Induction Motor Drive For PV Water Pumping With Reduced Sensors

ABSTRACT:

This study presents the reduced sensors based standalone solar photovoltaic (PV) energised water pumping. The system is configured to reduce both cost and complexity with simultaneous assurance of optimum power utilisation of PV array. The proposed system consists of an induction motor-operated water pump, controlled by modified direct torque control. The PV array is connected to the DC link through a DC–DC boost converter to provide maximum power point tracking (MPPT) control and DC-link voltage is maintained by a three-phase voltage-source inverter. The estimation of motor speed eliminates the use of tacho generator/encoder and makes the system cheaper and robust. Moreover, an attempt is made to reduce the number of current sensors and voltage sensors in the system. The proposed system constitutes only one current sensor and only one voltage sensor used for MPPT as well as for the phase voltage estimation and for the phase currents’ reconstruction. Parameters adaptation makes the system stable and insensitive toward parameters variation. Both simulation and experimental results on the developed prototype in the laboratory validate the suitability of proposed system.

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig. 1 circuit diagram (a) Proposed system,

 EXPECTED SIMULATION RESULTS:

Fig. 2 Performance indices (a) PV array during starting to steady state at 1000 W/m2, (b) IMD indices at 1000 W/m2

Fig. 3 Performance indices during insolation change 1000–500 W/m2

(a) PV array, (b) IMD indices 500–1000 W/m2, (c) PV array (d) IMD indices

Fig. 4 Adaptation mechanism

(a) Rs adaptation at rated speed and insolation, (b) τr Adaptation at rated speed and rated insolation

Fig. 5 Performance indices of the drive

(a) Starting at 1000 W/m2, (b) Starting at 500 W/m2, (c) Steady state at 1000 W/m2,

(d) Steady state at 500 W/m2

Fig. 6 Dynamic performance of the drive under variable insolation

(a) 1000–500 W/m2, (b) 500–1000 W/m2, (c) Intermediate speed signals at 1000–500

W/m2, (d) Intermediate speed signals at 500–1000 W/m2

Fig. 7 Intermediate signals in terms of

(a) Te* and Te at 1000–500 W/m2, (b) 500–1000 W/m2, (c) Reference stationary

components of flux and estimated flux at 1000–500 W/m2, (d) 500–1000 W/m2

Fig. 8 Reconstructed and measured current waveforms of phases a and b

at

(a) Starting performance at 1000 W/m2, (b) 1000 W/m2, (c) 500 W/m2, (d) Boost

converter parameters at 1000 W/m2

CONCLUSION:

The modelling and simulation of the proposed system has been carried out in MATLAB/Simulink and its suitability is validated experimentally on a developed prototype in the laboratory. The system comprises of one voltage sensor and one current sensor, which are sufficient for the proper operation of the proposed system. The motor-drive system performs satisfactorily during starting at various insolations, steady-state, dynamic conditions represented by changing insolation. The speed estimation has been carried out by flux components in stationary frame of reference. The flux and torque are controlled separately. Therefore, successful observation of the proposed system with satisfactory performance has been achieved without the mechanical sensors. This topology improves the stability of the system. The stability of the system at rated condition toward stator resistance variation is shown by Nyquist stability curve and the stability toward the rotor-time constant perturbation is shown by Popov's criteria. The DTC of an induction motor with fixed frequency switching technique reduces the torque ripple. The line voltages are estimated from this DC-link voltage. Moreover, the reconstruction of three-phase stator currents has been successfully carried out from DC-link current. Simulation results are well validated by test results. Owing to the virtues of simple structure, control, cost-effectiveness, fairly good efficiency and compactness, it is inferred that the suitability of the system can be judged by deploying it in the field.

REFERENCES:

[1] Masters, G.M.: ‘Renewable and efficient electric power systems’ (IEEE Press,Wiley and Sons, Inc., Hoboken, New Jersey, 2013), pp. 445–452

[2] Foster, R., Ghassemi, M., Cota, M.: ‘Solar energy: renewable energy and the environment’ (CRC Press, Taylor and Francis Group, Inc., Boca Raton, Florida, 2010)

[3] Parvathy, S., Vivek, A.: ‘A photovoltaic water pumping system with high efficiency and high lifetime’. Int. Conf. Advancements in Power and Energy (TAP Energy), Kollam, India, 24–26 June 2015, pp. 489–493

[4] Shafiullah, G.M., Amanullah, M.T., Shawkat Ali, A.B.M., et al.: ‘Smart grids: opportunities, developments and trends’ (Springer, London, UK, 2013)

[5] Sontake, V.C., Kalamkar, V.R.: ‘Solar photovoltaic water pumping system – a comprehensive review’, Renew. Sustain. Energy Rev., 2016, 59, pp. 1038– 1067

Design and Comparative Study of PhotovoltaicMaximum Power Point Tracking ConverterWith DC Motor Speed Control

ABSTRACT:

The photovoltaic panels as the power supply depends upon the weather condition (radiation, temperature). These conditions must be known to control the running point of the greatest power of photovoltaic panel. In the present paper , the study and design searching the greatest power point by solar panels direct current motor separately excited speed control. Three control methods studied and designed to search the greatest power point of the photovoltaic panel and speed control of direct current motor. The first method is perturbing and observing controller. The second method is proportional-integral-derivative controller, whereas the controller gains are obtained by using trial and error process. The third method is proportional-integralderivative controller based on bacterial foraging algorithm. It used to compute the proportional-integral-derivative controller gains. The three control methods are used to obtain the greatest power point of PV panels and improve the direct current motor output speed performance response. The study of comparative results for open loop and close loop system with different designed controllers. The Simulation results were studied and compared under many weather conditions and direct current motor load torque disturbance. The results of comparison that produce the best controller method is proportional-integral-derivative controller with bacterial foraging algorithm which produce optimal performance results..

KEYWORDS:

1.      Photovoltaic Panel (PV)

2.       Perturbation and Observation Algorithm (Per & Obs)

3.      Searching the Greatest Power Point (SGPP)

4.      Direct Current Motor (DC Motor),Proportional

5.      Integral Derivative Controller (PID) and Bacterial Foraging

6.      Optimization Algorithm (BFOA)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 The close loop system block diagram

EXPECTED SIMULATION RESULTS:

Fig.2. The PVpower response under various weather condition without Controller

Fig.3 DC motor speed response when TL=5-8 Nm without controller

Fig.4 PV power response under various condition with Per and Obs Controller

Fig.5. DC motor speed response when TL=5-8 Nm with Per and Obs Controller

Fig.6 PV power response under various condition with PID controller

Fig.7 DC motor speed response when TL=5-8 Nm with PID controller

Fig.8 PV power response under various condition with PID/BFOA Controller

Fig.9 DC motor speed response when TL=5-8 Nm with PID/BFOA Controller

Fig.10 PV power responses when various weather condition with three different controllers

Fig.11. Zoom of Power responses with three different controllers

Fig.12. DC motor speed responses when TL=5-8 Nm with three different Controllers

Fig.13. Zoom of speed response with three different controllers.

CONCLUSION:

The PV system designs and studies with the dc-dc step up boost converter, which loads by DC motor. The DC motor loads by various load torque. The simulation results of the system studies and the PV panels’ output power responses have been studied under the various weather conditions. The DC motor speed control performance have been studied, three techniques were designed, studied and used to improve and track of the maximum power of the PV panels system and these techniques were used to improve the DC motor speed performance. The first technique is Perturbation and Observation technique. The second technique is the proportional-integral-derivative controller and the third technique is hybrid Proportional-integral-derivative with optimization algorithm of bacterial foraging. The output motor speed and maximum power of the PV panels (PV model, DC motor) with the three techniques have been tested and comparatively studied. These comparative results under the various weather conditions and various external load torque that produce the best performance results and greatest tracking power of PV panels is the PID controller based BFOA controller .the comparison results in the table 4 and 5 proved that.

REFERENCES:

[1] H. Chihchiang and S. Chihming, “Study of Maximum Power Tracking Techniques and Control of DC/DC Converter for Photovoltaic Power System ," in IEEE PESC Power Electronics Specalists Conf.,Vol.1, 1998.

[2] Joe-Air, J., Tsong-Liang, H., Ying-Tung, H., and Chia-Hong ,C. “Maximum Power Tracking for Photovoltaic Power Systems," Tamkang Journal of Science and Engineering ,Vol.8, No 2,pp. 147-153(2005).

[3] Liu C., Wu B., and Cheung R., “ Advanced Algorithm for MPPT Control of Photovoltaic System," 1st Canadian Solar Building Research Network Conference, Aug. 2006.

[4] A. Yafaoui.,B. Wu and R. Cheung, “Implementation of Maximum Power Point Tracking Algorithm for Residential Photovoltaic Systems ," Calgary, June , Canadian Solar Conf. 2007.

[5] Vikrant.A.Chaudhari, “ Automatic Peak Power Tracking for Solar PV Module Using dSpacer Software. ," in Maulana Azad National Institute Of Technology, vol.Degree of Master of Technology In Energy. Bhopal: Deemed University, 2005,pp.98.

Grid Interactive Bidirectional Solar PV Array FedWater Pumping System

 ABSTRACT:

This paper proposes a grid interactive bidirectional solar water pumping system using a three phase induction motor drive (IMD). A single phase voltage source converter (VSC) is used to direct the flow of power from grid supply to the pump and back to the grid from SPV array. A boost converter is used for the maximum power point tracking (MPPT) of the SPV array. A smart power sharing control is proposed, with preference given to the power from SPV array over the grid power. Moreover, the grid input power quality is also improved. Various modes of operation of the pump are elaborated and the performance of the system at starting, in steady state and dynamic conditions are simulated. The simulated results show the novelty and the satisfactory performance of the system.

KEYWORDS:

1.      Solar water pump

2.      MPPT

3.      Grid interactive

4.      Smart power sharing

SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:

Fig. 1. Configuration for the single phase grid interactive SPV water

pumping system

 EXPECTED SIMULATION RESULTS:

Fig. 2(a) Starting performance of the proposed system in mode I

Fig. 3(b) Steady state performance of the proposed system in mode I

Fig. 4(c) Performance of the system in mode I under decreasing radiation

from 800 W/m2 to 500 W/m2

Fig. 5(d) Performance of the system in mode I under increasing radiation

from 500 W/m2 to 800 W/m2

Fig. 6(a) Starting performance of the system in mode II

Fig. 7(b) Steady state performance of the system in mode II

Fig. 8(a) Characteristics of the system in mode III with decrease in

Radiation

Fig. 9(b) Characteristics of the system in mode III with increase in

Radiation

Fig. 10(a) Characteristics of the system in mode IV with increase in

Radiation

Fig. 11 (b) Characteristics of the system in mode III with decrease in

radiation

CONCLUSION:

A single phase grid interactive solar water pumping is presented in the paper. Various modes of operation are identified and simulated in MATLAB Simulink environment. The simulated results have demonstrated the satisfactory performance of the system at starting, and in steady and dynamic conditions. The proposed system not only is able to share the power between two sources but it also improves the quality of power drawn. Moreover, the system manages to feed the power from the SPV array as in when required. The system is well suited for the rural and agricultural usage.

REFERENCES:

[1] J. Zhu, “Application of Renewable Energy,” in Optimization of Power System Operation, Wiley-IEEE Press, 2015, p. 664.

[2] Z. Ying, M. Liao, X. Yang, C. Han, J. Li, J. Li, Y. Li, P. Gao, and J. Ye, “High-Performance Black Multicrystalline Silicon Solar Cells by a Highly Simplified Metal-Catalyzed Chemical Etching Method,” IEEE J. Photovolt., vol. PP, no. 99, pp. 1–06, 2016.

[3] M. Steiner, G. Siefer, T. Schmidt, M. Wiesenfarth, F. Dimroth, and A. W. Bett, “43% Sunlight to Electricity Conversion Efficiency Using CPV,” IEEE J. Photovolt., vol. PP, no. 99, pp. 1–5, 2016.

[4] M. Kolhe, J. C. Joshi, and D. P. Kothari, “Performance analysis of a directly coupled photovoltaic water-pumping system,” IEEE Trans. Energy Convers., vol. 19, no. 3, pp. 613–618, Sep. 2004.

[5] S. R. Bhat, A. Pittet, and B. S. Sonde, “Performance Optimization of Induction Motor-Pump System Using Photovoltaic Energy Source,” IEEE Trans. Ind. Appl., vol. IA-23, no. 6, pp. 995–1000, Nov. 1987.