119 - 124
  • [10] Modelling of Destinations for Data-driven Pedestrian Trajectory Prediction in Public Buildings
    Lui, Andrew Kwok-Fai
    Chan, Yin-Hei
    Leung, Man-Fai
    [J]. 2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2021, : 1709 - 1717