Performance Improvement and Analysis of Stand- Alone Hybrid Wind /Battery/DG Power Generation System

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1 Performance Improvement and Analysis of Stand- Alone Hybrid Wind /Battery/DG Power Generation System 1 I. Hussain and 2 H. Ashfaq 1, 2 Department of Electrical Engineering, Jamia Millia Islamia(Central University), New Delhi, INDIA 1 ikhlaqb@gmail.com, 2 harun_ash@yahoo.com Abstract This paper presents a standalone hybrid power generation system based on low speed wind energy conversion system (WECS) using a variable speed permanent magnet synchronous generator (PMSG) with battery storage and diesel generator (DG). Different types of power management strategies are presents for minimal use of DG. For each PMS, mathematical model is developed based on the power balance (between the supply side and the load side), the battery bank charging/discharging limits (upper and lower energy limits) and the sizing of system elements. The topology for the same with different PMS has been verified using MATLAB Simulink based simulations. Keywords Wind energy conversion system, Permanent magnet synchronous generator, Isolated system, FFT analysis, DG. I. INTRODUCTION Stand-alone hybrid systems have turned into one of the most promising ways to handle the electrification requirements of numerous isolated consumers worldwide. Wind power can be used in off-grid systems, also called stand-alone hybrid systems with DG, not connected to an electric distribution system or grid. For isolated settlements located far from a utility grid, one practical approach to self-sufficient power generation involves using a wind turbine with battery and DG to create a stand-alone system. If wind conditions are favourable, these stand-alone wind energy systems usually can provide communities with electricity at the lowest cost and minimal use of DG [1-2]. Power quality is very important for such system as it is variable in nature in every time of instant Standalone hybrid systems often include batteries, because the available wind does not always produce the required quantities of power. If wind power exceeds the load demand, the surplus can be stored in the batteries[3-11]. For assessing the type of generator in WECS, criteria such as operational characteristics, weight of active materials, price, maintenance aspects and the appropriate type of power electronic converter are used[12]. The induction generator based on Squirrel-Cage rotor (SCIG) is a very popular machine because of its low price, mechanical simplicity, robust structure, and resistance against disturbance and vibration. Although wound rotor induction generator has the advantage described above, it is more expensive than a squirrel-cage rotor [13-14]. For small generation systems PMSG based WECS are preferred over induction generator based systems due to their high power factor, higher efficiency, and higher energy yield, improvement in the thermal characteristics, higher reliability and lighter [15-17]. In this paper a PMSG based hybrid wind/battery/dg is modelled and simulated. The best sizing of the system according to the load demand and energy availability is done. Also for satisfactory operation, several power management strategies (PMS) are developed so that minimal use of DG is used and verified using MATLAB simulations. For each PMS, mathematical model is developed based on the power balance (between the supply side and the load side), the battery bank charging/discharging limits (upper and lower energy limits) and the sizing of system elements. II. SYSTEM DESCRIPTION Figure 1: Block diagram of proposed system. Hybrid system consist of wind turbine (10kW), PMSG (50Hz, 3000rpm, 400V), Converter system, DG(8.1kVA, 1500rpm, 400V) (Backup), Storage Battery bank with Bidirectional converter and load(3kw) are used. To apply the power management techniques easily, all quantities of the energy sources, the storage device and the load are referred into the AC-bus by taking the losses associated with the power conversion and storage devices into consideration. The following circuit (Figure 2) shows a simple electrical circuit model for the block diagram represented by a controllable current source at the main AC-bus. The powers from the sources can be used directly or via the battery. 847

2 schemes are devised based on its energy content. This led to minimal use of DG. Figure 3 shows main flow chart for the standalone wind system Figure 2: Simple electrical circuit model for block diagram. III. MODELLING AND PMS For the above simple model (2), mathematical modelling is performed based on power or current control mechanism to check the balance of the instantaneous power or current between the supply side and the load side at the main AC-bus. The power balancing plays a big role in the control system of the hybrid power systems. For power balancing at the AC-bus, we have the fundamental mathematical model expressed as: P load (t) = P wg (t) + P dg (t) + P bb (t) (1) Where, P wg (t), P dg (t) and P bb (t) are the injected power into the AC bus from the wind generator system, diesel generator system and battery bank system respectively. P load (t) = load demand The different PMS proposed and validated for this system are: a. Wind generators partly supplying the load and partly charging the Battery bank. b. Hybrid wind generators/ DG supplying the load. c. Wind generators partly supplying the load and partly dump load (battery fully charged). A. Wind generators partly supplying the load and partly charging the Battery bank: With this operating mode, the wind generators are the only energy sources for the system. They provide the power demand of the load and charging the battery bank. The DG is not contributing any power with this PMS. 1. Mathematical modelling of wind generator partly supplying the load and partly charging the battery bank: By taking the power balance, the mathematical modelling, can be given as P wg (t) = P load (t) & E bmin E b (t) E bmax. (2) The battery can only charge or discharge between the maximum (E max ) and minimum (E min ) energy capacity limits (State of Charges) depending on the load demand and supplies. To control the charging and discharging of the battery within the limits, a Charging/Discharging Control Figure 3: Main flow chart At times when the supply power is greater than the demand, part of the supply power will charge the battery bank and this charging power can be determined as: P char (t) = P wg (t) - P load (t) & E b (t) E bpeak (3) Where E bpeak is peak energy capacity Thus, the energy stored in the battery bank(e stor (t) ) when it is charging is defined by: E stor (t) = P stor (t) dt & (4) E b (t) = E b_init (t) - P stor (t) dt (5) Where E b_init (t) is the Initial energy of the battery When the demand power exceeds the supply, the battery supplying the load and that part of the power contribution from the battery bank is: P bb (t) = P load (t) (P wg (t) & E b (t) E bpeak (6) Thus, the energy supplied from the battery bank (E disch (t) )while it is discharging can be expressed as: E disch (t) = P bb (t) dt & (7) E b (t) = E b_init (t) - P bb (t) dt (8) 2. Sizing of system elements: The preliminary sizing approach of the battery bank is given here by Eq-(9), can be applied with the first insight to the problem. BC = (E daily_load_demand /η b )*DOA/DOD (Wh) (9) 848

Where, E daily_load_demand is the total daily energy demand, BC= battery capacity, DOA= days of autonomous, DOD = depth of discharge, η b is the battery efficiency From the cyclic energy shape of the

3 Where, E daily_load_demand is the total daily energy demand, BC= battery capacity, DOA= days of autonomous, DOD = depth of discharge, η b is the battery efficiency From the cyclic energy shape of the battery bank which is based on its preliminary sizing, the battery bank is then resized to the maximum energy storing capacity for this PMS. While sizing the renewable energy resources (RESs), the energy balance approach can be used: N wg E wg = E daily_load (10) Where N wg is the number of wind generators and E wg is the total energy of wind generator. The number of wind generators (N wg ) can be determined by: N wg = ( P load (t) dt / P wg (t) dt (11) The maximum power capacities of Wind generators are, then, determined by multiplying the number of Wind turbines with the Watt-peak capacities of a selected Wind turbine. B. Hybrid wind generators/ DG supplying the load. With this operating mode, the wind generators with DG are the energy sources for the system. They provide the power demand of the load. The battery bank is not contributing any power with this PMS. 1. Mathematical modelling of hybrid wind/dg supplying the load By taking the power balance, the mathematical modelling, can be given as P wg (t) + P dg (t) = P load (t), P bb (t) = 0 (12) The mathematical equation for the design of Genset control can be devised as: P dg (t) = P load (t), 0 P load (t) P load_peak, = P dg_peak, P load (t) P load_peak = 0, otherwise (13) 2. Sizing of system elements: Sizing of the generator basically depends on the peak power of the load for which the generator should be capable of supplying it. Thus, the Genset sizing is defined as: there are losses during the conversion which must be taken into account. The losses associated with the DG. Similarly, there are losses with the AC/DC & DC/AC converters when the PMS is applied at the AC-bus. Therefore, the governing power& energy equation and the loss equations are used while designing the Simulink models of the PMSs. C. Wind generators partly supplying the load and partly dump load (battery fully charged). With this operating mode, the wind generators are the only energy sources for the system. They provide the power demand of the load and partly dump load. The DG is not contributing any power with this PMS. 1. Mathematical modelling of wind generator partly supplying the load and partly supplying the dump load By taking the power balance, the mathematical modelling, can be given as P wg (t) = P load (t) + P dump (t) & E b (t) = E bmax. (16) Where P dump (t) = dump load 2. Sizing of system elements The number of wind generators (N wg ) can be determined by: N wg = ( P load (t) dt / P wg (t) dt (17) The maximum power capacities of Wind generators are, then, determined by multiplying the number of Wind turbines with the Watt-peak capacities of a selected Wind turbine. IV. SIMULATION AND RESULTS The proposed system is modelled and simulated using MATLAB/Simulink environment for change in wind speed. P dg_peak = P load_peak (14) The number of wind generators (N wg ) can be determined by: N wg = P load (t) dt / P wg (t) dt (15) When the powers corresponding to each system sources are referred to the AC-bus where the PMSs are applied, Figure 4: Simulink model of hybrid system. 849

Figure 5: Three phase voltage, current, voltage fundamental positive sequence and 5 th harmonic negative sequence waveform of power quality analyzer1(at load) of WECS with variable wind supplying

e THD (bar relative to fundamental) of Vab load of variable wind system Figure 9: Three phase voltage, current, voltage fundamental positive sequence and 5 th harmonic negative sequence waveform of

4 Figure 5: Three phase voltage, current, voltage fundamental positive sequence and 5 th harmonic negative sequence waveform of power quality analyzer1(at load) of WECS with variable wind supplying RLload Figure 8: Display selected signal and FFT Analysis i.e THD (bar relative to fundamental) of Vab load of variable wind system Figure 9: Three phase voltage, current, voltage fundamental positive sequence and 5 th harmonic negative sequence waveform of power quality analyzer1(at load) of WECS/battery bank supplying RL-Load. Figure 6: V dc, V ab inverter, Vab load and modulation index of Wind system with variable wind supplying RL-load. Figure 7: Display selected signal and FFT Analysis i.e THD (bar relative to fundamental) of Vab inverter of variable wind system. Figure 10: V dc, V ab inverter, Vab load and modulation index of Wind system/battery bank supplying the RL-Load. 850

sequence is small. The simulated results validate the proposed topology. APPENDIX Table 1: Wind turbine parameters. S.NO. PARAMETER RATING 1 NOMINAL MECHANICAL POWER 10 kw 2 ROTOR DIAMETER 6.

5 sequence is small. The simulated results validate the proposed topology. APPENDIX Table 1: Wind turbine parameters. S.NO. PARAMETER RATING 1 NOMINAL MECHANICAL POWER 10 kw 2 ROTOR DIAMETER 6.2m Figure 11: Display selected signal and FFT Analysis i.e THD (bar relative to fundamental) of Vab load of wind/battery system 3 NO. OF BLADES 3 4 BLADE PROFILE NLF BLADE PITCH ROTOR AXIS ANGLE CUT IN WIND SPEED 3 m/s 8 BASE WIND SPEED 5 m/s 9 BASE POWER OF THE ELECTRICAL GENERATOR (kw) 10/ MAXIMUM POWER AT BASE WIND SPEED ( p.u. OF NOMINAL MACHANICAL POWER 0.73 p.u. Figure 12: Three phase voltage, current, voltage fundamental positive sequence and 5 th harmonic negative sequence waveform of power quality analyzer of hybrid wind/dg system supplying RL-Load. Figures 7 and 8 shows total harmonic distortion in Vab inverter, Vab load are 68.74% and 2.89% (using FFT analysis) in wind power generation system supplying RLload. Figure 11 shows total harmonic distortion in Vab load is 5.45% (using FFT analysis) in wind/battery power generation system supplying RL-load. V. CONCLUSION In this paper, an isolated hybrid power generation system which consists of wind turbines with storage battery and DG is modelled and simulated with different power management strategies. The sizing of the system according to the load demand and energy availability is done. Also for satisfactory operation, several power management strategies (PMS) are developed so that minimal use of DG is used and verified using MATLAB simulations. The total harmonic distortion in Vab load is 2.89% and 5.45% (using FFT analysis) in variable wind power generation system and wind/battery system respectively supplying RL-load. The voltage 5 th harmonic negative 11 BASE ROTATIONAL SPEED 1.2 Table 2: PMSG parameters S.NO. PARAMETER RATING 1 SPEED 3000 RPM 2 FREQUENCY 50 Hz 3 POLE PAIR 4 4 VOLTAGE 400 V 5 MECHANICAL TORQUE 27.3 Nm 6 TORQUE (CONSTANT) STATOR RESISTANCE 0.11 ohm 851

6 8 DIRECT INDUCTANCE H 9 QUDRATURE INDUCTANCE ( Lq) H 10 INERTIA Kgm 2 11 FRICTION FACTOR N.m.s Table 3: Synchronous generator parameters for DG system S.NO. PARAMETER RATING 1 POWER 8.1 kva 2 FREQUENCY 50 Hz 3 VOLTAGE 400 V 4 SPEED 1500 RPM 5 Rs ohm 6 Xd 1.8 ohm 7 Xd ohm 8 Xd ohm 9 Xq ohm 10 Xq X l REFERENCES [1] B. H. Khan, 2009, Non-Conventional Energy Resources, Tata McGraw-Hill Pub.Co [2] L. A. S. Ribeiro, et al., 2011, Isolated Micro-Grid with renewable hybrid generation: the case of Lencois Island, IEEE Transactions on Sustainable Energy, Vol. 2, no. 1, pp. 1-11, January [3] C. D. Dumitru and A. Gligo, 2010, Modeling and simulation of renewable hybrid power system using MATlab simulink environment, Scientific Bulletin of the Petru Major University of Targu Mures Vol. 7 (XXIV), No. 2, 2010, pp 5-9. [4] C. Liu, K.T. Chau and X. Zhang, 2010, An Effient Wind-Photovoltaic Hybrid Generation System Using Doubly Eecited Permanent-Magnet Brushless Machine, IEEE Transactions on Industrial Electronics, VOL. 57, NO. 3, March [5] J. K. Kaldellis, 2007, An integrated model for performance simulation of hybrid wind-diesel systems, Science Direct, Renewable Energy, 2007, pp, [6] Ahmed, E. Kalas, H. Medhat, S. Elfar and M. Sharaf, 2010, Simulation of a proposed maximum power extraction scheme for small wind turbine systems, MEPCON, December 19-21, 2010, pp, [7] J. F. Manwell and J.G. Mcgwan, 1993, Lead acid battery storage model for hybrid energy systems, solar energy vol.50, No. 5, pp , [8] M.K. Deshmukh and S.S. Deshmukh, 2008, Modeling of hybrid renewable energy systems, Renewable and Sustainable Energy Reviews 12, 2008, [9] O.C. Onar, M. Uzunoglu and M.S. Alam, 2006, "Dynamic modeling, design and simulation of a wind/fuel cell/ultra-capacitor-based hybrid power generation system," Journal of Power Sources- Science Direct, vol. 161, pp , 28th March [10] E. Muljadi and J.T. Bialasiewicz, 2003, "Hybrid Power System with a Controlled Energy Storage," in 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat No 03CH37468) IECON-03. vol. 2 Roanoke, Virginia, 2-6 November 2003, pp , ISBN: [11] Electropaedia, "Battery and Energy Technologies - Performance Characteristics by Ragone Plots," performance.htm. [12] F. Blaabjerg, Z. Chen, R. Teodorescu and F. Lov, 2006, Power electronics in wind turbine systems, IPEMC [13] A.G. Abo-Khalil, 2011, A new wind turbine simulator using a squirrel cage motor for wind power generation systems, IEEE PEDS 2011, Singapore, 5-8 December 2011, page no [14] M. Sasikumar and C. S. Pandian, 2010, Performance characteristics of self-excited induction generator fed current source inverter for wind energy conversion applications, International journal of computer and electrical engineering, Vol. 2, No. 6, December, 2010,pp, [15] M. Hilmy, M. E. Ahmed, M. Orabi and M. E. Nemr, 2010, Modeling and control of direct drive variable speed stand-alone wind energy conversion systems, MEPCON, Decemder 19-21, 2010, pp, [16] K. H. Dempewolf and B. Ponick, 2007, Modelling of permanent synchronous machines for simulations of transient phenomena, Power Electronics and Applications, 2007 European Conference on 2-5 Sept Page no [17] R. Melício, V.M.F. Mendes and J.P.S. Catalão, 2010, Modelling, Control and Simulation of Wind Turbines with Permanent Magnet Synchronous Generator and 852

7 Full-Power Converters, International Review of Electrical Engineering- IREE. 2010; 5 (2): Part A. BIOGRAPHIES Ikhlaq Hussain was born in Doda in the J&K, India, on May 1, He received the B.E. degree in Electrical Engineering from Jammu University, Jammu, India, in 2009 and M.Tech in electrical power system management from the Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, in He is currently working as contractual Lecturer in the Department of Electrical Engineering, NIT, Srinagar. His research interests include renewable energy, hybrid system, and power system management. Haroon Ashfaq was born in Aligarh, India, on January 17, He received the B.Tech, M.Tech. and Ph.D. degrees in Electrical Engineering from AMU, Aligarh, India. He is currently working as Assistant Professor in the Department of Electrical Engineering, Jamia Millia Islamia, New Delhi. His research interests include renewable energy, hybrid system, electric drives, switch gear and protection. 853

Dynamic Behaviour of Asynchronous Generator In Stand-Alone Mode Under Load Perturbation Using MATLAB/SIMULINK

International Journal Of Engineering Research And Development e-issn: 2278-067X, p-issn: 2278-800X, www.ijerd.com Volume 14, Issue 1 (January 2018), PP.59-63 Dynamic Behaviour of Asynchronous Generator