Economic analysis of exergy efficiency based control strategy for geothermal district heating system

Abstract In this study, the exergy efficiency based control strategy (ExEBCS) for exergy efficiency maximization in geothermal district heating systems (GDHSs) is economically evaluated. As a real case study, the Afyon GDHS in the city of Afyonkarahisar/Turkey is considered. Its actual thermal data as of average weekly data are collected in heating seasons during the period 2006–2010 for artificial neural network (ANN) modeling. The ANN modeling of the Afyon GDHS is used as a test system to demonstrate the effectiveness and economic impact of the ExEBCS under various operating conditions. Then, the ExEBCS is evaluated economically in case of application to real Afyon GDHS of the ExEBCS. The results show that the initial cost for the ExEBCS is more expensive than that for the old one by 6.33 kUS$/year as a result of replacing automatic controller. The saving in heat production makes the ExEBCS profitable by up to 7% of annual energy saving as a result of the increase in the heat production by 88% when the control system is operated. This results in a short payback period of 3.8 years. This study confirms that the use of ExEBCS in district heating systems (especially GDHS) is quite suitable.

[1]  M. J. Moran,et al.  Thermal design and optimization , 1995 .

[2]  Dennis L. Loveday,et al.  Artificial intelligence for buildings , 1992 .

[3]  İsmail Yabanova,et al.  Thermal monitoring and optimization of geothermal district heating systems using artificial neural network: A case study , 2012 .

[4]  Myoung-Souk Yeo,et al.  Predictive Control of the Radiant Floor Heating System in Apartment Buildings , 2002 .

[5]  Khalid M. Saqr,et al.  Development Of A Novel Control Strategy For A Multiple-Circuit Rooftop Bus Air-Conditioning System In Hot Humid Countries , 2008 .

[6]  Michaël Kummert,et al.  A neural network controller for hydronic heating systems of solar buildings , 2004, Neural Networks.

[7]  Ibrahim Dincer,et al.  New energy and exergy parameters for geothermal district heating systems , 2009 .

[8]  Ali Keçebaş,et al.  Performance and thermo-economic assessments of geothermal district heating system: A case study in Afyon, Turkey , 2011 .

[9]  Abdullatif Ben-Nakhi,et al.  Energy conservation in buildings through efficient A/C control using neural networks , 2002 .

[10]  Zoltán Pásztory,et al.  Multi-layer heat insulation system for frame construction buildings , 2011 .

[11]  İsmail Yabanova,et al.  Artificial neural network modeling of geothermal district heating system thought exergy analysis , 2012 .

[12]  Taraneh Sowlati,et al.  A multicriteria approach to evaluate district heating system options , 2010 .

[13]  Ibrahim Dincer,et al.  Investigation of some renewable energy and exergy parameters for two Geothermal District Heating Systems , 2011 .

[14]  C. Byron Winn,et al.  Optimal controllers of the second kind , 1979 .

[15]  Constantinos A. Balaras,et al.  Development of a neural network heating controller for solar buildings , 2000, Neural Networks.

[16]  Theodore F. Smith,et al.  Development of proportional-sum-derivative control methodology , 1996 .

[17]  Ali Keçebaş,et al.  Performance investigation of the Afyon geothermal district heating system for building applications: Exergy analysis , 2011 .

[18]  Christopher Kennedy,et al.  Energy use in Canada: environmental impacts and opportunities in relationship to infrastructure systems , 2005 .

[19]  Ali Keçebaş Energetic, exergetic, economic and environmental evaluations of geothermal district heating systems: An application , 2013 .

[20]  İsmail Yabanova,et al.  Development of ANN model for geothermal district heating system and a novel PID-based control strategy , 2013 .

[21]  Peng Jia,et al.  ANN-based PID controller for an electro-hydraulic servo system , 2008, 2008 IEEE International Conference on Automation and Logistics.

[22]  Nicolas Morel,et al.  NEUROBAT, A PREDICTIVE AND ADAPTIVE HEATING CONTROL SYSTEM USING ARTIFICIAL NEURAL NETWORKS , 2001 .

[23]  Derya Burcu Özkan,et al.  Optimization of insulation thickness for different glazing areas in buildings for various climatic regions in Turkey , 2011 .