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ScienceDirect Energy Procedia 107 (2017) 232 – 236

3rd International Conference on Energy and Environment Research, ICEER 2016, 7-11 September 2016, Barcelona, Spain

Modelling and Simulation of Standalone PV Systems with Batterysupercapacitor Hybrid Energy Storage System for a Rural Household Lee Wai Chong*, Yee Wan Wong, Rajprasad Kumar Rajkumar, Dino Isa The University of Nottingham Malaysia Campus, Jalan Broga, Semenyih 43500, Malaysia

Abstract This paper presents the comparison between the standalone photovoltaic (PV) system with battery-supercapacitor hybrid energy storage system (BS-HESS) and the conventional standalone PV system with battery-only storage system for a rural household. Standalone PV system with passive BS-HESS and semi-active BS-HESS are presented in this study. Two control strategies, Rule Based Controller (RBC) and Filtration Based Controller (FBC), are developed for the standalone PV system with semi-active BS-HESS with the aim to reduce the battery stress and to extend the battery lifespan. The simulation results show that the system with semi-active BS-HESS prolongs the battery lifespan by significantly reducing the battery peak current up to 8.607% and improving the average SOC of the battery up to 0.34% as compared to the system with battery-only system. © 2016The TheAuthors. Authors.Published PublishedbybyElsevier Elsevier Ltd. © 2017 Ltd. This is an open access article under the CC BY-NC-ND license Peer-review under responsibility of the scientific committee of the 3rd International Conference on Energy and Environment (http://creativecommons.org/licenses/by-nc-nd/4.0/). Research. under responsibility of the scientific committee of the 3rd International Conference on Energy and Environment Research. Peer-review Keywords: Renewable energy; PV; hybrid energy storage system; supercapacitor; battery; control strategy

1. Introduction In a standalone PV system with battery storage system, the battery usually experiences frequent deep cycles, irregular charging pattern which shorten the lifespan of the battery [1]. The supercapacitor and battery are complementary in technical characteristics, it is advantageous to incorporate both devices to form a Battery-

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1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 3rd International Conference on Energy and Environment Research. doi:10.1016/j.egypro.2016.12.135

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Lee Wai Chong et al. / Energy Procedia 107 (2017) 232 – 236

Supercapacitor Hybrid Energy Storage System (BS-HESS) which has the potential to reduce the size of the battery bank and improve the battery life [2]. There are several types of BS-HESS. Passive hybrid is the most common configuration that studied by researchers [3] where the battery and supercapacitor are connected in parallel. The advantages of passive HESS are simplicity, high reliability, and low cost because of the absence of control circuitries and power electronics. However, the power flow of the BS-HESS is uncontrollable [4]. Semi-Active HESS enhances the performance of passive HESS at the price of an additional bidirectional DC/DC converter and control circuitry [5]. This topology offers a good trade-off between the performance and the circuit complexity and process achieved because only one DC-DC converter is used. The common control strategies for BS-HESS are rule based controller (RBC) and filtration based controller (FBC). The RBC uses a set of rules to divide the power between battery and supercapacitor based on the real-time condition. FBC uses a filter to decompose the power demand of the HESS into high-frequency component and low-frequency component. This paper presents three different types of standalone PV system which are: (i) Standalone PV System with battery-only system, (ii) Standalone PV system with passive BS-HESS, and (iii) Standalone PV system with semiactive BS-HESS. Two control strategies, particularly FBC (Moving Average Filter) and RBC, are developed for the system with semi-active BS-HESS. 2. Structure and modelling of the system Three different models of the standalone PV system are constructed in MATLAB Simulink which are the system with battery-only system, passive BS-HESS and semi-active BS-HESS as illustrated in Fig. 1(a), 1(b), and 1(c), correspondingly. The general power equation of the system can be expressed as (1).

PPV + PESS

/ HESS

= Pload

(1)

where PPV is the power generation of PV, PESS/HESS is the power flow of energy storage system (PESS) or the power flow of hybrid energy storage system (PHESS), and Pload is the power demand of the load. In the system with batteryonly storage, PESS is the battery power (PBatt). For the system with BS-HESS, the PHESS is the combination of PBatt and supercapacitor power (Psc). The specification of the models are listed in Table 1.

Fig. 1. Simulink Models. (a) Standalone PV system with Battery-only Storage. (b) Standalone PV System with Passive BS-HESS. (c) Standalone PV system with Semi-Active BS-HESS. Table 1: Specification of the Simulink Models Standalone PV system with Battery-

Standalone PV System with

Standalone PV system with Semi-

only Storage.

Passive BS-HESS

Active BS-HESS

PV Array

2kW

2kW

2kW

Battery

48V 300Ah

48V 300Ah

48V 300Ah

Supercapacitor

-

60V 200F

45V 267F

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3. Control Strategy 3.1. Rule based controller (RBC) Fig. 2 illustrates a simple RBC control strategy based on the concept of dead-zone function. The Pb1 and Pb2 are the positive and negative battery power thresholds, respectively. K1 and K2 are the power-sharing ratio. In this study, the parameter of Pb1, Pb2, K1, and K2 are set as 265W, -265W, 1, and 1, respectively. When the power demand exceeds the battery power threshold 1 (PHESS > Pb1) or the battery power threshold 2 (PHESS > Pb2), the power mismatch between the PHESS and battery power threshold (Pb1 or Pb2) will be shared among the battery and supercapacitor with power sharing ratio of K1 or K2 accordingly. When the power demand is within the threshold Pb1 and Pb2 (Pb1 > PHESS > Pb2), the supercapacitor is not needed.

Fig. 2. RBC in Deadzone Function.

3.2. Moving average filter based controller Moving average filtering is an effective power smoothing control strategy that could remove fast transients in battery current and voltage. The algorithm would set to calculate the average value of the data in the buffer. When a new sampling data comes into a specific period, the first data saved in the buffer is overwritten by the new data, and then the moving average calculates the new average value. The moving average power, Pmvg, is expressed as (2). Pmvg =

1 T mvg

³

t

t + T mvg

PHESS dt

(2)

where Tmvg is the moving time window that is defined according to the frequency of the applied loading. In this control strategy, Tmvg is set as 120s. Pmvg is supplied by the battery in order to reduce the battery stress level and the power mismatch between the PHESS and Pmvg is met by supercapacitor. 4. Simulation Figs. 3(a), 3(b), and 3(c) show the actual 24-hours solar irradiation profile in The University of Nottingham Malaysia Campus on 25 April 2014, the daily load profile of a rural household, and the PV power output, respectively. The solar irradiation and load profile will be used in all the simulations. 5. Result and Discussion Figs. 4 and 5 show the battery current and supercapacitor current profiles of all the models. The information of the battery current of all the models is summarized in Table 2. The performance of the system such as smoothness of the battery current, battery peak current reduction, and average SOC of the battery need to be evaluated. The smoothness of battery current indicates the dynamic stress level of the battery. By reducing the peak current demand of the battery, the deep discharging of the battery can be avoided and the battery bank can be downsized. The average SOC of the battery is also can key factor for the system. Due to the limited energy capacity of SC, the

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improvement of average and final battery SOC might not be high but it indicates the amount of SC energy being transferred in different systems. (b) (b)Load LoadDemand Demand

Time (hour)

(c) (c)PV PVPower PowerOutput Output

Power (W)

Power (W)

Solar Irradiation (W/m2)

(a) (a)Solar SolarIrradiation IrradiationProfile Profile

Time (hour)

Time (hour)

Fig. 3. 24-hours Profiles. (a) Solar Irradiation Profile. (b) Load Demand (c) PV Power Output. (b) Passive

Current (A)

Current (A)

(a) Battery-only

Time (hour)

Time (hour)

(d) Semi-Active Moving Average

Current (A)

Current (A)

(c) Semi-Active RBC

Time (hour)

Time (hour)

Fig. 4. Battery Current. (a) Battery-only (b) Passive BS-HESS. (c) Semi-active BS-HESS (RBC). (d) Semi-active BS-HESS (Moving Average).

For system with battery-only storage, the battery always experiences highly fluctuating charging/discharging current and deep discharge. For system with passive HESS, Fig. 4(b) shows that the dynamic stress of the battery is slightly improved as compared to the battery-only system. Fig. 5(a) illustrates that the supercapacitor absorbs/supplies only a small portion of dynamic components of the power demand. Table 2 shows that the battery peak current reduction is not improved significantly and the improvement of average and final battery SOC are negative. This is because the supercapacitor absorbs some of the power from the battery as the supercapacitor in passive configuration is uncontrollable. For system with semi-active (RBC), Figs. 4(c) and 5(b) illustrate that the supercapacitor charges/discharges according to the pre-defined rules and battery peak current is reduced. The system has improved final SOC and average SOC of the battery by 0.39% and 0.033% respectively. Table 2 shows that it has the best performance in term of peak current reduction (8.607%) and the reduction of battery deep discharge as the strategy is designed to minimize the peak power demand of the battery. For system with semi-active (moving average), the strategy reduces the peak current of battery by 0.624%. Besides that, the final SOC and average SOC

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of the battery has improved by 0.058% and 0.022% respectively. The semi-active (moving average) is not as good as semi-active (RBC) in term of battery peak current reduction. Fig. 4(d) shows that the dynamic of battery current is smoothest among all models. Fig. 5(c) shows the supercapacitor is charging and discharging at a high frequency as it absorbs the fast transient component of the power demand. (b) Semi-Active RBC

(c) Semi-Active Moving Average

Current (A)

Current (A)

Current (A)

(a) Passive

Time (hour)

Time (hour)

Time (hour)

Fig. 5. Supercapacitor Current. (a) Passive BS-HESS. (b) Semi-active BS-HESS (RBC). (c) Semi-active BS-HESS (Moving Average). Table 2. Performance of Battery in Simulation Test Batt-Only

Passive

Semi-Active Moving Average

Semi-Active RBC

Peak Current

Current (A)

6.664

6.655

6.622

6.090

Final SOC

Reduction (%) SOC (%) Improvement (%)

76.702 -

0.137 76.693 -0.011

0.624 76.746 0.058

8.607 77.00 0.390

SOC (%) Improvement (%)

67.226 -

67.200 -0.039

67.241 0.022

67.248 0.033

Average SOC

6. Conclusion The BS-HESS shows the positive impact to the battery and the overall system. The passive BS-HESS is easy to be implemented, but the improvement is not significant as it cannot be controlled. Therefore, semi-active BS-HESS is a better configuration that improves the battery lifespan and maximizes the level of utilization of the supercapacitor. The system with semi-active BS-HESS (moving average filter) has significantly smoothened the battery current. The system with semi-active BS-HESS (RBC) shows a great capability in battery peak current reduction and the prevention of battery deep discharge by reducing the peak power demand by 8.607% and improving the average SOC of the battery by 0.34% as compared to the system with battery-only system. Acknowledgement This project is supported by Ministry of Science, Technology and Innovation (MOSTI) and The University of Nottingham Malaysia Campus. References [1] Kan SY, Verwaal M, and Broekhuizen H, The use of battery-capacitor combinations in photovoltaic powered products, J. Power Sources 2006, 162: 971–974. [2] Chong LW, Wong YW, Rajkumar RK, Rajkumar RK, and Isa D, Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems, Renew. Sustain. Energy Rev. 2016, 66, pp: 174–189. [3] Kuperman A and Aharon I, Battery-ultracapacitor hybrids for pulsed current loads: A review, Renew. Sustain. Energy Rev. 2011, 15: 981– 992. [4] Dougal RA, Liu S, and White RE, Power and life extension of battery-ultracapacitor hybrids, IEEE Trans. Components Packag. Technol 2002., 25: 120–131. [5] Kuperman A, Aharon I, Malki S, and Kara A, Design of a semiactive battery-ultracapacitor hybrid energy source, IEEE Trans. Power Electron.2013, 28: 806–815.