Published November 2012 | Version v1
Journal article

Multi-agent control system with information fusion based comfort model for smart buildings

  • 1. Department of Electrical Engineering and Computer Science, University of Toledo, 2801 Bancroft Rd., Toledo, OH 43606 (United States)
  • 2. Department of Automation, Technological Educational Institute of Piraeus, 250 P. Ralli and Thivon Str., Egaleo 12244 (Greece)

Description

Highlights: ► Proposed a model to manage indoor energy and comfort for smart buildings. ► Developed a control system to maximize comfort with minimum energy consumption. ► Information fusion with ordered weighted averaging aggregation is used. ► Multi-agent technology and heuristic intelligent optimization are deployed in developing the control system. -- Abstract: From the perspective of system control, a smart and green building is a large-scale dynamic system with high complexity and a huge amount of information. Proper combination of the available information and effective control of the overall building system turns out to be a big challenge. In this study, we proposed a building indoor energy and comfort management model based on information fusion using ordered weighted averaging (OWA) aggregation. A multi-agent control system with heuristic intelligent optimization is developed to achieve a high level of comfort with the minimum power consumption. Case studies and simulation results are presented and discussed in this paper.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.apenergy.2012.05.020

Additional details

Identifiers

DOI
10.1016/j.apenergy.2012.05.020;
PII
S0306-2619(12)00368-6;

Publishing Information

Journal Title
Applied Energy
Journal Volume
99
Journal Page Range
p. 247-254
ISSN
0306-2619
CODEN
APENDX

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
45019837
Subject category
S42: ENGINEERING;
Descriptors DEI
AGGLOMERATION; BUILDINGS; CIVIL ENGINEERING; COMPUTERIZED SIMULATION; CONTROL SYSTEMS; ENERGY CONSUMPTION; ENVIRONMENTAL ENGINEERING; OPTIMIZATION
Descriptors DEC
ENGINEERING; SIMULATION

Optional Information

Copyright
Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.