Available online at ScienceDirect. Energy Procedia 75 (2015 )

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1 Available online at ScienceDirect Energy Procedia 75 (2015 ) The 7 th International Conference on Applied Energy ICAE2015 Optimization on performance of the latent heat storage unit (LHSU) in telecommunications base stations (TBSs) in China Li Yantong a, Zhang Quan a,*, Sun Xiaoqin b, Du Yaxing a, Liao Shuguang c a College of Civil Engineering, Hunan University, Changsha, , China b School of Energy and Power Engineering, Changsha University of Science and Technology Changsha, , China c Changsha Maxxom High-Tech Co. Ltd., Changsha, , China Abstract A latent heat storage unit (LHSU) that combined with energy storage modules and an air cooler was investigated to save the space cooling energy consumption in telecommunications base stations in China. A mathematical model was employed to simulate the heat transfer processes within energy storage modules and air cooler. In addition, an experiment was carried out in an enthalpy difference laboratory. The relative errors of air and temperature difference between the simulation and experimental results were calculated for energy charging process and energy discharging process, respectively. It was shown that the relative error for the water circulation system was reported to 1.33% and 5.23% under the charging and discharging process and 7.27% and 8.00% for air circulation system. The annual energy saving ratio was presented as a function of PCM melting temperature for varied pump flow rates and fan flow rates. To obtain the maximum annual energy savings ratio, a genetic algorithm was developed considering fan flow rate, pump flow rate and melting temperature of PCM. Annual energy savings ratios were improved by 6.48%, 4.39%, 3.48%, and 3.51% in Shenyang, Zhengzhou, Changsha, and Kunming, respectively The Authors. Published by Elsevier by Elsevier Ltd. This Ltd. is an open access article under the CC BY-NC-ND license ( Peer-review Selection and/or under responsibility peer-review of under Applied responsibility Energy Innovation of ICAE Institute Keywords:latent heat storage unit; energy savings ratio; genetic algorithm 1. Introduction Approximately 7 billion (kwh) electricity is consumed by telecommunication base stations (TBSs) in China every year, which has the largest communication network scale in the world [1]. Among the total electrical consumption, air conditioning system is using 30-50% electricity of the entire electricity consumption in TBS. More efficient air conditioning system should be developed to reduce its energy consumption [2]. Free air cooling can reduce the space cooling consumption in TBSs [3]. However, natural cold energy is discrete and unpredictable. Latent heat storage system having high energy storage density [6, 7] is used to bridge the gap between energy supply and demand of natural cold energy [4, 5], because it provides. Sun et al. [8] investigated the energy and electricity savings from the application of * Corresponding author. Tel.: address: quanzhang@hnu.edu.cn The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of Applied Energy Innovation Institute doi: /j.egypro

2 2120 Li Yantong et al. / Energy Procedia 75 ( 2015 ) PCM boards in building enclosures theoretically for a time period of three summer months. At recent years, LHSU had been proposed with a natural cold source to generate cool air to reduce the indoor air temperature in TBSs [9]. However, the operation conditions [10] and the PCM melting temperature [11] are the main factors to influence performance of the LHSU system. Haillot et al. [12] identified the optimal PCM melting temperature to maximize the solar fraction or minimize the electrical consumption for the hot water system. In Ref. [13], the optimal air flow rate was found to maximize the coefficient of performance in a latent heat thermal storage system and meet the need for comfort conditions in Eindhoven city. This work focuses on the optimization of the LSHU previously developed in Ref [9]. A mathematical model was developed to the heat transfer processes within energy storage modules and air cooler. Inlet and outlet water temperatures and outlet air temperature of LSHU were calculated. Average relative errors were obtained, comparing with the experimental data measured in an Enthalpy Difference Laboratory. Energy savings ratios were predicted for the different melting temperatures of PCM and pump flow rates. Finally, a genetic algorithm (GA) was developed to get optimal PCM melting temperature and operation conditions containing fan flow rate, pump flow rate to maximize the annual energy savings ratios of the LSHU system for TBSs in four different climatic zones in China. 2. System description Fresh air Supply air 9 Return air 3 4 Energy charging and fresh air mode Energy discharging mode Fig.1 Schematic diagram of the latent heat storage unit (LHSU) in the TBS Supply air 9 1. Fresh air inlet 2. Filter 3. Air valve 4. Return air inlet 5. Air cooler 6. Pump 7. Fan 8. Energy storage module 9. Supply air outlet Fig. 1 presents schematic diagram of the latent heat storage unit (LHSU) [9] in the TBS. The outer diameter and length of copper pipe are 9.52 mm and approximately 3 m, respectively. Copper pipe connects the air cooler (AC) and the energy storage modules (ESMs), forming a closed water loop. LHSU operates under three modes, which are the energy charging, fresh air, and the energy discharging modes. For the energy charging mode, outdoor air temperature is between 0 o C and the PCM melting temperature. Pump and fan are running in this mode. When outdoor air temperature is in the range of the PCM melting temperature to 25 o C, fresh air is drawn into TBS. In addition, when outdoor air temperature is over 25 o C, LHSU is switched to discharging mode. Pump and fan are running to release the cold energy. 3. Theoretical formulation LHSU performance optimization was carried out using a genetic algorithm (GA), which was known to be robust and particularly efficient to deal with discontinuous parameters [12]. It was used to maximize the LHSU energy savings ratio (ESR), considering the PCM melting temperature, the fan flow rate and pump flow rate. Fig. 2 presents flow chart of energy savings ratio optimization process for different

3 Li Yantong et al. / Energy Procedia 75 ( 2015 ) operation conditions using GA. Start GA Optimization GA Population Initialization Igen=0,[Gw,Ga,Tm] Calculate Objective Function ESR(Gw,Ga,Tm) Igen 1500? No Yes GA Operation:Selection GA Operation: Crossover,Mutation Fitness Evaluation-the Igen generation 1.Calculate the fitness function ESR(Gw,Ga,Tm) 2.Record the elitist and the new best fitness,esr(igen) 3.Copy the best fitness to the worst fitness Igen=Igen+1 Stop &Output Best Fitness,Gw,Ga,Tm Fig. 2 Flow chart of energy savings rate optimization process for different operational conditions using GA Annual energy savings ratio was selected as the objective function in GA, which was defined as the rate of energy savings attained by using LHSU to the energy consumption of the conventional air conditioner. It depended on the fan flow rate, pump flow rate, and PCM melting temperature, the threshold values of which are varied from 1000m 3 /h to2000m 3 /h, 0m 3 /h to 1m 3 /h and 0 o C to 25 o C, respectively. The annual energy savings ratio (ESR) was calculated by Eq. (1): Icon ( Iec I fa Ied ) ESR 100% I. (1) con The heat transfer process in the LHSU consists of the heat transfer between the air and the water in the AC, and the heat transfer between the water and the PCM in the ESM. The heat transfer rate between the air and the water in the AC was calculated using Eqs. (2) (5): During the energy charging mode, out in Qaw, ec cama ( Ta, ec T a, ec ) (2) out in Qaw, ec cwmw( Tw, ec T w, ec ) (3) Q aw, ec UacAac Tawec, (4) During the fresh air mode, Q c m aw, fa a out a( Tin Ta, fa ) The heat transfer rate between the water and the PCM in the ESM was calculated using Eq. (6) and (7) [14, 15]: During the energy charging mode, out Q c m T T ) (6) wm, ec w in w( w, ec w, ec (5)

4 2122 Li Yantong et al. / Energy Procedia 75 ( 2015 ) Q wm, ec waap Twm, ec (7) For the discharging mode, the mechanism of heat transfer is similar to the charging process, where their heat transfer directions are opposite. 4. Results and discussion Comparisons between the calculated results and tested data are presented in Fig. 3. The experimental data are tested by placing the LHSU inside of an enthalpy difference laboratory (EDL) [9]. It is found that the relative error less than calculated by Sun [9] for charging and discharging modes. It was proven that the mathematical model developed and the corresponding program can be used to characterize the heat transfer process of LHSU more accurately. Fig. 3 Comparisons between calculated and tested temperature differences Annual energy savings ratios of the LHSU in four different Chinese climatic zones were predicted through a self-developed MATLAB program. Fig.4 presents energy savings ratio as a function of melting temperature of PCM at the constant fan flow rate of 2000 m 3 /h for different pump flow rate in four different Chinese climatic zones. When the pump flow rate increased from 0.2m 3 /h to 0.8m 3 /h, ESR increased, but the increasing trend slowed down. The maximum ESR was between 55% and 56% in Shenyang city, while they are between 56% and 57% in other three cities. Table.1 Optimization results of LHSU using genetic algorithm Locations Working conditions after optimization ESR (%) Fan flow rate(m 3 /h) Pump flow rate(m 3 /h) Melting temperature( o C) Before optimization After optimization Shenyang Zhengzhou Changsha Guangzhou Table.1 shows the optimal results of the genetic algorithm, which are obtained in four different Chinese climatic zones. Before optimization, the PCM melting temperature, fan flow rate and pump flow rate were set at 20 o C, 2000m 3 /h and 0.4m 3 /h, respectively. The energy savings ratio in Shenyang, Zhengzhou, Changsha, and Kunming was improved by 6.48%, 4.39%, 3.48%, and 3.51% after the optimization, respectively.

5 Li Yantong et al. / Energy Procedia 75 ( 2015 ) Shenyang Zhengzhou Changsha Kunming Fig.4 Energy savings ratio as a function of melting temperature of PCM in four different Chinese climatic locations for different pump flow rate 5. Conclusion In this paper, a latent heat storage unit that combined with energy storage modules and an air cooler was investigated to reduce the space cooling energy of TBSs in China. Annual energy savings ratios were depended on melting temperature of PCM of different pump flow rates and fan flow rates. In addition, GA was used to optimize the annual energy savings ratio to get the specified operational parameters and PCM melting temperature in different climatic zones in China. The conclusions were as follows. (1) The average relative error between experimental data and simulation results was 5.46% for water and air temperature differences, which illustrated that the mathematical model and corresponding program simulated the LHSU performance accurately. (2) After the optimization using GA, annual energy savings ratios were improved by 6.48%, 4.39%, 3.48%, and 3.51% in Shenyang, Zhengzhou, Changsha, and Kunming, respectively.

6 2124 Li Yantong et al. / Energy Procedia 75 ( 2015 ) Acknowledgements The authors appreciate the support of the International Engineering Foundation and the financial support from the National 863 Project (2012AA052503), Strategic Emerging Industries in Hunan Province (2012GK4069), Science and Technology Key Project in Hunan Province (2013WK2011), Science and Technology Plan Projects in Municipality of Changsha (K ), and Interdisciplinary Program in Hunan University. References [1] Chen Y, Zhang Y F, Meng Q L. Study of ventilation cooling technology for telecommunication TBS in Guangzhou. Energy and Buildings 2009;41: [2] Tu R, Liu X, Li Z, Jiang Y.Energy performance analysis on telecommunication base station.energ and Buildings 2011; 43: [3] Sorrentino M, Rizzo G, Genova F. Gaspardone M.A model for simulation and optimal energy management of telecom switching plants. Applied Energy 2010; 87: [4] Gioacchino N, Antonella M, Fabio D M, Nicole B. PCM-based energy recovery from electric arc furnaces. Applied Energy 2014;136: [5] Mohammad R, Mehrdad K, Mojtaba S S. Simulation of energy storage system with phase change material (PCM). Energy and Buildings 2012;49: [6] Francis A, Neil H, Philip E, Mervyn S. A review of materials, heat transfer and phase change problem formulation for latent heat thermal energy storage systems (LHTESS). Renewable and Sustainable Energy Reviews 2010;14: [7] Jegadheeswaran S, Pohekar S D, Kousksou T. Exergy based performance evaluation of latent heat thermal storage system:a review. Renewable and Sustainable Energy Reviews 2010;14: [8] Xiaoqin S, Quan Z, Mario A M, Kyoung O L. Energy and economic analysis of a building enclosure outfitted with a phase change material board (PCMB). Energy Conversion and Management 2014;83: [9] Xiaoqin S, Quan Z, Mario A Medina, Yingjun L, Shuguang L. A study on the use of phase change materials (PCMs) in combination with a natural cold source for space cooling in telecommunications base stations (TBSs) in China. Applied Energy 2014;117: [10] Samuel L, Christof H. Optimization of operation conditions for the startup of aerobic granular sludge reactors biologically removing carbon, nitrogen, and phosphorous. Water research 2014;59: [11] Roberta P, Marco M. Genetic optimization of a PCM enhanced storage tank for Solar Domestic Hot Water Systems. Solar Energy 2014;103: [12] Didier H, Erwin F, Stephane G, Jean P B. Optimization of solar DHW system including PCM media. Applied Energy 2013; 109: [13]Mosaffa A H, Ferreira C A I, Rosen M A,Talati F. Thermal performance optimization of free cooling systems using enhanced latent heat thermal storage unit. Applied Thermal Engineering2 013;59: [14] Mahfuz M H, Kamyar A, Afshar O, Sarraf M, Anisur M R, Kibria M A, et al. Exergetic analysis of a solar thermal power system with PCM storage. Energy Conversion and Management 2014;78: [15] Ya Q L,Ya L H, Zhi F W, Chao X, Weiwei W. Exergy analysis of two phase change materials storage system for solar thermal power with finite-time thermodynamics. Renewable Energy 2012;39: Biography Prof. Zhang Quan is a full professor in Hunan University, China; his research is focus on the renewable energy and the energy storage.