A STATCOM-Control Scheme for Grid Connected Wind Energy System for Power Quality Improvement

ABSTRACT:

Injection of the wind power into an electric grid affects the power quality. The performance of the wind turbine and thereby power quality are determined on the basis of measurements and the norms followed according to the guideline specified in International Electro-technical Commission standard, IEC-61400. The influence of the wind turbine in the grid system concerning the power quality measurements are-the active power, reactive power, variation of voltage, flicker, harmonics, and electrical behavior of switching operation and these are measured according to national/international guidelines. The paper study demonstrates the power quality problem due to installation of wind turbine with the grid. In this proposed scheme STATic COMpensator (STATCOM) is connected at a point of common coupling with a battery energy storage system (BESS) to mitigate the power quality issues.

The battery energy storage is integrated to sustain the real power source under fluctuating wind power. The STATCOM control scheme for the grid connected wind energy generation system for power quality improvement is simulated using MATLAB/SIMULINK in power system block set. The effectiveness of the proposed scheme relives the main supply source from the reactive power demand of the load and the induction generator. The development of the grid co-ordination rule and the scheme for improvement in power quality norms as per IEC-standard on the grid has been presented.

KEYWORDS:

1.      International electro-technical commission (IEC)

2.      power quality

3.       wind generating system (WGS)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

                                 Fig.1.System operational scheme in grid system

CONCLUSION:

The paper presents the STATCOM-based control scheme for power quality improvement in grid connected wind generating system and with non linear load. The power quality issues and its consequences on the consumer and electric utility are presented. The operation of the control system developed for the STATCOM-BESS in MATLAB/SIMULINK for maintaining the power quality is simulated. It has a capability to cancel out the harmonic parts of the load current. It maintains the source voltage and current in-phase and support the reactive power demand for the wind generator and load at PCC in the grid system, thus it gives an opportunity to enhance the utilization factor of transmission line. The integrated wind generation and STATCOM with BESS have shown the outstanding performance. Thus the proposed scheme in the grid connected system fulfills the power quality norms as per the IEC standard 61400-21.

 REFERENCES:

[1] A. Sannino, “Global power systems for sustainable development,” in IEEE General Meeting, Denver, CO, Jun. 2004.

[2] K. S. Hook, Y. Liu, and S. Atcitty, “Mitigation of the wind generation integration related power quality issues by energy storage,” EPQU J., vol. XII, no. 2, 2006.

[3] R. Billinton and Y. Gao, “Energy conversion system models for adequacy assessment of generating systems incorporating wind energy,” IEEE Trans. on E. Conv., vol. 23, no. 1, pp. 163–169, 2008, Multistate.

[4] Wind Turbine Generating System—Part 21, International standard-IEC 61400-21, 2001.

[5] J. Manel, “Power electronic system for grid integration of renewable energy source: A survey,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1002–1014, 2006, Carrasco. 

High Performance of Space Vector Modulation Direct Torque Control SVM-DTC Based on Amplitude Voltage and Stator Flux Angle

High Performance of Space Vector Modulation Direct Torque Control SVM-DTC Based on Amplitude Voltage and Stator Flux Angle

ABSTRACT:

 Various aspects related to controlling induction motor are investigated. Direct torque control is an original high performance control strategy in the field of AC drive. In this proposed method, the control system is based on Space Vector Modulation (SVM), amplitude of voltage in direct- quadrature reference frame (d-q reference) and angle of stator flux. Amplitude of stator voltage is controlled by PI torque and PI flux controller. The stator flux angle is adjusted by rotor angular frequency and slip angular frequency. Then, the reference torque and the estimated torque is applied to the input of PI torque controller and the control quadrature axis voltage is determined. The control d-axis voltage is determined from the flux calculator. These q and d axis voltage are converted into amplitude voltage. By applying polar to Cartesian on amplitude voltage and stator flux angle, direct voltage and quadratures voltage are generated. The reference stator voltages in d-q are calculated based on forcing the stator voltage error to zero at next sampling period. By applying inverse park transformation on d-q voltages, the stator voltages in α and β frame are generated and apply to SVM. From the output of SVM, the motor control signal is generated and the speed of the induction motor regulated toward the rated speed. The simulation Results have demonstrated exceptional performance in steady and transient states and shows that decrease of torque and flux ripples is achieved in a complete speed range.

KEYWORDS:

1. Amplitude voltage

2. Direct Torque Control (DTC)

3. Space Vector Modulation (SVM)

4. Stator flux angle

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1: DTC-SVM scheme

Fig. 2: Simulation of proposed SVM-DTC

CONCLUSION:

This proposed method describes the performance of Direct Torque Control (DTC) based on space vector modulation, amplitude voltage and stator flux angle. In this system, hysteresis controller is substituted with PI torque controller and PI flux controller while switching table is replaced by SVM in order to improve the performance of this system especially at low speed, SVM is based on amplitude voltage and stator flux angle. The stator flux angle is controlled by PI torque controller and stator angular frequency and this gives a high accuracy for the value of the angle due to presence of PI torque controller. The amplitude voltage is controlled by PI torque and PI flux controller. This proposed method shows a reduction ability of flux and torque ripple with constant switching frequency and fast response of speed .This control technique can be done practically by using Digital Signal Processing (DSP) board.

REFERENCES:

1. Brahim, M., T. Farid, A. Ahmed, T. Nabil and R. Toufik, 2011. A new fuzzy direct torque control strategy for induction machine based on indirect matrix converter. Int. J. Res. Rev. Comput. Eng., 1: 18-22.

2. Buja, G., D. Casadei and G. Serra, 1998. Direct stator flux and torque control of an induction motor: Theoretical analysis and experimental results. In Proceedings of 24th Annual Conference of the IEEE Industrial Electronics Society, 1998 (IECON 98), Aachen, 1: T50- T64.

3. Domenico, C., G. Serra and T. Angelo, 2000. Implementation of a direct torque control algorithm for induction motors based on discrete space vector. Modulation IEEE T. Power Electr., 15: 769-777.

4. Kennel, R., A. El-refaei, F. Elkady, S. Mahmoud and E. Elkholy, 2003. Torque ripple minimization for induction motor drives with direct torque control. Proceeding of 5th International Conference on Power Electronics and Drive Systems, 1: 210-215. 

Integration and Operation of a Single-Phase Bidirectional Inverter With Two Buck/Boost MPPTs for DC-Distribution Applications

Integration and Operation of a Single-Phase

Bidirectional Inverter With Two Buck/Boost MPPTs

for DC-Distribution Applications

ABSTRACT:

This study is focused on integration and operation of a single-phase bidirectional inverter with two buck/boost maximum power point trackers (MPPTs) for dc-distribution applications. In a dc-distribution system, a bidirectional inverter is required to control the power flow between dc bus and ac grid, and to regulate the dc bus to a certain range of voltages.Adroop regulation mechanism according to the inverter inductor current levels to reduce capacitor size, balance power flow, and accommodate load variation is proposed. Since the photovoltaic (PV) array voltage can vary from 0 to 600 V, especially with thin-film PV panels, the MPPT topology is formed with buck and boost converters to operate at the dc-bus voltage around 380 V, reducing the voltage stress of its followed inverter. Additionally, the controller can online check the input configuration of the two MPPTs, equally distribute the PV-array output current to the two MPPTs in parallel operation, and switch control laws to smooth out mode transition. A comparison between the conventional boost MPPT and the proposed buck/boost MPPT integrated with a PV inverter is also presented. Experimental results obtained from a 5-kW system have verified the discussion and feasibility.

KEYWORDS:

1.     Bidirectional inverter

2.     Buck/Boost Maximum Power Point Trackers (MPPTs)

3.     DC-distribution applications.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

               

            Fig. Configuration of the studied PV inverter system with the buck/boost MPPTs.

  

CONCLUSION:

In this paper, a single-phase bidirectional inverter with two buck/boost MPPTs has been designed and implemented. The inverter controls the power flow between dc bus and ac grid, and regulates the dc bus to a certain range of voltages. A droop regulation mechanism according to the inductor current levels has been proposed to balance the power flow and accommodate load variation. Since the PV-array voltage can vary from 0 to 600 V, the MPPT topology is formed with buck and boost converters to operate at the dc-bus voltage around 380 V, reducing the voltage stress of its followed inverter. Additionally, the controller can online check the input configuration of the MPPTs, equally distribute the PV-array output current to the two MPPTs in parallel operation, and switch control laws to smooth out mode transition. Integration and operation of the overall inverter system have been discussed in detail, which contributes to dc distribution applications significantly. Experimental results obtained from a 5-kW, single-phase bidirectional inverter with the two MPPTs have verified the analysis and discussion.

REFERENCES:

[1] J. M. Carrasco, L. G. Franquelo, J. T. Bialasiewicz, E. Galvan, R. C. P. Guisado, Ma. A. M. Prats, J. I. Leon, and N. Moreno-Alfonso, “Power-electronic systems for the grid integration of renewable energy sources: a survey,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1002– 1016, Aug. 2006.

[2] L. N. Khanh, J.-J. Seo, T.-S. Kim, and D.-J. Won, “Power-management strategies for a grid-connected PV-FC hybrid system,” IEEE Trans. Power Deliv., vol. 25, no. 3, pp. 1874–1882, Jul. 2010.

[3] Y. K. Tan and S. K. Panda, “Optimized wind energy harvesting system using resistance emulator and active rectifier for wireless sensor nodes,” IEEE Trans. Power Electron., vol. 26, no. 1, pp. 38–50, Jan. 2011.

[4] J.-M. Kwon, K.-H. Nam, and B.-H. Kwon, “Photovoltaic power conditioning system with line connection,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1048–1054, Aug. 2006.

[5] J. Selvaraj and N. A. Rahim, “Multilevel inverter for grid-connected PV system employing digital PI controller,” IEEE Trans. Ind. Electron., vol. 56, no. 1, pp. 149–158, Jan. 2009.

Control for Grid-Connected and Intentional Islanding Operations of Distributed Power Generation

Control for Grid-Connected and Intentional Islanding

Operations of Distributed Power Generation

ABSTRACT:

Intentional islanding describes the condition in which a microgrid or a portion of the power grid, which consists of a load and a distributed generation (DG) system, is isolated from the remainder of the utility system. In this situation, it is important for the microgrid to continue to provide adequate power to the load. Under normal operation, each DG inverter system in the microgrid usually works in constant current control mode in order to provide a preset power to the main grid. When the microgrid is cut off from the main grid, each DG inverter system must detect this islanding situation and must switch to a voltage control mode. In this mode, the microgrid will provide a constant voltage to the local load. This paper describes a control strategy that is used to

implement grid-connected and intentional-islanding operations of distributed power generation. This paper proposes an intelligent load-shedding algorithm for intentional islanding and an algorithm of synchronization for grid reconnection.

KEYWORDS:

1.     Distributed generation (DG)

2.     Grid-connected operation

3.     Intentional-islanding operation

4.     Islanding detection

5.     Load shedding

6.     Synchronization

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Schematic diagram of the grid-connected inverter system.

CONCLUSION:

Through this paper, the control, islanding detection, load shedding, and reclosure algorithms have been proposed for the operation of grid-connected and intentional-islanding DGs. A controller was designed with two interface controls: one for grid-connected operation and the other for intentional islanding operation. An islanding-detection algorithm, which was responsible for the switch between the two controllers, was presented. The simulation results showed that the detection algorithm can distinguish between islanding events and changes in the loads and can apply the load-shedding algorithms when needed. The reclosure algorithm causes the DG to resynchronize itself with the grid. In addition, it is shown that the response of the proposed control schemes is capable of maintaining the voltages and currents within permissible levels during grid connected and islanding operation modes. The experimental results showed that the proposed control schemes are capable of maintaining the voltages within the standard permissible levels during grid-connected and islanding operation modes. In addition, it was shown that the reclosure algorithm causes the DG to resynchronize itself with the grid.

REFERENCES:

[1] D. Jayaweera, S. Galloway, G. Burt, and J. R. McDonald, “A sampling approach for intentional islanding of distributed generation,” IEEE Trans. Power Syst., vol. 22, no. 2, pp. 514–521, May 2007.

[2] J. M. Guerrero, J. C. Vásquez, J. Matas, M. Castilla, and L. García de Vicuña, “Control strategy for flexible microgrid based on parallel lineinteractive UPS systems,” IEEE Trans. Ind. Electron., vol. 56, no. 3, pp. 726–736, Mar. 2009.

[3] P. Fuangfoo, T. Meenual,W.-J. Lee, and C. Chompoo-inwai, “PEA guidelines for impact study and operation of DG for islanding operation,” IEEE Trans. Ind. Appl., vol. 44, no. 5, pp. 1348–1353, Sep./Oct. 2008. 156 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 58, NO. 1, JANUARY 2011

[4] E. Carpaneto, G. Chicco, and A. Prunotto, “Reliability of reconfigurable distribution systems including distributed generation,” in Proc. Int. Conf. PMAPS, 2006, pp. 1–6.

[5] IEEE Recommended Practice for Utility Interface of Photovoltaic (PV) Systems, IEEE Std 929-2000, 2000, p. i.

Dynamic Modeling and Simulation of Hybrid Power Systems Based on Renewable Energy

Dynamic Modeling and Simulation of Hybrid Power

Systems Based on Renewable Energy

ABSTRACT:

This paper describes dynamic modeling and simulation results of a renewable energy based hybrid power system. The paper focuses on the combination of solar cell (SC), wind turbine (WT), fuel cell (FC) and ultra-capacitor (UC) systems for power generation. As the wind turbine output power varies with the wind speed and the solar cell output power varies with both the ambient temperature and radiation, a FC system with an UC bank can be integrated to ensure that the system performs under all conditions. Excess wind and solar energies when available are converted to hydrogen using an electrolyzer for later use in the fuel cell. Dynamic modeling of various components of this isolated system is presented. Transient responses of the system to step changes in the load, ambient temperature, radiation, and wind speed in a number of possible situations are studied.

KEYWORDS:

1. Fuel cell

2. Hybrid power system

3. Renewable energy

4. Solar cell

5. Ultra-capacitor

6. Wind turbine

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Figure 1. Renewable energy based hybrid power system model in Simulink.

CONCLUSION:

In this paper, a novel renewable energy based hybrid power system is proposed and modeled for a stand-alone user with appropriate power controllers. The available power from the renewable energy sources is highly dependent on environmental conditions such as wind speed, radiation, and ambient temperature. To overcome this deficiency of the solar cell and wind system, we integrated them with the FC/UC system using a novel topology. The voltage variation at the output is found to be within the acceptable range. The output fluctuations of the wind turbine varying with wind speed and the solar cell varying with both environmental temperature and sun radiation are reduced using a fuel cell. Therefore, this system can tolerate the rapid changes in load and environmental conditions, and suppress the effects of these fluctuations on the equipment side voltage. The proposed system can be used for off-grid power generation in non interconnected areas or remote isolated communities.

REFERENCES:

[1] C. T. Pan, J. Y. Chen, C. P. Chu, and Y. S. Huang, “A Fast Maximum Power Point Tracing for Photovoltaic Power Systems,” in Proc. 1999 IEEE Industrial Electronics Society Conf., vol. 1, pp. 390-393.

[2] J. A. Gow and C. D. Manning, “Development of a Photovoltaic Array Model for Use in Power-electronics Simulation Studies,” IEE Proc.- Electric Power Application, vol. 146, no. 2, pp. 193-200, March 1999.

[3] The MathWorks http://www.mathworks.com/.

[4] M. J. Khan and M. T. Iqbal, “Dynamic Modeling and Simulation of a Small Wind-Fuel Cell Hybrid Energy System,” Renewable Energy, pp. 421-439, 2005.

[5] S. M. Shaahid and M. A. Elhadidy, “Technical and Economic Assessment of Gidindependent Hybrid Photovoltaic-Diesel-Battery Power Systems for Commercial Loads in Desert Environments,” Renewable and Sustainable Energy Reviews, vol. 11, pp. 1794-1810, Oct. 2007.

                                      

Electric Springs—A New Smart Grid Technology

Electric Springs—A New Smart Grid Technology

ABSTRACT:

The scientific principle of “mechanical springs” was described by the British physicist Robert Hooke in the 1660’s. Since then, there has not been any further development of the Hooke’s law in the electric regime. In this paper, this technological gap is filled by the development of “electric springs.” The scientific principle, the operating modes, the limitations, and the practical realization of the electric springs are reported. It is discovered that such novel concept has huge potential in stabilizing future power systems with substantial penetration of intermittent renewable energy sources. This concept has been successfully demonstrated in a practical power system setup fed by an ac power source with a fluctuating wind energy source. The electric spring is found to be effective in regulating the mains voltage despite the fluctuation caused by the intermittent nature of wind power. Electric appliances with the electric springs embedded can be turned into a new generation of smart loads, which have their power demand following the power generation profile. It is envisaged that electric springs, when distributed over the power grid, will offer a new form of power system stability solution that is independent of information and communication technology.

KEYWORDS:

1. Distributed power systems

2. Smart loads

3. Stability

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. The experimental setup for the electric spring (with control block diagram).

 CONCLUSION:

The Hooke’s law on mechanical springs has been developed into an electric spring concept with new scientific applications for modern society. The scientific principles, operating modes and limits of the electric spring are explained. An electric spring has been practically tested for both voltage support and suppression, and for shaping load demand (of about 2.5 kW) to follow the fluctuating wind power profile in a 10 kVA power system fed by an ac power source and a wind power simulator. The electric springs can be incorporated into many existing noncritical electric loads such as water heaters and road lighting systems [26] to form a new generation of smart loads that are adaptive to the power grid. If many noncritical loads are equipped with such electric springs and distributed over the power grid, these electric springs (similar to the spring array in Fig. 1) will provide a highly reliable and effective solution for distributed energy storage, voltage regulation and damping functions for future power systems. Such stability measures are also independent of information and communication technology (ICT). This discovery based on the three-century-old Hooke’s law offers a practical solution to the new control paradigm that the load demand should follow the power generation in future power grid with substantial renewable energy sources. Unlike traditional reactive power compensation methods, electric springs offer both reactive power compensation and real power variation in the noncritical loads. With many countries determined to de-carbonize electric power generation for reducing global warming by increasing renewable energy up to 20% of the total electrical power output by 2020 [22]–[25], electric spring is a novel concept that enables human society to use renewable energy as nature provides. The Hooke’s law developed in the 17th century has laid down the foundation for stability control of renewable power systems in the 21st century.

REFERENCES:

[1] Hooke’s law—Britannica Encyclopedia [Online]. Available: http://www.britannica.com/EBchecked/topic/271336/Hookes-law

[2] A. M. Wahl, Mechanical Springs, 2nd ed. New York: McGraw-Hill, 1963.

[3] W. S. Slaughter, The Linearized Theory of Elasticity. Boston, MA: Birkhauser, 2002.

[4] K. Symon, Mechanics. ISBN 0-201-07392-7. Reading, MA: Addison- Wesley, Reading,1971.

[5] R. Hooke, De Potentia Restitutiva, or of Spring Explaining the Power of Springing Bodies. London, U.K.: John Martyn, vol. 1678, p. 23.

Enhancement of Power Quality in Distribution System Using D-STATCOM

Abstract:

This paper presents the enhancement of voltage sags, harmonic distortion and low power factor using Distribution Static Compensator (D-STATCOM) with LCL Passive Filter in distribution system. The model is based on the Voltage Source Converter (VSC) principle. The D-STATCOM injects a current into the system to mitigate the voltage sags.LCL Passive Filter was then added to D-STATCOM to improve harmonic distortion and low power factor. The simulations were performed using MATLAB SIMULINK version R2007b.

Keywords:

1.      D-STATCOM

2.       Voltage Sags

3.       Voltage Source Converter (VSC)

4.       LCL Passive Filter

5.       Total harmonics Distortion (THD)

Software: MATLAB/SIMULINK

 Block Diagram:

Figure.1. Schematic diagram of a D-STATCOM

Conclusion:

The simulation results show that the voltage sags can be mitigate by inserting D-STATCOM to the distribution system. By adding LCL Passive filter to D-STATCOM, the THD reduced within the IEEE STD 519-1992. The power factors also increase close to unity. Thus, it can be concluded that by adding D-STATCOM with LCL filter the power quality is improved.

References:

  [1] A.E. Hammad, Comparing the Voltage source capability of Present and future Var Compensation Techniques in Transmission System, IEEE Trans, on Power Delivery . volume 1. No.1 Jan 1995.

[2] G.Yalienkaya, M.H.J Bollen, P.A. Crossley, “Characterization of Voltage Sags in Industrial Distribution System”, IEEE transactions on industry applications, volume 34, No. 4, July/August, PP.682-688, 1999

[3] Haque, M.H., “Compensation Of Distribution Systems Voltage sags by DVR and D-STATCOM”, Power Tech Proceedings, 2001 IEEE Porto, Volume 1, PP.10-13, September 2001.

[4] Anaya-Lara O, Acha E., “Modeling and Analysis Of Custom Power Systems by PSCAD/EMTDC”, IEEE Transactions on Power Delivery, Volume 17, Issue: 2002, Pages: 266-272.

[5] Bollen, M.H.J.,”Voltage sags in Three Phase Systems”, Power Engineering Review , IEEE, Volume 21, Issue :9, September 2001, PP: 11-15.