A building automation and control tool for remote and real time monitoring of energy consumption

Abstract Nowadays, buildings are responsible for about 40% of the EU's total final energy consumption and greenhouses emissions, putting them among the largest end-use sectors globally. In this context, a number of studies exist in the international literature analyzing the importance of effective energy and environmental management of the buildings. With respect to the above, the main aim of the paper is to present a building automation and control tool for remote and real time monitoring of energy consumption in the building sector. Apart from analyzing the building's energy profile, the tool integrates control scenarios that minimizes the energy consumption and rationalizes the energy use in the highest degree. The proposed tool achieves significant decrease in the operating cost of active system in a tertiary sector building, while maintaining desirable comfort.

[1]  Denia Kolokotsa,et al.  Interconnecting smart card system with PLC controller in a local operating network to form a distributed energy management and control system for buildings , 2002 .

[2]  Lingfeng Wang,et al.  Multi-objective optimization for decision-making of energy and comfort management in building automation and control , 2012 .

[3]  Agis M. Papadopoulos,et al.  Application of multicriteria analysis in designing HVAC systems , 2009 .

[4]  Alexandra G. Papadopoulou,et al.  Decision support for assessing demand side management programmes , 2011 .

[5]  Theocharis Tsoutsos,et al.  Assessing renewables-to-electricity systems: a fuzzy expert system model , 2006 .

[6]  Karsten Menzel,et al.  Multi-dimensional building performance data management for continuous commissioning , 2010, Adv. Eng. Informatics.

[7]  P. A. Mehta,et al.  Artificial intelligence and networking in integrated building management systems , 1997 .

[8]  Agis M. Papadopoulos,et al.  A typological classification of the Greek residential building stock , 2011 .

[9]  M. Zaheer-Uddin,et al.  Optimal, sub-optimal and adaptive control methods for the design of temperature controllers for intelligent buildings , 1993 .

[10]  K. F. Fong,et al.  HVAC system optimization for energy management by evolutionary programming , 2006 .

[11]  Shengwei Wang,et al.  Online adaptive control for optimizing variable-speed pumps of indirect water-cooled chilling systems , 2001 .

[12]  H.S. Matthews,et al.  Scoping the potential of monitoring and control technologies to reduce energy use in homes , 2007, Proceedings of the 2007 IEEE International Symposium on Electronics and the Environment.

[13]  Jane P. Laudon,et al.  Management Information Systems: Organization and Technology in the Networked Enterprise , 1999 .

[14]  Ibrahim Dincer,et al.  Development of sustainable energy options for buildings in a sustainable society , 2011 .

[15]  Kostas Kalaitzakis,et al.  Genetic algorithms optimized fuzzy controller for the indoor environmental management in buildings implemented using PLC and local operating networks , 2002 .

[16]  A. Kanarachos,et al.  Multivariable control of single zone hydronic heating systems with neural networks , 1998 .

[17]  Shengwei Wang,et al.  Intelligent building research: a review , 2005 .

[18]  John Psarras,et al.  Sustainable energy technologies in Israel under the CDM: Needs and prospects , 2009 .

[19]  Paul Raftery,et al.  Key factors methodology—A novel support to the decision making process of the building energy manager in defining optimal operation strategies , 2012 .

[20]  Agis M. Papadopoulos,et al.  Impact of energy pricing on buildings' energy design , 2006 .

[21]  John Psarras,et al.  Intelligent building energy management system using rule sets , 2007 .

[22]  M. Zaheer-Uddin.  Intelligent control strategies for HVAC processes in buildings , 1994 .

[23]  Xiangjiang Zhou,et al.  Optimal operation of a large cooling system based on an empirical model , 2004 .

[24]  Ronald G. Ross.  Data base systems: Design, implementation, and management , 1978 .

[25]  H. N. Lam,et al.  Using genetic algorithms to optimize controller parameters for HVAC systems , 1997 .

[26]  John Psarras,et al.  Assessing energy-saving measures in buildings through an intelligent decision support model , 2009 .

[27]  Rahul V. Ralegaonkar,et al.  Improving environmental performance of building through increased energy efficiency: A review , 2011 .