Robust prediction and MPC-based optimal energy management for HVAC System

Takatoshi Suda, Toru Namerikawa

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The purpose of this paper is to achieve a cut in peak electricity demand and lower electricity costs through the optimal management of a heating ventilation and air conditioning (HVAC) system. In addition, robust solar radiation prediction is required for optimal HVAC management. First, solar radiation prediction is applied using a clustering technique based on the k-means method, classifying all data on similar types of solar radiation. Second, an H filter, which is a robust prediction method for outliers, is applied. Next, an optimal HVAC management system is considered for operating the air conditioning, such as the cooling and heating of each room. Model predictive control (MPC), which is used to predict and control the future changes in the temperature of the room and the electrical charge from solar radiation, is applied. Finally, we confirmed the validity of this research through numerical simulations.

Original languageEnglish
Pages (from-to)472-477
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number25
DOIs
Publication statusPublished - 2018 Jan 1

Fingerprint

Model predictive control
Energy management
Solar radiation
Air conditioning
Ventilation
Heating
Electricity
Cooling
Computer simulation
Costs
Temperature

Keywords

  • BEMS
  • H filter
  • HVAC
  • MPC
  • Solar radiation prediction

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Robust prediction and MPC-based optimal energy management for HVAC System. / Suda, Takatoshi; Namerikawa, Toru.

In: IFAC-PapersOnLine, Vol. 51, No. 25, 01.01.2018, p. 472-477.

Research output: Contribution to journalArticle

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