Digital Twin Based Evolutionary Building Facility Control Optimization

Kohei Fukuhara, Ryo Kumagai, Fukawa Yuta*, Tanabe Shin-Ichi, Hiroki Kawano, Yoshihiro Ohta, Hiroyuki Sato

*この研究の対応する著者

研究成果: Conference contribution

抄録

This work addresses a real-world building facility control problem by using evolutionary algorithms. The variables are facility control parameters, such as the start/stop time of air-conditioning, lighting, and ventilation operation, etc. The problem has six objectives: annual energy consumption, elec-tricity cost, overall satisfaction, thermal satisfaction, indoor air quality satisfaction, and lighting satisfaction. The problem has five constraints: power consumption, temperature, humidity, CO_2 concentration, and average illuminance. To solve the problem, we utilize IBEA framework. For efficient solution generation, we employ the steady-state model for IBEA. We propose the total constraint win-loss rank for multiple constraints to treat multiple constraints equally. Experimental results on artificial test problems and building facility control problems show that the proposed constraint IBEA with steady-state and total con-straint win-loss rank archives better search performance than conventional representative algorithms.

本文言語English
ホスト出版物のタイトル2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781665467087
DOI
出版ステータスPublished - 2022
イベント2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Padua, Italy
継続期間: 2022 7月 182022 7月 23

出版物シリーズ

名前2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings

Conference

Conference2022 IEEE Congress on Evolutionary Computation, CEC 2022
国/地域Italy
CityPadua
Period22/7/1822/7/23

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ サイエンスの応用
  • 計算数学
  • 制御と最適化

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