NDLI: Computational intelligence techniques for HVAC systems: A review

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Computational intelligence techniques for HVAC systems: A review

Content Provider	Springer Nature Link
Author	Ahmad, Muhammad Waseem Mourshed, Monjur Yuce, Baris Rezgui, Yacine
Copyright Year	2016
Abstract	Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air-conditioning (HVAC) systems are the major source of energy consumption in buildings and ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems. The analysis of trends reveals that the minimisation of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences. Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE-2, HVACSim+ and ESP-r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on multi-agent systems (MAS), as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions.
Starting Page	359
Ending Page	398
Page Count	40
File Format	PDF
ISSN	19963599
Journal	Building Simulation
Volume Number	9
Issue Number	4
e-ISSN	19968744
Language	English
Publisher	Tsinghua University Press
Publisher Date	2016-03-31
Publisher Place	Beijing
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	heating ventilation and airconditioning (HVAC) optimization computational intelligence energy conservation energy efficiency buildings Building Construction Engineering Thermodynamics, Heat and Mass Transfer Atmospheric Protection/Air Quality Control/Air Pollution Environmental Monitoring/Analysis
Content Type	Text
Resource Type	Article
Subject	Building and Construction Energy

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