Table of Contents Author Guidelines Submit a Manuscript
International Journal of Photoenergy
Volume 2016, Article ID 7134904, 6 pages
http://dx.doi.org/10.1155/2016/7134904
Research Article

Design and Experimental Results of Battery Charging System for Microgrid System

Division of Electrical, Electronics and Control Engineering, Kongju National University, Chungcheongnam-do, Republic of Korea

Received 26 July 2016; Accepted 11 October 2016

Academic Editor: Santolo Meo

Copyright © 2016 Byunggyu Yu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Nowadays, many countries have paid attention to renewable energy due to fossil fuel crisis and its related environmental pollution. In particular, following the government supply business for renewable energy industry, the private sectors drive the stable power supply by using renewable sources for both microgrid system and standalone application. Battery charging and discharging control system of microgrid system are critical to extend lifetime of standalone photovoltaic system. Corresponding to this demand, this paper presents the development of battery charging and discharging system based on battery modeling, SOC (state of charge) estimation, and its implementation for 5 kW. As a result, the conversion efficiency shows 96.35% with over 95% charging performance.

1. Introduction

A microgrid system is defined as an autonomous energy grid system to operate in parallel with or independently of the traditional grid [1, 2]. In accordance with the growing industry trend on renewable energy, microgrid systems integrated with renewable energy resources are becoming widespread in the world [35]. This type of microgrid system consisted of several renewable energy resources like photovoltaic generation and a battery backup system like lead-acid battery system [68]. In particular, battery system is the key component to stabilize the microgrid system as a concrete grid voltage function. Typically, lead-acid battery is mostly used for storage system, but it has relative short lifetime for a stable operation. Thus, the battery charging and discharging system are regarded as one of the most essential systems for the long lifetime operation [912]. The battery systems for both microgrid system and standalone PV generation are different from the conventional system for UPS (uninterruptable power supply), because the charging and discharging profiles are depending on the environmental condition like irradiance. Corresponding to this demand, this paper presents the development of battery charging and discharging system based on battery modeling, SOC (state of charge) estimation, and its implementation.

This paper consisted of three sections. Firstly, the modelling of battery and battery charger/discharger is presented. Secondly, based on the modeling, the simulation of the target system is conducted with topology design for 5 kW. Lastly, with the proposed control algorithm, the final system output is implemented to verify the proposed algorithm and hardware.

2. Battery Modeling

It is required to have appropriate battery modeling to implement a battery charging and discharging system. Typically, this modeling can be classified into three categories. One is an electrochemical modeling, and it is too complicated to apply even though it shows the highest accuracy [13]. The second one is a mathematical modeling and it is acceptable to apply under some limited condition [14]. The third one is based on the electrical modeling by using voltage source, resistor, and capacity and it is practical for battery charging system implementation. In particular, this paper uses the electrical modeling for battery as in Figure 1. In order to model battery electrical characteristic, it is assumed that SOC function is used to improve the modeling accuracy as the following equation:where Ah_rate is the battery rating and Ah_init is the initial battery charging state.

Figure 1: Battery electrical modeling.

3. System Configuration

Battery system is installed to regulate the DC bus among PV generation, wind turbine, and local loads in Figure 2. Specifically, the battery charger is implemented by using 5 kW bidirectional buck-boost converter. As shown in Figure 3, the operating mode between charging mode and discharging mode is determined by monitoring DC bus voltage and current. In other words, when it is the charging mode, the charger is operated as buck converter. While it is the other mode, the charger is operated as the boost converter.

Figure 2: Standalone micropower grid configuration.
Figure 3: Battery charger system diagram.
3.1. Buck Converter for Charging Mode

Buck converter is called a step-down converter, at which the input voltage magnitude is decreased from the output voltage by the on/off control of switch (Figure 4(a)). When the switch is on during , where the switching duty ratio is and the switching period is designated as , the inductor voltage is determined by the following equation. During the short switching period , both and are assumed as constant values.

Figure 4: Battery charger operational circuit diagram. (a) Buck converter for charging mode; (b) boost converter for discharging mode.

When the switch is off during , the inductor voltage is determined by the following equation.

Under the steady state condition for the continuous current control, the net inductor current change during one switching cycle is equal to zero as following equation.

Thus, the output voltage is equal to .

Since the average capacitor () current is equal to zero at the steady state, the average inductor current should be equal to the load current. is representing the load resistance for the 5 kW battery charger converter. Since the nominal battery bank voltage is 240 V, the nominal load resistance can be calculated by the power definition. This is because the load current through is limited by the controller. Thus, is used for the converter design. Thus,

The maximum inductor current and the minimum inductor current can be calculated from the inductor average current and the net inductor current change.

For the continuous current mode of inductor current, the minimum inductor current should be more than zero. Thus, the minimum inductance can be calculated from the fixed switching frequency .

From the designed switching 12 kHz and 5 kW converter power capacity, the minimum inductance can be calculated by 877 uH.

For the capacitance design, the capacitance can be calculated by the designed voltage ripple ratio.

When the current variation is 40% and the ripple voltage is designed as 1 V, the designed capacitance can be designed as 87.5 uF.

3.2. Boost Converter for Discharging Mode

Boost converter is called a step-up converter, at which the input voltage magnitude is decreased from the output voltage by the on/off control of switch (Figure 4(b)). When the switch is on during , where the switching duty ratio is and the switching period is designated as , the inductor voltage is determined by the following equation.

When the switch is off during , the inductor voltage is determined by the following equation.

Under the steady state condition for the continuous current control, the net inductor current change during one switching cycle is equal to zero as following equation.

Thus, the output voltage is equal to .

Since the average capacitor () current is equal to zero at the steady state, the average inductor current should be equal to the load current. Thus,

The maximum inductor current and the minimum inductor current can be calculated from the inductor average current and the net inductor current change.

For the continuous current mode of inductor current, the minimum inductor current should be more than zero. Thus, the minimum inductance can be calculated from the fixed switching frequency .

From the designed switching 12 kHz and 5 kW converter power capacity, the minimum inductance can be calculated by 884 uH.

For the capacitance design, the capacitance can be calculated by the designed voltage ripple ratio.

When the ripple voltage is designed as 1 V, the designed capacitance from (8) can be designed as 400 uF.

4. Experimental Results

The proposed battery charging system was implemented by using buck converter as designed in the previous section. The electrical specification is listed in Table 1. Figure 5 shows the implemented system front-view.

Table 1: Electrical specification.
Figure 5: System hardware front-view picture.

Figure 6 shows the experimental waveforms for both CC and CV modes. DC link voltage is implemented by DC power supply and batteries are stacked to generate 240 V. Buck-boost converter is implemented for battery charging operation. The charging current is designed as 3 A, while the maximum charging current is limited as 10 A, and the temperature is controlled to be less than 50°C. When the battery voltage reaches the nominal battery voltage, the charging mode moves from constant current (CC) mode to constant voltage (CV) mode as shown in Figure 6. As a result, SOC as a charging performance index, is estimated over 95% with 96.35 conversion efficiency.

Figure 6: Experimental result for battery charging performance. (a) CC mode; (b) CV mode.

5. Conclusion

This paper presents the development of battery charging and discharging system based on battery modeling, SOC estimation, and its implementation. As a result, the conversion efficiency shows 96.35% with over 95% charging performance. Based on the presented design and experimental results for battery charging system, the battery backup system can be expected to be of high efficiency with long lifetime.

Competing Interests

The author declares no competing interests.

Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea Government (MSIP) (no. 2016R1C1B1007001).

References

  1. O. Deblecker, C. Stevanoni, and F. Vallee, “Cooperative control of multi-functional inverters for renewable energy integration and power quality compensation in micro-grids,” in Proceedings of the International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM '16), pp. 1051–1058, Capri, Italy, June 2016. View at Publisher · View at Google Scholar
  2. F. Ornelas-Tellez, “Optimal control for a renewable-energy-based micro-grid,” in Proceedings of the IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC '14), pp. 1–6, November 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Dong, F. Gao, X. Guan, Q. Zhai, and J. Wu, “Storage-reserve sizing with qualified reliability for connected high renewable penetration micro-grid,” IEEE Transactions on Sustainable Energy, vol. 7, no. 2, pp. 732–743, 2016. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Chen and S. Mei, “An integrated control and protection system for photovoltaic microgrids,” CSEE Journal of Power and Energy Systems, vol. 1, no. 1, pp. 36–42, 2015. View at Publisher · View at Google Scholar
  5. T. Strasser, F. Andrén, J. Kathan et al., “A review of architectures and concepts for intelligence in future electric energy systems,” IEEE Transactions on Industrial Electronics, vol. 62, no. 4, pp. 2424–2438, 2015. View at Publisher · View at Google Scholar · View at Scopus
  6. N. Fernanders, R. Demonti, J. Andrade et al., “Control strategy for pulsed lead acid battery charger for stand alone photovoltaics,” in Proceedings of the IEEE 13th Brazilian Power Electronics Conference and 1st Southern Power Electronics Conference (COBEP/SPEC '15), pp. 1–6, Fortaleza, Brazil, December 2015. View at Publisher · View at Google Scholar
  7. Y.-D. Lee, S.-Y. Park, and S.-B. Han, “Online embedded impedance measurement using high-power battery charger,” IEEE Transactions on Industry Applications, vol. 51, no. 1, pp. 498–508, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Ryu, D. Jung, J. Baek, and H. Kim, “An optimized design of bi-directional dual active bridge converter for low voltage battery charger,” in Proceedings of the 16th International Power Electronics and Motion Control Conference and Exposition (PEMC '14), pp. 177–183, September 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. R. K. Singh and S. Mishra, “A digital optimal battery charger with the inbuilt fault detection property,” in Proceedings of the IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES '12), pp. 1–6, IEEE, Bengaluru, India, December 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. Y.-L. Ke, Y.-C. Chuang, M.-S. Kang, Y.-K. Wu, C.-M. Lai, and C.-C. Yu, “Solar power battery charger with a parallel-load resonant converter,” in Proceedings of the 2011 46th IEEE Industry Applications Society Annual Meeting (IAS '11), pp. 1–8, Orlando, Fla, USA, October 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. J.-H. Lee, J.-S. Moon, Y.-S. Lee, Y.-R. Kim, and C.-Y. Won, “Fast charging technique for EV battery charger using three-phase AC-DC boost converter,” in Proceedings of the 37th Annual Conference of the IEEE Industrial Electronics Society (IECON '11), pp. 4577–4582, Melbourne, Australia, November 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. I.-S. Kim, P.-S. Ji, U.-D. Han, C.-G. Lhee, and H.-G. Kim, “State estimator design for solar battery charger,” in Proceedings of the IEEE International Conference on Industrial Technology (ICIT '09), pp. 1–6, February 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. X. Li, M. Xiao, K. Malinowski, and S.-Y. Choe, “State-of-charge (SOC) estimation based on reduced order of electrochemical model for a pouch type high power Li-polymer battery,” in Proceedings of the 7th IEEE Vehicle Power and Propulsion Conference (VPPC '11), pp. 1–6, Chicago, Ill, USA, September 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. S. Li and B. Ke, “Study of battery modeling using mathematical and circuit oriented approaches,” in Proceedings of the IEEE Power and Energy Society General Meeting, pp. 1–8, Detroit, Mich, USA, July 2011. View at Publisher · View at Google Scholar