Electrical Power and Energy Systems 34 (2012) 81–89 Contents lists available at SciVerse ScienceDirect Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes Comparative evaluation of different power management strategies of a stand-alone PV/Wind/PEMFC hybrid power system Erkan Dursun ⇑, Osman Kilic Marmara University, Technical Education Faculty, 34722 Goztepe, Istanbul, Turkey a r t i c l e i n f o Article history: Received 7 January 2011 Received in revised form 15 August 2011 Accepted 20 August 2011 Available online 1 November 2011 Keywords: Stand-alone hybrid power system Energy management Battery energy efﬁciency a b s t r a c t This study presents different power management strategies of a stand-alone hybrid power system. The system consists of three power generation systems, photovoltaic (PV) panels, a wind turbine and a proton exchange membrane fuel cell (PEMFC). PV and wind turbine is the main supply for the system, and the fuel cell performs as a backup power source. Therefore, continuous energy supply needs energy storing devices. In this proposed hybrid system, gel batteries are used. The state of charge (SOC), charge-discharge currents are affecting the battery energy efﬁciency. In this study, the battery energy efﬁciency is evaluated with three different power management strategies. The control algorithm is using MatlabSimulinkÒ. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction The demand for new and environmentally friendly energy system is growing worldwide. Wind and solar energy systems are taking the biggest share from, this current trend . To increase the energy reliability, wind and solar energy are used as dual energy sources. However, seasonal climatic conditions and geographic conditions affect the wind-solar energy output [2,3]. Therefore, a third energy system is needed to improve the energy supply reliability. Thus, the PEM fuel cell ideally fulﬁlls the need for any start up power. When the wind-solar system energy output is insufﬁcient, the fuel cell backups the supply system. However, fuel cell lifetime is less than 2000 h for transportation and 20,000 h for stationary fuel cells . Frequent start-up and shutdown actions degrade the electrolyzer and the fuel cell performance . In addition, battery charge-discharge cycle and battery bank energy efﬁciency gains importance. Therefore, improved energy management strategies are proposed, and Matlab/Simulink simulation results are presented. The proposed strategies are implemented as a case study to a mobile house for two-member family designed by UNIDOICHET. The evaluation of the power management strategy performance is evaluated using real weather data for the region of installation. In the literature, there are a few studies related to power management of hybrid power systems. Ipsakis et al. have proposed a power management strategy for hydrogen production performance ⇑ Corresponding author. Tel.: +90 216 3365770; fax: +90 216 337 89 87. E-mail addresses: [email protected] (E. Dursun), [email protected] (O. Kilic). 0142-0615/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijepes.2011.08.025 and system efﬁciency . Onar et al. proposed a power management strategy algorithm which dealt with a hybrid (wind turbine/PV/fuel cell) power system containing a ultra capacitor bank . Ahmed et al. proposed Power management strategy studied power ﬂuctuations on a hybrid power system . Mohamed and Koivo have proposed an optimization and simulation algorithm for the microgrid system containing a wind turbine, a micro turbine, a diesel generator, a photovoltaic array, a fuel cell and a battery storage . In this study, three new power management strategies are proposed. Their effects on battery bank energy efﬁciency and PEMFC membrane life span is truly investigated. The paper is organized as follows. Section 2, describes of the hybrid power system. Section 3, the structure of the battery bank charge–discharge currents. Finally, presented power management strategies and control algorithms. 2. Hybrid power system The hybrid system consists of three power generation systems, photovoltaic (PV) arrays, a wind turbine and a fuel cell. The PV and wind turbine are used as the main power generation system for the system and the fuel cell is assigned as a backup power generator for the continuous power supply. The hybrid power system consists of an 8 1 array each with a 100 W PV panel, a 1 kW wind turbine, and a 2 kW fuel cell. The hybrid power system and data acquisition setup given Figs. 1 and 2. Energy ﬂow route is given at Fig. 3. The control system of the hybrid power system uses the fuel cell as a backup power. The electrolyzer produces hydrogen for storage. This hydrogen is kept in a hydrogen tank. This system is installed 82 E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 where In, Vn, and Dn are the current, voltage and duty cycle of each appliance used during the day, respectively and Ed shows the total energy demand for the system. The average daily energy consumption of the system is calculated as 4220 Wh (Table 1). The total power, 2695 W, declares the maximum instantaneous power, which the inverter should meet; to maintain the stability of the energy supply, an inverter rated at least 2295 W is required. Daily average AC loads of the system is shown Fig. 6. 2.2. System components PV panels are composed of poly-Si PV modules. The commonly used three types of solar PV system are amorphous, monocrystalline, polycrystalline . Polycrystalline silicon (poly-Si) solar cells are receiving signiﬁcant attention in recent years due to the potential of reduced manufacturing cost . The technical speciﬁcations of the PV panels are at Table 2. The PV panels have a tilt angle of 41° with respect to optimum panel tilt angle according to the latitude of the region’s geographical location [15,16]. The power output of the photovoltaic module is based on current and voltage as follows , a- Wind turbine (Zephyr Air dolphin) b- PV panels (Solera) c- Weather station (Davis Vantage Pro2) Fig. 1. The hybrid power system . PPV ¼ Y PV fPV 2- DC-DC converter for the PV panels 3- DC power supplies 4- Fuses 5- Voltage transducers 6- Current transducer for AC loads 7- DAQ (Data acquisition) NIcFP-180x ½1 þ ap ðT C T C;STC Þ ð2Þ 1 qAC p ðk; hÞV 3 2 Pw ¼ 9- Current transducer for PV panels q is the air density (kg m3), A the rotor sweep area (m2), Cp the 0 0 in Istanbul, Turkey (41°33 N; 28°59 E). The wind-solar data used in the study were taken from the weather station for the year 2009 . Solar radiation and wind speed data of the Istanbul are shown in Figs. 4 and 5. 2.1. Load proﬁle The load proﬁle of a two-person family is established for annual power consumption. The load proﬁle of the system is analyzed to ensure that energy source generates sufﬁcient energy during the whole year. Eq. (1) shows the estimation of average daily energy consumption. In V n Dn ð3Þ power coefﬁcient, a function of tip speed ratio (k) and pitch angle (h), and V is the wind velocity (m s1)Energy output from the turbine can be calculated by Fig. 2. Data acquisition setup. i¼1 GT;STC 8- Current transducer for the battery bank 10- DC bus n X ! PPV is the output power of the PV array (kW), YPV the rated capacity of the PV array, meaning its power output under standard test conditions (kW), fPV the PV derating factor (%), GT the solar radiation incident on the PV array (kW m2), GT;STC incident radiation at standard test conditions (1 kW m2), ap the temperature coefﬁcient = 0.004 °C1, Tc the PV cell operation temperature (°C), TC,STC PV cell temperature under standard test conditions (25 °C). Thermocouples used for PV panel back surface temperatures are shown in Fig. 7. Monthly averages PV panel’s output power at Fig. 8. The wind turbine generates 1 kW of rated power with a permanent magnet synchronous generator. Wind turbine AC/DC converter is a built in device. The Wind turbine technical speciﬁcations are in Table 3 . Electricity obtained from the wind turbine can be calculated using the wind speed data. The instantaneous power produced from wind is [19,20]; 1- DC-DC converter for the PEMFC Ed ¼ GT ð1Þ Ew ¼ n X P i ðwÞt ð4Þ i¼1 where n is the number of hours in the period such as year, season or month, t is 1 h. Monthly results are given at Fig. 9. PEMFC is a common type of fuel cell, and traditionally uses hydrogen . PEMFC has been regarded as the most adequate system as a power source for many portable electric devices. PEMFC could also be a sustainable alternative for the power generation in zero-emission automotive applications as well as for stationary power stations [22,23]. PEMFC technical speciﬁcations are at Table 4 . The PEM air-cooled fuel cell is from the FutureE model Jupiter the rated power 2 kW.Peak values show the load demand current rate with respect to time. A daily PEMFC power output at Fig. 10. The fuel cell was not active in February and July from Fig. 11. Hence, the wind turbine and E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 83 Fig. 3. Energy ﬂow route of the system. Fig. 4. Monthly average global solar radiation of Istanbul. Fig. 5. Monthly average wind speed of Istanbul. PV panels supplied the total load demand. The battery bank consists of eight batteries each of 200 Ah 12 V. The battery bank capacity is 19.2 kW h. The usable capacity is 9.6kWh, which is sufﬁcient for 1.8 days of autonomy. The hydrogen tank has 10 kg of capacity, which is enough to absorb all produced hydrogen, and are connected to the fuel cell. The system is composed of a 0.4 kW electrolyzer and a 3.5 kW inverter. Electrolyzer speciﬁcations are shown in Table 5. 84 E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 Table 1 Calculated energy consumption of the system. Appliance Power (W) Air conditioner Refrigerator LCD TV Electrolyzer Lighting Water heater Total a 560 70 65 400 100 1500 2695 Used/day (h) a 5 8a 2a 0.5 2a 0.22 Table 2 PV panel parameters . Energy used/day (Wh) Maximum power (W) Maximum current (A) Short circuit current (A) Open circuit voltage (V) Number of cells and type Weight (kg) Length (mm) Depth (mm) Efﬁciency (%) 2800 560 130 200 400 330 4220 100 5.86 6.44 21.4 36 poly-Si 12 1490 35 16 Discrete work hours. 3. The battery energy efﬁciency Usually, two indexes, the state-of-charge (SOC) and the terminal voltage mainly characterize a lead–acid battery. Besides, the charge or discharge time and the current value are required . SOC ¼ SOC 0 þ Z t t0 Capbat Ibat Ibat dt Capbat ð5Þ battery capacity ðAhÞ the battery current ðAÞ where SOC0 the battery SOC of the starting point; t0 and t, are the time of the starting point and the time of interest, respectively. Kattakayam and Srinivasan  recommended through trial and error and pro-longed experimentations that 50% < SOC < 80% would be ideal working range for the lead–acid batteries. The lower limit is in tune with the ﬁndings of Lancashire  and Calloway , which observed the life of the battery bank, expands to 4000 charges/discharges cycles at 60% SOC or to 2000 cycles at 40% SOC. The upper limit arises out of heating effects and gassing. Fig. 12 shows the annually SOC variation of the battery bank. Most storage systems are not ideal, losses occur in charging and discharging cycles during storing periods [30,31]. 4. Discharge and charge currents The value, at any time, of the battery charge and discharge currents will vary according to the excess or shortage of local power available. However, it is sensible, through a charge controller, to limit the discharge and charge rates to maximum values to protect Fig. 7. Thermocouples used for PV panel operation temperature. the battery and ensure an efﬁciently operation [32–34]. When the fuel cell does not work, the battery current can be calculated as follows. Ibat0 ¼ pPV greg1 þ Pwind greg2 P dem =ginv erter V bat ð6Þ PPV is the PV output power (kW), Pwind the wind turbine output power (kW), greg1 the PV panel’s regulator efﬁciency (%) = 90%, greg2 wind turbine’s regulator efﬁciency (%) = 90%, pdem the demand power (kW), ginverter the inverter efﬁciency (%) = 92%, Vbat battery bank voltage (V), Pfc fuel cell output power (kW), and gcon is the fuel cell’s converter efﬁciency (%) = 90%. Fig. 6. Daily average AC loads curve in February, 2009. 85 E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 Fig. 8. Monthly averages PV panels output power. Table 4 PEM fuel cell parameters. Table 3 Wind turbine parameters. Wind turbine type Rotor diameter (mm) Weight (kg) Blade number Generator type Cut-in (m s1) Cut-off (m s1) Nominal power (W) Maximum power (W) Output voltage Vertical axis 1800 17.5 3 Permanent magnet synchronous 2.5 50 1000 3200 (20 m s1) 25 VDC Fuel cell type PEM Nominal power (kW) Number of cells Output voltage Efﬁciency (%) Consumption 2 70 48 VDC 50 22 slpm 1400 1200 Ibat00 pPV greg1 þ Pwind greg2 þ Pfc gcon Pdem =ginv erter ¼ V bat ð7Þ 1000 Power [W] If battery current is positive, the battery is discharging. If battery current is negative, the battery is charging. When fuel cell is working, battery current; 800 600 400 200 5. Power management strategies 0 The main decision factors for the power management strategies are the level of the power provided by the renewable energy system (wind-solar) and the state of charge (SOC) of the battery bank. The battery bank or the fuel cell should be capable of providing the needed power. Power energy generated by wind turbine (Pwind) and Time [min] Fig. 10. PEMFC output power in a day. PV panels (Psolar) is summed up at renewable energy system power (Pres). Load (Pload) is subtracted from the Pres and the excess power Fig. 9. Monthly average wind turbine output power. 86 E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 Fig. 11. Monthly average PEMFC output power. Fig. 12. Annual SOC [%] of the battery bank. Table 5 Electrolyzer speciﬁcations . Maximum power (W) Hydrogen ﬂow rate (slh1) Max outlet pressure Purity Operating temperature Storage temperature Efﬁciency 400 60 10.5 bar 99.9999% 15–40 °C 2–60 °C 35% (Pexcess). The stand-alone system is composed from renewable power sources. Therefore, the power management strategies became even more complex. The algorithms for strategy1, strategy2 and strategy3 are given at Figs. 13–15 respectively. At strategy1, SOCmax > SOC > SOCmin and Pexcess > 0, the electrolyzer will run and the battery bank will discharge. When, SOC 6 SOCmin and hydrogen tank pressure P 4, the fuel cell will run and the battery bank will be charged (Fig. 13). At strategy2, SOCmax > SOC > SOCmin and Pexcess 6 0, the fuel cell will not run, and the battery bank will be discharged. When, SOC 6 SOCmin, the battery bank will charged (Fig. 14). At strategy3, SOCmax > SOC > SOCmin and Pexcess > 0, the electrolyzer will run, and the battery bank will be charged. If, SOC 6 SOCmin or Pexcess 6 0, the fuel cell will run, and battery bank discharges (Fig. 15). The best result for the battery bank energy Fig. 13. Power management strategy1 for the hybrid power system. efﬁciency was obtained from the strategy3 algorithm. In strategy3, renewable energy system (RES) power is then directed to the electrolyzer for hydrogen production. This strategy aims to protect the battery bank from overcharging. The developed algorithms have E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 87 degrade their performance and possibly reduce their lifespan with strategy3. The battery bank energy efﬁciency is obtained with Eq. (8). Hybrid power system algorithm for power management is shown Fig. 16. The control subsystem driven from Eq. (8) is shown at Fig. 17. The battery energy efﬁciency (gb) of the battery is expressed as the ratio between the output energy from the battery, Eout (kW h year1), and the total inputs, Ein (kW h year1). gb ¼ Eout 100% Ein ð8Þ Eout ¼ P out t Fig. 14. Power management strategy2 for the hybrid power system. Fig. 15. Power management strategy3 for the hybrid power system. improved overall efﬁciency closed to 80–85% range (Fig. 18). Thus, this efﬁciency range is well above than previously proposed results . The energy efﬁciency of the battery bank was between 73.1% and 84% [36,37] from previous studies. Frequent start-up and shut down actions for the electrolyzer, and the fuel cell will eventually ð9Þ Ein ¼ Pin t ð10Þ Pout V bat Ibatdischarge ð11Þ Pin ¼ V bat Ibatcharge ð12Þ Ibatcharge the charge current of the battery bank, Ibatdischarge the discharge current of the battery bank, Pout instantaneous output power of the battery bank, Vbat instantaneous voltage of the battery bank. The higher is the total energy efﬁciency of the battery. The lower is the cost of charging the battery. Therefore, the control algorithm is needed to keep the battery efﬁciency is as high as possible. The energy efﬁciency of the battery is affected by the charging and discharging currents. All three strategies have fully supplied the connected loads. Since, the battery bank is a bit oversized, the supply capacity for the system is high. The PEMFC start-up number is less in strategy3 (Fig. 19). This improves the fuel cell membrane lifetime. The PEMFC hydrogen consumption reached it is lowest level with strategy3. Thus, the PEMFC energy production is also at its minimum. Even though the hydrogen consumption is at its minimum, the energy need is supplied continuously. PMS3 resulted in the highest hydrogen production because the entire RES power was directed to the electrolyzer whenever the maximum SOC limit was reached. However, the largest variability in the SOC for the accumulator caused the fuel cell to operate more intensively. Therefore, hydrogen inventory was depleted during the four-month time period leading to signiﬁcant deﬁcit in hydrogen. The PEMFC running time at PM strategy3 is shown in Fig. 20. Ò Fig. 16. Hybrid power system algorithm in Matlab/Simulink . 88 E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89 Fig. 17. Control subsystem. 6. Conclusions Fig. 18. Comparison of the annual battery bank energy efﬁciency. 100 PEMFC electrical production (kWh) PEMFC start-up number 90 80 Using stand-alone wind-solar energy system has become popular in recent years. Stand-alone power system depends on the geographical and meteorological conditions of the installed region. Therefore, the wind turbine and solar cells may not meet the energy demand. So, a third power supply source might be needed. This source should not be affected from any geographical or meteorological conditions. PEMFC is an ideal power generation system for such implementations. However, the price of PEMFC is high and its membrane lifetime is short. Thus to increase the operation time of the membrane and to enable the continuous energy ﬂow, three power management strategies are proposed. The proposed power management strategies for the hybrid power system satisfy the load and battery bank SOC. Battery bank’s maximum and minimum SOC levels are determining the operation of the fuel cell. All these strategies have enhanced the energy efﬁciency of the battery bank, and the results are compared at Fig. 18. The best result for energy efﬁciency is obtained with strategy3. The battery bank’s energy efﬁciency has reached up to 85% with this proposed power management algorithm. 70 60 50 Acknowledgments 40 30 20 10 0 PM strategy1 PM strategy2 PM strategy3 Fig. 19. Annual electrical production and start-up number of the PEMFC. The project is supported by UNIDO-ICHET (United Nations Industrial Development Organization – International Centre for Hydrogen Energy Technologies) with the mission of raising public awareness for renewable energy and demonstrating viable implementations of hydrogen energy technologies in developing countries. Partial support from NANOCOFC project under EC-FP6 program is also acknowledged. Special thanks to Dr. M. Suha Yazıcı and Mehmed Eroglu from UNIDO-ICHET. References Fig. 20. The PEMFC running time at PM strategy3.  Erdem ZB. The contribution of renewable resources in meeting Turkey’s energy-related challenges. Renew Sust Energy Rev. 2010;14:2710–22.  Degeilh Y, Singh C. A quantitative approach to wind farm diversiﬁcation and reliability. Int J Electr Power Energy Syst 2011;33:303–14.  Zervas PL, Sarimveis H, Palyvos JA, Markatos NCG. Model-based optimal control of a hybrid power generation system consisting of photovoltaic arrays and fuel cells. J Power Sources 2008;181:327–38.  Wang Y, Chen KS, Mishler J, Cho SC, Adroher XC. A review of polymer electrolyte membrane fuel cells: Technology, applications, and needs on fundamental research. Appl Energy, in press. 10.1016/j.apenergy.2010.09.030.  Miller M, Bazylak A. A review of polymer electrolyte membrane fuel cell stack testing. J Power Sources 2011;196:601–13.  Ipsakis D, Voutetakis S, Seferlis P, Stergiopoulos F, Elmasides C. Power management strategies for a stand-alone power system using renewable energy sources and hydrogen storage. Int J Hydrogen Energy 2009;34:7081–95. E. Dursun, O. Kilic / Electrical Power and Energy Systems 34 (2012) 81–89  Onar OC, Uzunoglu M, Alam MS. Modeling, control and simulation of an autonomous wind turbine/photovoltaic/fuel cell/ultra-capacitor hybrid power system. J Power Sources 2008;185:1273–83.  Ahmed NA, Miyatake M, Al-Othman AK. Power ﬂuctuations suppression of stand-alone hybrid generation combining solar photovoltaic/wind turbine and fuel cell systems. Energy Convers Manage 2008;49:2711–9.  Mohamed FA, Koivo HN. System modelling and online optimal management of microgrid using mesh adaptive direct search. Int J Electr Power Energy Syst 2010;32:398–407.  Eroglu M, Dursun E, Sevencan S, Song J, Yazici S, Kilic O. A mobile renewable house using PV/wind/fuel cell hybrid power system. Int J Hydrogen Energy 2011;36:7985–92.  http://www.davisnet.com/weather/products/vantagepro.asp [10.03.09].  Sherwani AF, Usmani JA, Varun. Life cycle assessment of solar PV based electricity generation systems: a review. Renew Sust Energy Rev 2010;14: 540–4.  He S, Sproul AB. Optical properties of evaporated poly-Si thin-ﬁlms on glass. Thin Solid Films 2010;519:351–6.  http://www.rixinsolar.com/english/chanpin_Article_Show.asp?ArticleID=301 [08.02.09].  Kacira M, Simsek M, Babur Y, Demirkol S. Determining optimum tilt angles and orientations of photovoltaic panels in Sanliurfa, Turkey. Renew Energy 2004;29:1265–75.  Chang TP. Output energy of a photovoltaic module mounted on a single-axis tracking system. Appl Energy 2009;86:2071–8.  Skoplaki E, Palyvos JA. On the temperature dependence of photovoltaic module electrical performance. A review of efﬁciency/power correlations. Sol Energy 2009;83:614–24.  <http://www.zephyreco.co.jp/en/products/product/air-dolphin/speciﬁcation. html> [08.02.09].  Ghedamsi K, Aouzellag D. Improvement of the performances for wind energy conversions systems. Int J Electr Power Energy Syst 2010;32:936–45.  Elizondo J, Martínez J, Probst O. Experimental study of a small wind turbine for low- and medium-wind regimes. Int J Energy Res 2009;33:309–26.  By EG&G Services Parsons, Inc. Science Applications International Corporation Under Contract No. DE-AM26-99FT40575 US Department of Energy Ofﬁce of Fossil Energy National Energy Technology Laboratory P.O. Box 880 Morgantown, West Virginia 26507-0880, Fuel Cell Handbook, Fifth ed.; 2000.  Santa Rosa DT, Pinto DG, Silva VS, Silvab RA, Rangel CM. High performance PEMFC stack with open cathode at ambient pressure and temperature conditions. Int J Hydrogen Energy 2007;32:4350–7. 89  Jia J, Wang Y, Li Q, Cham YT, Han M. Modeling and dynamic characteristic simulation of a proton exchange membrane fuel cell. IEEE Trans Energy Convers 2009;24(1):283–91.  http://www.future-e.com/en/produkte_jupiter.htm. [08.02.09].  <http://www.heliocentris.com/ﬁleadmin/user_upload/03_Systems/H2_Supply/ Hydrogen_Generator_ENG_1006_01.pdf>. [10.02.09].  El-Shafy A, Nafeh A. An effective and safe charging algorithm for lead-acid batteries in PV systems. Int J Energy Res, 10.1002/er.1735.  Kattakayam TA, Srinivasan K. Lead acid batteries in solar refrigeration systems. Renew Energy 2004;29:1243–50.  Lancashire SJ. Life cycle comparison of different battery types for use with photovoltaic systems. IEEE PV Specialists Conf 1988;2:1158.  Calloway TM. Autonomous photovoltaic diesel power system design. In: 18th IEEE photovoltaic specialists conference; 1985. p. 280.  Sharma P, Agarwal V. Optimization of Operational Energy Cost in a Hybrid Distributed Generation System Industrial and Information Systems, 2008. ICIIS 2008. IEEE Region 10 and the Third international Conference on Digital Object Identiﬁer: 10.1109/ICIINFS.2008.4798462 Publication Year: 2008; 1.  Zhang J, Xia C. State-of-charge estimation of valve regulated lead acid battery based on multi-state unscented Kalman ﬁlter. Int J Electr Power Energy Syst 2011;33:472–6.  Jenkins DP, Fletcher J, Kane D. Model for evaluating impact of battery storage on microgeneration systems in dwellings. Energy Convers Manage 2008;49: 2413–24.  Maclay JD, Brouwer J, Samuelsen GS. Dynamic analyses of regenerative fuel cell power for potential use in renewable residential applications. Int J Hydrogen Energy 2006;31:994–1009.  Noroozian R, Abedi M, Gharehpetian GB, Hosseini SH. Distributed resources and DC distribution system combination for high power quality. Int J Electr Power Energy Syst 2010;32:769–81.  Kaldellis JK, Zaﬁrakis D, Kavadias K. Techno-economic comparison of energy storage systems for island autonomous electrical networks. Renew Sust Energy Rev 2009;13:378–92.  Li CH, Zhu XJ, Cao GY, Sui S, Hu MR. Dynamic modeling and sizing optimization of stand-alone photovoltaic power systems using hybrid energy storage technology. Renew Energy 2009;34:815–26.  Ikeya T, Sawada N, Takagi S, Murakami J, Kobayashi K, Sakabe T, et al. Charging operation with high energy efﬁciency for electric vehicle valve-regulated lead– acid battery system. J Power Sources 2000;91:130–6.