Power quality control strategy for grid-connected renewable energy sources using PV array and supercapacitor

Transcription

1 2010 International Conference Electrical Machines and Systems, Oct , 2010, Incheon, Korea Power quality control strategy for grid-connected renewable energy sources using PV array and supercapacitor Hyo-Ryong Seo, Gyeong-Hun Kim, Sang-Yong Kim, Namwon Kim, Hyo-Guen Lee, Chulsang Hwang, Minwon Park, and In-Keun Yu Department of Electrical Engineering, Changwon National University, Korea Abstract The output power from renewable energy sources fluctuates because of weather variations. This paper proposes an effective power quality control strategy of renewable energy sources connected to power system using photovoltaic (PV) array and supercapacitor. A supercapacitor is connected to the bus of PV power generation system for power quality control of the grid-connected renewable energy sources. The results of a powerhardware-in-the-loop simulation demonstrate the effectiveness of the proposed control method. The system not only enhances the reliability of renewable energy systems, but also improves the availability of PV systems. PV PV system Supercapacitor Energy storage system AC I. INTRODUCTION Renewable energy sources are regarded as an important alternative to traditional power generating sources. Enhanced public awareness of the environment has led to rapid wind power growth throughout the world to reduce greenhouse gas emissions associated with conventional energy generation [1]. Recently, the number of renewable energy power systems and their sizes are going to increase rapidly, simultaneous with their impact on the system. Fundamental disadvantage of renewable energy generations is the fluctuation of output power. The power fluctuation is a serious problem for power grid companies or transmission system owners. Power system frequency stability relies on the balance between the active power output of the generators and the active power consumed by the loads. Therefore, it is essential to mitigate the renewable energy power fluctuation up to a certain range. Different power backup strategies for renewable energy power systems have been proposed: gas units, pump storage units, batteries etc. [2]-[5]. For mitigating fluctuations, conventional batteries might be less suited since they cannot provide the necessary high number of charge cycles. Electrical and magnetic storage devices, such as supercapacitor and superconducting magnetic energy storage, can reduce fluctuations, and their capacity is rapidly increasing [6], [7]. New energy storage technology is energy capacitor system (ECS), which is composed of power electronic devices and supercapacitor. From the environmental viewpoint, it is a relatively clean source of energy as it does not contain any toxic material. It can be cycled millions of time, i.e., it has a virtually unlimited life cycle. Its standby loss is also very low. Therefore, ECS can effectively be used for renewable energy power application [8]-[14]. In this paper, a control method of a multi-source system including PV array and supercapacitor is proposed for Wind generator Fig. 1. Conceptual configuration of the model power system. smoothing the output power of grid-connected renewable energy sources. The proposed control strategy reduces the fluctuations of a grid-connected renewable power system and the effectiveness is confirmed through a power hardware-inthe-loop simulation (PHILS). The characteristic of real-pv module and supercapacitor is implemented in the PHILS. The system guarantees stable and cost-effective utilization of renewable energy sources. II. CONFIGURATION OF MODEL POWER SYSTEM Fig. 1 shows a conceptual configuration of a model power system. It consists of` a wind generator, a PV array, a supercapacitor bank, two - converters and a -AC inverter. The -AC inverter converts the power to AC and it changes its output for releasing or absorbing active power to or from the network. A. Wind Power Generator A MOD-2 turbine is used for the wind turbine model. The MOD-2 turbine is modeled using (1) Pwtb = ρcp ( λ) πr V (1) w 2 where P wtb is the wind turbine output [W], R is the radius of the blade [m], ρ is the air density [kg/m 3 ]. λ is the tip speed ratio, V w is the wind speed [m/s], and C P is the power coefficient. The rated capacity of the wind generator is 3 MW. 437

2 Fig. 2. Pitch control block diagram. Fig. 4. Schematic diagram of the proposed control system. Fig. 3. PV power generation system. In the pitch controller shown in Fig. 2, the output of the wind generator fluctuates when the wind speed is less than the rated speed (12.9 [m/s]), and this may cause fluctuation in the utility frequency. P WG is the wind turbine output and β is the blade pitch angle [deg]. B. PV Power Generation System A photovoltaic cell is a nonlinear device that can be represented as a current source model. Equation (2) gives the V-I characteristic equation of a solar cell. q ( V + I Rs ) I = Isc Id = Isc Ios exp 1 n κ T where I sc is the light generated current, I os is the diode reverse saturation current, q is the electronic charge, k is the Boltzmann constant, T is the temperature, V is the terminal voltage of the module, and R s is the series resistance. The V-P curve of PV characteristic has a maximum power point (MPP) which is the optimal operation point for efficient use of the PV array. It is necessary to extract the maximum power at any condition in order to minimize power loss from PV array. The rated capacity of the PV array in this work is 200 kw. The boost - converter with maximum power point tracking (MPPT) keeps the PV array voltage at a maximum operating point. The PV system is controlled by the perturbation and observation (P&O) method for MPPT [10]. Fig. 3 depicts the PV power generation system. C. Energy Storage System The energy storage device used in this study is a supercapacitor bank which has a large capacitance of 6.08 F. The rated supercapacitor bank voltage is 1.6 kv and the rated capacity is 1 MJ. A bi-directional - converter with charging and discharging control of supercapacitor has been operated for mitigating the fluctuations caused by weather variations. (2) III. CONTROL STRATEGY A schematic diagram of the proposed control system is shown in Fig. 4. The -AC voltage source inverter (VSI) controls the dc-link voltage and the reactive power output, whereas the real power output is controlled by the boost - converter for generating power from the PV array and the bi-directional - converter for charging/discharging power from the supercapacitor bank. The -AC inverter output P I is determined as follows: PI = PPV + PS (3) where P PV is the PV array output and P S is the supercapacitor output. The output power of PV array P PV is given by: PPV = VPVMPP + IPVMPP (4) where V PVMPP is the voltage of PV array and I PVMPP is the current of PV array at the maximum power point. The output power reference of supercapacitor P Sref is calculated using the following: P P P + S = WG+ PV WG PV (5) where P WG+PV is the sum of the wind generator and the PV array output. P WG+ PV is a moving average of the wind generator output and the PV array output over a time interval T, which is given by: 1 t WG+ PV WF + PV T t T P = P dτ (6) When the reference power of the supercapacitor P Sref is less than the supercapacitor output P S, the bi-directional - converter operates in the charging mode otherwise in the discharging mode. 438

3 Fig. 5. Energy storage system including supercapacitor bank. Fig. 7. Schematic diagram of the PHIL-based experiment. Fig. 6. Schematic diagram of -AC voltage source inverter. Fig. 5 describes the energy storage system including supercapacitor bank. Schematic diagram of -AC voltage source inverter is shown in Fig. 6. The controller of the inverter maintains the dc-link voltage as constant and provides or absorbs active power to/from the grid. IV. EXPERIMENT AND THE RESULTS A. PHILS configuration An experimental test has been implemented as illustrated in Fig. 7. The controller of the bi-directional - converter receives signals of the wind generator output power P WG through gigabit transceiver analogue output (GTAO) card and PV module output power P PV to compensate the fluctuation of renewable energy sources. Signals of the dc-link voltage and current is transferred to a real time digital simulator (RTDS) by gigabit transceiver analogue input (GTAI) card to generate power reference of the -AC VSI modeled in RTDS. Fig. 8 shows the photos of the PHILS-based experimental setup. Its hardware control was realized with the DSP of TMS320F2812. Experiments were carried out to validate the proposed control algorithm. The parameters of the PV module, the supercapacitor, and the - converter are shown in Table I, II, and III, respectively. Fig. 8. PHIL-based experimental setup. TABLE I THE PARAMETERS OF THE PV MODULE USED IN EXPERIMENT Rated Capacity 200 W Maximum Power Voltage V Maximum Power current 7.4 A Open-circuit Voltage V Short-circuit Current 8.30 A TABLE II THE PARAMETERS OF THE SUPERCAPACITOR USED IN EXPERIMENT Rated Capacitance 166 F Maximum Voltage 50.4 V Equivalence Series Resistance 7.2 mω Rated Current 150 A Ambient Temperature -40 ~ 65 C TABLE III THE PARAMETERS OF THE - CONVERTER USED IN EXPERIMENT Type Boost Bi-direction Rated Capacity 1 kw 7.5 kw Reactance (L1) 1 mh 3 mh Capacitance (C1) 8000 μf 8000 μf Controller TMS320F2812 TMS320F2812 Switching Frequency 20 khz 20 khz Switching Device IGBT IGBT 439

4 B. Experimental Results Fig. 9. Wind speed. Fig. 13. Photovoltaic module voltage and current. Fig. 10. Wind generator output power with/without supercapacitor. Fig. 14. Photovoltaic module output power in RTDS. Fig. 11. Supercapacitor voltage and current. Fig. 15. Wind generator and photovoltaic module output power with/without supercapacitor. Fig. 13 presents the PV module voltage and current controlled by MPPT. The PV module output power changed from 330 kw to 230 kw due to variation of irradiation at 38 sec, as illustrated in Fig. 14. The PHILS experimental result in Fig. 15 show that the proposed control algorithm is the effectiveness for the improving the power quality of gridconnected renewable energy sources Fig. 12. Supercapacitor output power in RTDS. Wind speed shown in Fig. 9 was applied for PHILS experiment. The output power of wind generator with and without supercapacitor is shown in Fig. 10. The response of the supercapacitor voltage and current during charge and discharge is shown in Fig. 11. Fig. 12 depicts the supercapacitor output power in RTDS to compensate the fluctuation of wind generator output power. V. CONCLUSIONS This paper proposes an effective power quality control strategy of renewable energy sources connected to power system using PV array and supercapacitor. Real time digital simulator (RTDS) and hardware based experiment was performed to confirm the effectiveness of the proposed control method under various weather conditions. The fluctuations due to wind speed and irradiation variations can be smoothed more effectively by the supercapacitor connected to the bus of PV power generation system. This system enhances the 440

5 reliability of renewable energy system and makes PV system more cost-effective. ACKNOWLEDGMENTS This work was supported by the Ministry of Education, Science and Technology (MEST), and the ETRI SoC Industry Promotion Center, Human Resource Development Project for IT SoC Architect. REFERENCES [1] R. Karki, P. Hu, and R. Billinton, A Simplified Wind Power Generation Model for Reliability Evaluation, IEEE Tran. Energy Conversion, Vol. 21, pp , June [2] E. Spahic and G. Balzer, Power Fluctuation from a Large Wind Farm, in Proc Future Power Systems Int. conf., pp [3] C. Luo, H. Banakar, B. Shen, and B. Ooi, Strategies to Smooth Wind Powr Fluctuations of Wind Turbine Generator, IEEE Tran. Energy Conversion, Vol. 22, No. 2, pp , June [4] X. Y. Wang, D. M. Vilathgamuwa, and S.S. Choi, Determination of Battery Storage Capacity in Energy Buffer for Wind Farm, IEEE Tran. Energy Conversion, Vol. 23, No. 3, pp , Sep [5] M. Lu, C. Chang, W. Lee, and L. Wang, Combining the Wind Power Generation System with Energy Storage Equipment, IEEE Tran. Industry Applications, Vol.45, No. 6, pp , Nov [6] H. Jung, A. Kim, J. Kim, M. Park, and I. Yu, A study on the operating characteristics of SMES for the dispersed power generation system, IEEE Trans. Appl. Superconductivity, Vol. 19, Issue 3, pp , [7] S. Nomura, Y. Ohata, T. Hagita, H. Tsutsui, S. Tsuji-Iio, and R. Shimada, Wind Farms Linked by SMES Systems, IEEE Tran. Applied Superconductivity, Vol. 15, No. 2, pp , June [8] C. Abbey and G. Joos, Supercapacitor Energy Storage for Wind Energy Applications, IEEE Tran. Industry Applications, Vol. 43, No. 3, pp , MAY/JUNE [9] M. Mufti, S. A. Lone, S. J. Iqbal, M. Ahmad, and M. Ismail, Supercapacitor based energy storage system for improved load frequency control, Electric Power System Research, Vol. 79, Issue 1, pp , Jan [10] S.M. Muyeen, R. Takahashi, T. Murata, and J. Tamura, Integration of an Energy Capacitor System with a Variable-Speed Wind Generator, IEEE Tran. Energy Conversion, Vol. 24, No. 3, pp , Sep [11] W. Li, G. Joos, and J. Belanger, Real-Time Simulation of a Wind Turbine Generator Coupled With a Battery Supercapacitor Energy Storage System, IEEE Tran. Industrial Electronics, Vol. 57, No. 4, pp , April [12] N. Kakimoto, H. Satoh, S. Takayama, and K. Nakamura, Ramp-Rate Control of Photovoltaic Generator with Electric Double-Layer Capacitor, IEEE Tran. Energy Conversion, Vol. 24, No. 2, pp , June [13] T. Kinjo, T. Senjyu, N. Urasaki, and H. Fujita, Output Levelling of Renewable Energy by Electric Double-Layer Capacitor Applied for Energy Storage System, IEEE Tran. Energy Conversion, Vol. 21, No. 1, March [14] N. kakimoto, S. Takayama, H. Satoh, and K. Nakamura, Power Modulation of Photovoltaic Generator for Frequency Control of Power System, IEEE Tran. Energy Conversion, Vol. 24, No. 4, pp , Dec [15] S. Kim, J. Jeon, C. Cho, E. Kim, and J. Ahn, Modeling and simulation of a grid-connected PV generation system for electromagnetic transient analysis, Solar Energy, Vol. 83, pp ,