Welcome to the InfoSci Platform
Using Fuzzy Control Methods for Increasing the Energy Efficiency of Buildings

Using Fuzzy Control Methods for Increasing the Energy Efficiency of Buildings

Vassiliki Mpelogianni, Peter Groumpos
Copyright: © 2017 |Pages: 22
ISBN13: 9781522516712|ISBN10: 1522516719|EISBN13: 9781522516729
DOI: 10.4018/978-1-5225-1671-2.ch042
Cite Chapter Cite Chapter

MLA

Mpelogianni, Vassiliki, and Peter Groumpos. "Using Fuzzy Control Methods for Increasing the Energy Efficiency of Buildings." Renewable and Alternative Energy: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 1256-1277. https://doi.org/10.4018/978-1-5225-1671-2.ch042

APA

Mpelogianni, V. & Groumpos, P. (2017). Using Fuzzy Control Methods for Increasing the Energy Efficiency of Buildings. In I. Management Association (Ed.), Renewable and Alternative Energy: Concepts, Methodologies, Tools, and Applications (pp. 1256-1277). IGI Global. https://doi.org/10.4018/978-1-5225-1671-2.ch042

Chicago

Mpelogianni, Vassiliki, and Peter Groumpos. "Using Fuzzy Control Methods for Increasing the Energy Efficiency of Buildings." In Renewable and Alternative Energy: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1256-1277. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1671-2.ch042

Export Reference

Mendeley
Favorite

Abstract

The energy sector worldwide faces significant challenges that everyday become even more acute. Innovative technologies and energy efficiency measures are nowadays well known and widely spread, and the main issue is to identify the more effective and reliable in the long term. In order to do so the decision maker has to compensate many factors. This article investigates the feasibility of the application of new intelligent control methods in modeling and controlling the performance of a building. For the first time a performance comparison of Fuzzy Logic vs Fuzzy Cognitive Maps (FCMs) theories is performed and interesting results are presented. Multi-level intelligent controllers to manage the various parts of a building's automation and increase its energy efficiency are presented. For the first time the Building Energy Management System has been modeled using FCMs. Simulation studies with real environmental data have been performed and useful results have been obtained and discussed. Challenging future research topics are provided.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.