An Efficient UPF Rectifier for a Stand-Alone Wind Energy Conversion System

ABSTRACT:

 In this paper, a near-unity-power-factor front-end rectifier employing two current control methods, namely, average current control and hysteresis current control, is considered. This rectifier is interfaced with a fixed-pitch wind turbine driving a permanent-magnet synchronous generator. A traditional diode-bridge rectifier without any current control is used to compare the performance with the proposed converter. Two constant wind speed conditions and a varying wind speed profile are used to study the performance of this converter for a rated stand-alone load. The parameters under study are the input power factor and total harmonic distortion of the input currents to the converter. The wind turbine generator–power electronic converter is modeled in PSIM, and the simulation results verify the efficacy of the system in delivering satisfactory performance for the conditions discussed. The efficacy of the control techniques is validated with a 1.5-kW laboratory prototype, and the experimental results are presented.

KEYWORDS:

1.      Average current control (ACC)

2.      Hysteresis current control (HCC)

3.      Permanent-magnet synchronous generator (PMSG)

4.      Unity-power-factor (UPF) converter

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Schematic of the UPF converter in the wind generator system employing

the ACC method.

Fig. 2. Schematic of the UPF converter in the wind generator system employing the HCC method.

EXPERIMENTAL RESULTS:

Fig. 3. Performance parameters of the UPF rectifier using ACC at a rated wind speed of 12 m/s. (a) Input power factor of the front-end rectifier employing  ACC at a rated wind speed of 12 m/s. (b) FFT of phase “a” current to frontend rectifier employing ACC at a rated wind speed of 12 m/s. (c) Mechanical, PMSG, and dc output powers of the system employing ACC at a rated wind of speed 12 m/s. (d) DC bus capacitor voltages of the system employing ACC at a rated wind speed of 12 m/s.

Fig. 4. Performance parameters of the UPF rectifier employing ACC at a wind speed of 14 m/s. (a) Input power factor of the front-end rectifier employing ACC at a wind speed of 14 m/s. (b) FFT of phase “a” current to front-end rectifier employing ACC at a wind speed of 14 m/s. (c) Mechanical, PMSG, and dc output powers of the system employing ACC at a wind speed of 14 m/s.

Fig. 5. Wind speed variation and performance coefficient of wind turbine for

system operating with ACC.

Fig. 6. Performance parameters of the UPF rectifier using HCC at a rated wind speed of 12 m/s. (a) Input power factor of the front-end rectifier employing HCC at a rated wind speed of 12 m/s. (b) FFT of phase “a” current to frontend rectifier for HCC at a rated wind speed of 12 m/s. (c) Mechanical, PMSG, and dc output powers of the system for HCC at a rated wind speed of 12 m/s. (d) DC bus capacitor voltages for HCC at a rated wind speed of 12 m/s.

Fig. 7 Performance parameters of the UPF rectifier using HCC at a wind speed of 14 m/s. (a) Input power factor of the front-end rectifier employing HCC at a higher wind speed of 14 m/s. (b) FFT of phase “a” current to frontend rectifier for HCC at a higher wind speed of 14 m/s. (c) Mechanical, PMSG, and dc output powers of the system for HCC at a higher wind speed of 14 m/s.

Fig. 8.Wind speed variation and performance coefficient of wind turbine for

system operating with HCC.

Fig. 9. Performance parameters of the diode-bridge rectifier at a rated wind speed of 12 m/s. (a) Input power factor of the front-end diode-bridge rectifier at a rated wind speed of 12 m/s. (b) FFT of phase “a” current of front-end diode bridge rectifier at a rated wind speed of 12 m/s. (c) Mechanical, PMSG, and dc output powers of the system for front-end diode-bridge rectifier at a rated wind speed of 12 m/s.

Fig. 10. Wind speed variation and performance coefficient of wind turbine for

system operating without current control.

CONCLUSION:

In this paper, a WECS interfaced with a UPF converter feeding a stand-alone load has been investigated. The use of simple bidirectional switches in the three-phase converter results in near-UPF operation. Two current control methods, i.e., ACC and HCC, have been employed to perform active input line current shaping, and their performances have been compared for different wind speed conditions. The quality of the line currents at the input of the converter is good, and the harmonic distortions are within the prescribed limits according to the IEEE 519 standard for a stand-alone system. A high power factor is achieved at the input of the converter, and the voltage maintained at the dc bus link shows excellent voltage balance. The proposed method yields better performance compared to a traditional uncontrolled diode bridge rectifier system typically employed in wind systems as the front-end converter. Finally, a laboratory prototype of the UPF converter driving a stand-alone load has been developed, and the ACC and HCC current control methods have been tested for comparison. The HCC current control technique was found to be superior and  has better voltage balancing ability. It can thus be an excellent front-end converter in a WECS for stand-alone loads or grid connection.

REFERENCES:

[1] C. E. A. Silva, D. S. Oliveira, L. H. S. C. Barreto, and R. P. T. Bascope, “A novel three-phase rectifier with high power factor for wind energy conversion systems,” in Proc. COBEP, Bonito-Mato Grosso do Sul, Brazil, 2009, pp. 985–992.

[2] Online. Available: http://en.wikipedia.org/wiki/Wind_energy

[3] M. Druga, C. Nichita, G. Barakat, B. Dakyo, and E. Ceanga, “A peak power tracking wind system operating with a controlled load structure for stand-alone applications,” in Proc. 13th EPE, 2009, pp. 1–9.

[4] S. Kim, P. Enjeti, D. Rendusara, and I. J. Pitel, “A new method to improve THD and reduce harmonics generated by a three phase diode rectifier type utility interface,” in Conf. Rec. IEEE IAS Annu. Meeting, 1994, vol. 2, pp. 1071–1077.

[5] A. I. Maswood and L. Fangrui, “A novel unity power factor input stage for AC drive application,” IEEE Trans. Power Electron., vol. 20, no. 4, pp. 839–846, Jul. 2005.

Development of High-Performance Grid-Connected Wind Energy Conversion System for Optimum Utilization of Variable Speed Wind Turbines

ABSTRACT:

This paper presents an improvement technique for the power quality of the electrical part of a wind generation system with a self-excited induction generator (SEIG) which aims to optimize the utilization of wind power injected into weak grids. To realize this goal, an uncontrolled rectifier-digitally controlled inverter system is proposed. The advantage of the proposed system is its simplicity due to fewer controlled switches which leads to less control complexity. It also provides full control of active and reactive power injected into the grid using a voltage source inverter (VSI) as a dynamic volt ampere reactive (VAR) compensator. A voltage oriented control (VOC) scheme is presented in order to control the energy to be injected into the grid. In an attempt to minimize the harmonics in the inverter current and voltage and to avoid poor power quality of the wind energy conversion system (WECS), an filter is inserted between VOC VSI and the grid. The proposed technique is implemented by a digital signal processor (DSP TMS320F240) to verify the validity of the proposed model and show its practical superiority in renewable energy applications.

KEYWORDS:

1.      Grid connected systems

2.      Self-excited induction generator (SEIG)

3.      Voltage oriented control (VOC)

4.      Voltage source inverter (VSI)

5.      Wind energy conversion systems (WECSs)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Proposed SEIG-based WECS with VOC VSI.

 EXPERIMENTAL RESULTS:

Fig. 2. Line voltage of theVSI in frame (400 V/div–5ms). (a) Simulation.

(b) Experiment.

Fig. 3. Phase voltage of the VSI in frame (400 V/div–5 ms). (a) Simulation.

(b) Experiment.

Fig. 4. Grid phase voltage (50 V/div–10 ms) and injected current

(1 A/div–10 ms). (a) Simulation. (b) Experiment.

Fig. 5. Inverter phase voltage to be connected to the grid with only filter

(50 V/div–10 ms). (a) Simulation. (b) Experiment.

Fig. 6. Grid voltage (50 V/div–25 ms) and injected current (1 A/div–25 ms)

under step change in the reactive power injected into grid. (a) Simulation.

(b) Experiment.

Fig. 7. VSI response with filter for the grid and capacitor voltage

(100 V/div–10 ms) with the injected line current (5 A/div–10 ms). (a) Simulation.

(b) Experiment.

Fig. 8. Harmonic spectrum analysis with filter. (a) Injected current harmonic

content. (b) Filter capacitor voltage harmonic content.

CONCLUSION:

In this paper, the SEIG-based WECS dynamic model has been derived. The VOC grid connected VSI has been investigated for high performance control operation. The test results showed how the control scheme succeeded in injecting the wind power as active or reactive power in order to compensate the weak grid power state. An filter is inserted between VOC VSI and grid to obtain a clean voltage and current waveform with negligible harmonic content and improve the power quality. Also, this technique achieved unity power factor grid operation (average above 0.975), very fast transient response within a fraction of a second (0.4 s) under different possible conditions (wind speed variation and load variation), and high efficiency due to a reduced number of components (average above 90%) has been achieved. Besides the improvement in the converter efficiency, reduced mechanical and electrical stresses in the generator are expected, which improves the overall system performance. The experimental results obtained from a prototype rated at 250 W showed that the current and voltage THD (2.67%, 0.12%), respectively, for the proposed WECS with filter is less than 5% limit imposed by IEEE-519 standard. All results obtained confirm the effectiveness of the proposed system feasible for small-scale WECSs connected to weak grids.

REFERENCES:

[1] V. Kumar, R. R. Joshi, and R. C. Bansal, “Optimal control of matrix-converter-based WECS for performance enhancement and efficiency optimization,” IEEE Trans. Energy Convers., vol. 24, no. 1, pp. 264–272, Mar. 2009.

[2] Y. Zhou, P. Bauer, J. A. Ferreira, and J. Pierik, “Operation of grid connected DFIG under unbalanced grid voltage,” IEEE Trans. Energy Convers., vol. 24, no. 1, pp. 240–246, Mar. 2009.

[3] S. M. Dehghan, M.Mohamadian, and A. Y. Varjani, “A new variable speed wind energy conversion system using permanent-magnet synchronous generator and z-source inverter,” IEEE Trans Energy Convers., vol. 24, no. 3, pp. 714–724, Sep. 2009.

[4] K. Tan and S. Islam, “Optimum control strategies for grid-connected wind energy conversion system without mechanical sensors,” WSEAS Trans. Syst. Control, vol. 3, no. 7, pp. 644–653, Jul. 2008, 1991-8763.

[5] B. C. Rabelo, W. Hofmann, J. L. da Silva, R. G. de Oliveira, and S. R. Silva, “Reactive power control design in doubly fed induction generators for wind turbines,” IEEE Trans. Ind. Elect., vol. 56, no. 10, pp. 4154–4162, Oct. 2009.

Intelligent Energy Control Center for Distributed Generators Using Multi-Agent System

ABSTRACT:

This paper presents the modeling of intelligent energy control center (ECC) controlling distributed generators (DGs) using multi-agent system. Multi-agent system has been proposed to provide intelligent energy control and management in grids because of their benefits of extensibility, autonomy, reduced maintenance, etc. The multi-agent system constituting the smart grid and agents such as user agent, control agent, database agent, distributed energy resources (DER) agent work in collaboration to perform assigned tasks. The wind power generator connected with local load, the solar power connected with local load and the ECC controlled by fuzzy logic controller (FLC) are simulated in MATLAB/SIMULINK. The DER model is created in client and ECC is created in server. Communication between the server and the client is established using transmission control protocol/internet protocol (TCP/IP). The results indicate that the controlling of DER agent can be achieved both from server and client.

KEYWORDS:

1.      Distributed energy resources (DER) and transmission control protocol/internet protocol (TCP/IP)

2.      Distributed generators (DGs)

3.      Energy control center (ECC)

4.      Fuzzy logic controller (FLC)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Block diagram of power system interconnected with wind and solar

power generation scheme.

EXPERIMENTAL RESULTS:

Fig. 2. Voltage waveform of wind and solar power – circuit breaker (CB-1) closed after 0.1 s and circuit breaker (CB-2) closed after 0.3 s to interconnect solar power to wind.

Fig. 3. Voltage waveform of wind and solar power circuit breaker (CB-1) closed after 0.1 s and circuit breaker (CB-2) closed after 0.3 s to interconnect  solar power to wind observed up to 0.6 s.

CONCLUSION:

The simulation model of ECC, controlling the solar power generation and wind power generation interconnected with grid using multi-agent system is described in this paper. The voltage of wind and solar power are stored in a excel sheet as a database agent. Intelligent controller FLC controls the switch provided in the solar panel to add/remove depending upon the voltage requirements. This excel sheet acting as a monitoring tool to access the simulation results, provides the visualization of the grid. The results prove that the multi-agent component controls the Distributed Energy Resources.

REFERENCES:

[1] T. Nagata and H. Sasaki, “A multi-agent approach to power system restoration,” IEEE Trans. Power Syst., vol. 17, no. 2, pp. 457–462, May 2002.

[2] T. A. Dimeas and N. D. Hatziargyriou, “Operation of a multi-agent system for microgrid control,” IEEE Trans. Power Syst., vol. 20, no. 3,  pp. 1447–1455, Aug. 2005.

[3] S. G. Ankaliki, “Energy control center functions for power system,” Int. J. Math. Sci., Technol., Humanities, vol. 2, no. 1, pp. 205–212, 2012.

[4] R. L. Krutz, Securing SCADA Systems. New York, NY, USA: Wiley, 2006.

[5] O. Castillo and P. melin, Studies in Fuzziness and Soft Computing Type2 Fuzzy Logic : Theory and Applications. NewYork,NY,USA: Springer-Verlag, 2008.

Simulation and Analysis of MPPT Algorithms for Solar PV based Charging Station

ABSTRACT:

Maximum Power Point Tracking (MPPT) algorithms is conferred in this paper used in photovoltaic (PV) systems for changing temperature and irradiance conditions. The MPPT control is always combined with a DC-DC power converter to produce maximal power under differing metrological conditions. The boost converter is used along with the Maximum Power Point Tracking control system. Perturb and Observe (P&O) and Incremental Conductance algorithm (INC) are the two widely used algorithms for drawing maximal power from the photovoltaic source. Direct duty ratio control technique is used for both the algorithms. The system is modeled using MATLAB Simulink software. The simulation result of 50W PV module produced by the two algorithms are analysed and a comparative study is presented.

KEYWORDS:

1.      Maximum power point tracking (MPPT)

2.      MATLAB SIMULINK

3.      Photovoltaic (PV)

4.      Perturb and Observe (P&O)

5.      Incremental conductance (INC)

6.      Duty ratio (D)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1. Block diagram of MPPT control

 EXPERIMENTAL RESULTS:

Fig.2. Non-linear P-V and I-V curves for 1000 W/m2 at 25ᵒC

                                                         

                                                          Fig.3. I-V and P-V curves for different irradiance values at 25ᵒC

Fig.4. Waveforms at irradiance values from 400 W/m2 – 800 W/m2 for a

step time of 0.4 seconds at 25ᵒC

Fig.5. Waveforms at irradiance values from 800W/m2 – 1000 W/m2 for a

step time of 0.4 seconds at 25ᵒC

Fig.6.Waveforms at irradiance values from 400 W/m2- 800 W/m2 for a

step time of 0.4 seconds at 25ᵒC

Fig.7. Waveforms at irradiance values from 800 W/m2 -1000 W/m2 for a

step time of 0.4 seconds at 25ᵒC

CONCLUSION:

A mathematical model of a 50W photovoltaic (PV) panel modeled with MPPT control algorithms is discussed in this paper. The Perturb and Observe algorithm, and Incremental conductance algorithm are explained and simulated using the MATLAB Simulink. Here the MPPT control is achieved by direct duty ratio control of the boost converter which is linked to the load for its maximum efficiency under varying temperature and irradiance values of solar PV panel. The Perturb and Observe (P&O) method is simple to implement. It has slow response during changing atmospheric conditions due to fixed step size and has a tendency of drifting the operating point towards the wrong side. These issues are addressed by using Incremental conductance method (INC) which has a better performance over Perturb and Observe algorithm. It has a faster response and is more efficient in tracking when the irradiance values are changing continuously. The steady-state performance of the photovoltaic control system are improved by using the MPPT algorithms.

REFERENCES:

[1] S.Mekhilef, "Performance of grid connected inverter with maximum power point tracker and power factor control, “International Journal of Power Electronics, vol. 1, pp. 49-62, 2008.

[2] Shridhar Sholapur, K. R. Mohan, T. R. Narsimhegowda,” Boost Converter Topology for PV System with Perturb And Observe MPPT Algorithm”,” IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), Volume 9, Issue 4 Ver. II (Jul – Aug. 2014), PP 50-56.

[3] Pallavi Bharadwaj, Vinod John, “Direct Duty Ratio Controlled MPPT Algorithm for Boost Converter in Continuous and Discontinuous Modes of Operation” Indian Institute of Science Bangalore, India.

[4] Hyeonah Park, Hyosung Kim,” PV cell modeling on single-diode equivalent circuit”.

[5] Bijit Kumar Dey, Imran Khan, Nirabhra Mandal, Ankur Bhattacharjee,” Mathematical Modelling and Characteristic analysis of Solar PV Cell”, Institute of Engineering & Management Kolkata, India.

Low Switching Frequency Based Asymmetrical Multilevel Inverter Topology With Reduced Switch Count

ABSTRACT:

The inceptions of multilevel inverters (MLI) have caught the attention of researchers for medium and high power applications. However, there has always been a need for a topology with a lower number of device count for higher efficiency and reliability. A new single-phase MLI topology has been proposed in this paper to reduce the number of switches in the circuit and obtain higher voltage level at the output. The basic unit of the proposed topology produces 13 levels at the output with three dc voltage sources and eight switches. Three extentions of the basic unit have been proposed in this paper. A detailed analysis of the proposed topology has been carried out to show the superiority of the proposed converter with respect to the other existing MLI topologies. Power loss analysis has been done using PLECS software, resulting in a maximum efficiency of 98.5%. Nearest level control (NLC) pulse-width modulation technique has been used to produce gate pulses for the switches to achieve better output voltage waveform. The various simulation results have been performed in the PLECS software and a laboratory setup has been used to show the feasibility of the proposed MLI topology.

KEYWORDS:

1.      DC/AC converter

2.      Multilevel inverter

3.      Reduce switch count

4.      Nearest level control (NLC)

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Figure 1. Basic unit of the proposed topology.

 EXPERIMENTAL RESULTS:

Figure 2. Simulation results with (a) dynamic change of modulation

index (b) FFT of 13 level output voltage and current with ZD10C100mH

and (c) output voltage and current waveforms with change of load from

ZD50 to ZD50C100mH.

CONCLUSION:

The paper presents a novel MLI topology with multiple extension capabilities. The basic unit of the proposed topology produces 13 levels using eight unidirectional switches and three dc voltage sources. Three different extension of the basic unit has been proposed. The performance analysis of the basic unit of the proposed topology has been done and the comparative results with some recently proposed topologies in literature have been presented in the paper. Further, a power loss analysis of the dynamic losses (switching and conduction) in the MLI has also been presented, which gives the maximum efficiency of the basic unit as 98.5%. The power loss distribution in all the switches for different combination of loads have also been demonstrated in the paper. The performance of the proposed topology has been simulated with dynamic modulation indexes and different combination of loads using PLECS software. A prototype of the basic unit has been developed in the laboratory and the simulation results have been validated using the different experimental results considering different modulation indexes.

REFERENCES:

[1] S. Kouro, M. Malinowski, K. Gopakumar, J. Pou, L. G. Franquelo, B.Wu, J. Rodriguez, M. A. Perez, and J. I. Leon, ``Recent advances and industrial applications of multilevel converters,'' IEEE Trans. Ind. Electron., vol. 57, no. 8, pp. 2553_2580, Aug. 2010.

[2] H. Aburub, J. Holtz, and J. Rodriguez, ``Medium-voltage multilevel converters-state of the art, challenges, and requirements in industrial applications,'' IEEE Trans. Ind. Electron, vol. 57, no. 8, pp. 2581_2596, Dec. 2010.

[3] H. Akagi, ``Multilevel converters: Fundamental circuits and systems,'' Proc. IEEE, vol. 105, no. 11, pp. 2048_2065, Nov. 2017.

[4] J. I. Leon, S. Vazquez, and L. G. Franquelo, ``Multilevel converters: Control and modulation techniques for their operation and industrial applications,'' Proc. IEEE, vol. 105, no. 11, pp. 2066_2081, Nov. 2017.

[5] J. Venkataramanaiah, Y. Suresh, and A. K. Panda, ``A review on symmetric, asymmetric, hybrid and single DC sources based multilevel inverter topologies,'' Renew. Sustain. Energy Rev., vol. 76, pp. 788_812, Sep. 2017.