Applied Energy 87 (2010) 1158–1175
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Energy efﬁcient fuzzy based combined variable refrigerant volume and variable air volume air conditioning system for buildings R. Karunakaran a, S. Iniyan b,*, Ranko Goic c
Department of Mechanical Engineering, Anna University Tiruchirappalli-Thirukkuvalai campus, India Institute for Energy Studies, Department of Mechanical Engineering, Anna University Chennai, Chennai, India c Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia b
a r t i c l e
i n f o
a b s t r a c t
Energy conservative building design has triggered greater interests in developing ﬂexible and sophisticated air conditioning systems capable of achieving enhanced energy-savings potential without sacriﬁcing the desired thermal comfort and indoor air quality (IAQ). This research work greatly aimed at achieving enhanced energy conservation, good thermal comfort and better IAQ for space conditioning with the application of combined variable refrigerant volume (VRV) and variable air volume (VAV) air conditioning (A/C) systems. Experimental investigation on the proposed combined air conditioning system with the application of intelligent fuzzy logic controller was performed for summer and winter climatic conditions to substantiate the energy-savings capability. The proposed system experimentally analyzed under ﬁxed ventilation, demand controlled ventilation (DCV) and combined DCV and economizer cycle (EC) ventilation techniques effectively conserved 44% and 63% of per day average energy-savings in summer and winter design conditions respectively, while compared to the conventional constant air volume (CAV) A/C system. The results of the present investigation have proved that the proposed combined air conditioning system operated under the different ventilation strategies and controlled by the intelligent fuzzy logic controller (FLC) can be considered as an efﬁcient technology to achieve good thermal comfort, IAQ and energy conservation in the modern heating, ventilation and air conditioning (HVAC) applications. Ó 2009 Elsevier Ltd. All rights reserved.
Article history: Received 26 September 2008 Received in revised form 6 August 2009 Accepted 12 August 2009 Available online 19 September 2009 Keywords: Energy conservation Fuzzy logic Indoor air quality Thermal comfort Ventilation Variable refrigerant volume Variable air volume
1. Introduction For over a century, the heating, ventilation and air conditioning (HVAC) community has witnessed a quantum leap in the ﬁeld of design and value added renovations in air conditioning (A/C) engineering. The prime factors to be indisputably considered as the four pillars of the HVAC system are, thermal comfort, indoor air quality (IAQ), HVAC controls and energy-savings. The part played by humidity in the perception of thermal comfort cannot be exaggerated, as minor shifts in RH will have a sharp impact on microbial growth, in particular, at lower RH levels i.e. less than 30%. The thermal comfort and IAQ inside the building envelope can be obtained by properly monitoring the supply air temperature and supply airﬂow rate based on the ﬂuctuated thermal load conditions. Energy usage in air conditioning systems is considered an essential part of a building’s functional requirements. Since the late
* Corresponding author. Tel.: +91 44 22531070. E-mail addresses: email@example.com (R. Karunakaran), iniyan777@ hotmail.com (S. Iniyan), firstname.lastname@example.org (R. Goic). 0306-2619/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.apenergy.2009.08.013
1960s, however, HVAC engineers have begun to explore various design concepts to minimize energy use in air handling systems. The major drawback of the constant volume systems is that they generally use more energy. Variable volume...
References:  Zhou YP, Wu JY, Wang RZ, Shiochi S. Energy simulation in the variable refrigerant ﬂow air-conditioning system under cooling conditions. Energy Build 2007;39:212–20.  Wu Chen, Xingxi Zhou, Shiming Deng. Development of control method and dynamic model for multi-evaporator air conditioners (MEAC). Energy Convers Manage 2005;46:451–65.  Georges B, Winandy E, Lebrun J, Xia J. Experimental analysis of the performances of variable refrigerant ﬂow systems. Build Serv Eng Res Technol 2004;25:17–23.  Brodrick James, Roth Kurt W, Goetzler William. Variable ﬂow and volume refrigerant system. ASHRAE J 2004;46:S164.  Qi Qi, Deng Shiming. Multivariable control of indoor air temperature and humidity in a direct expansion (DX) air conditioning (A/C) system. Build Environ 2009;44:1659–67.  Liang Xia, Chan MY, Shiming Deng. Development of a method for calculating steady-state equipment sensible heat ratio of direct expansion air conditioning units. Appl Energy 2008;85:1198–207.  Li Zheng, Deng Shiming. An experimental study on the inherent operational characteristics of a direct expansion (DX) air conditioning (A/C) unit. Build Environ 2007;42:1–10.  Chen Wu, Deng Shiming. Development of a dynamic model for a DX VAV air conditioning system. Energy Convers Manage 2006;47:2900–24.  Nasution Henry, Wan Hassan Mat Nawi. Potential electricity savings by variable speed control of compressor for air conditioning systems. Clean Technol Environ Policy 2006;8:105–11.  Achter bosch GGJ, de Jong PPG, Kristspit PPG. The development of a convenient thermal dynamic building model. Energy build 1985;8:96–123.  Mendes N, Oliveira GHC, de Araujo HX. Building thermal performance analysis by using MATLAB/SIMULINK. In: Proceedings of 7th international IBPSA conference, IBPSA: Rio de Janeiro, Brazil; 2001. p. 473–7.  Nassif N, Moujaes S. A new operating strategy for economizer dampers of VAV system. Energy Build 2008;40:289–99.  Ke Y-P, Mumma SA. Using carbon dioxide measurements to determine occupancy for ventilation controls. ASHRAE Trans 1997. BN-97-1-1.  Lawrence Thomas M, Braun James E. A methodology for estimating occupant CO2 source generation rates from measurements in small commercial buildings. Build Environ 2007;42:623–39.  Lawrence Thomas M, Braun James E. Evaluation of simpliﬁed models for predicting CO2 concentrations in small commercial buildings. Build Environ 2006;41:184–94.  Chowdhury Ashfaque Ahmed, Rasul MG, Khan MMK. Thermal-comfort analysis and simulation for various low-energy cooling-technologies applied to an ofﬁce building in a subtropical climate. Appl Energy 2008;85:449–62.  Kontoleon KJ, Bikas DK. The inﬂuence of the zone’s indoor temperature settings on the cooling/heating loads for ﬁxed and controlled ventilation. Build Environ 2006;41:75–86.  Wang Shengwei, Xu Xinhua. Optimal and robust control of outdoor ventilation airﬂow rate for improving energy efﬁciency and IAQ. Build Environ 2004;39:763–73.  Shahnawaz Ahmed S, Shah Majid Md, Novia Hendri, Rahman Hasimah Abd. Fuzzy logic based energy saving technique for a central air conditioning system. Energy 2007;32:1222–34.  Thompson Richard, Dexter Arthur. A fuzzy decision-making approach to temperature control in air-conditioning systems. Control Eng Practice 2005;13:689–98.  Calvino Francesco, Gennusa Maria La, Rizzo Gianfranco, Scaccianoce Gianluca. The control of indoor thermal comfort conditions: introducing a fuzzy adaptive controller. Energy Build 2004;36:97–102.  Aprea C, Mastrullo R, Renno C. Fuzzy control of the compressor speed in a refrigeration plant. Int J Refrig 2004;27:639–48.  Kim Jung Ho, Kim Kyung Sik, Sim Min Sub, Han Kyung Hae, Ko Bum Suk. An Application of Fuzzy Logic to control the Refrigerant Distribution for the Multi type Air conditioner. In: Proceedings, international fuzzy systems conference Seoul, Korea; 1999. p. 22–5.  Cheung JYM, Kamal AS. Fuzzy logic control of refrigerant ﬂow. In: Proceedings (Conf. Publ. No. 427), control ’96, UKACC international conference UK; 1996. p. 2–5.  ASHRAE. ASHRAE handbook fundamentals. Atlanta, GA: ASHRAE Inc.; 1990.
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