Modeling, Simulation and Implementation of a Five-Phase Induction Motor Drive System

 ABSTRACT:  

This paper presents a comprehensive simulation model of a five-phase induction motor drive system. Both open loop and closed-loop control is elaborated. The complete component modeling is developed using ‘simpower system’ blocksets of Matlab/Simulink. To address the real time implementation issues, dead banding of the inverter switches are also incorporated in the simulation model. To validate the modeling procedure, experimental implementation is done in TMS320F2812 DSP platform with a custom built five-phase drive system. Excitation, acceleration and loading transients are investigated. The developed simulation model is fully verified by the real time implementation.

 KEYWORDS:

1.      Five-phase drive

2.      V/f control

3.      Induction motor

 SOFTWARE: MATLAB/SIMULINK

 BLOCK  DIAGRAM:

 

Fig. 1. Constant V/F control scheme for a five-phase drive.

   EXPERIMENTAL RESULTS:

 

Fig. 2. Speed response for open-loop constant v/f control at no-load.

Fig. 3. Speed response for constant v/f control at rated load operating at

1500rpm

Fig. 4.(a) Speed response of a five-phase IM for open loop constant v/f

control at no-load (three step rising and one step fall).

 

Fig. 4.(b) Speed response of a five-phase IM for open loop constant v/f

control at no-load(step rising)

Fig. 5. Speed response of a five-phase IM for open loop constant v/f

control at rated load operating at 1500rpm

 

Fig. 6. Speed response for closed-loop constant v/f control of a five-phase

Induction motor.

 

CONCLUSION:

This paper presents a complete simulation model to simulate a five-phase induction motor drive system for constant v/f speed control method. The simulation model is developed using simpower system block sets of the Matlab/Simulink software. Step by step model development is elaborated. Dead banding in the simulation procedure is presented. A detailed simulation results are presented to validate the modeling procedure. Experimental set up is discussed and the experimental results are provided to exactly match the results obtained using simulation. This proves the successful implementation of the control scheme.

 REFERENCES:

[1] D. Novotony, and T.A. Lipo, Vector control and dynamics of ac drives, Clarendon Press, Oxford, UK, 2000.

[2] A.M. Trzynadlowski, The field oriented Principle in Control of Induction motors, Kuluwer Press, 1994.

[3] I. Boldea and S.A. Nasar, Vector Control of AC Drives, CRC Press, London, 1992.

[4] D.C. White and H.H. Woodson, Electromechanical energy conversion, John Wiley and Sons, New York, 1959.

[5] S.A. Nasar and I. Boldea, The Induction Machine Handbook, CRC Press, London, 2002.

Control of Solar Photovoltaic Integrated Universal Active Filter Based on Discrete Adaptive Filter

ABSTRACT:  

In this work, a novel technique based on adaptive filtering is proposed for the control of three phase universal active power filter with a solar photovoltaic array integrated at its DC bus.  Two adaptive filters along with a zero crossing detection technique, are used to extract the magnitude of fundamental active component of distorted load currents, which is then used in estimation of reference signal for the shunt active filter. This technique enables extraction of active component of all three phases with reduced mathematical computation. The series active filter control is based on synchronous reference frame theory and it regulates load voltage and maintains it in-phase with voltage at point of common coupling under conditions of voltage sag and swell. The performance of the system is evaluated on an experimental prototype in the laboratory under various dynamic conditions such as sag and swell in voltage at point of common coupling, load unbalancing and change in solar irradiation intensity.

KEYWORDS:

1.      Power quality

2.      Universal active power filter

3.      Adaptive filtering

4.      Photovoltaic system

5.      Maximum power point tracking

6.      Quadrature signal generation

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig. 1. System Configuration of Solar Photovoltaic Integrated Unified Active

Power Filter

EXPERIMENTAL RESULTS:

Fig. 2. Salient Signals in Extraction of Fundamental Positive Sequence Load

Current using Adaptive Filter

Fig. 3. Salient Signals in Series Active Filter Control

Fig. 4. Steady State Per Phase Signals of PCC and Load Side in a PV-UAPF Compensated System

Fig. 5. PV-UAPF Response under Nominal Condition

Fig. 6. PV-UAPF Response under Sag Condition

Fig. 7. PV-UAPF Response under Swell Condition

Fig. 8. PV-UAPF Response under Voltage Sag/Swell Condition at PCC

Fig. 9. PV-UAPF Response under Load Unbalancing Condition

Fig. 10. PV-UAPF Operation During Change in Solar Irradiation

CONCLUSION:

The performance of adaptive filter based PV-UAPF system under both steady state and dynamic conditions, have been analyzed in detail. The method of sampling the fundamental component of load current obtained through adaptive filter enables fast extraction of fundamental active component of  nonlinear load currents for all phases in one sampling. Only two adaptive filters are required to extract magnitude of active component of three phase load currents. This technique requires reduced computational resources while achieving good dynamic and steady state performance in extraction of fundamental active component of nonlinear load current. The system performance has been found to be satisfactory under various disturbances in load current, PCC voltage and solar irradiation. The series active filter is able to regulate load voltage at 220 V under variations of PCC voltage from 170 V to 270 V. The grid  current THD is maintained at approximately 3% even though  the THD of load current is 28% thus meeting requirement of IEEE-519 standard. The PV-UAPF system has been able to maintain the grid currents balanced under unbalanced loading condition.

The proposed topology and algorithm are suited for employing in conditions where PCC voltage sags/swells and load current harmonics are major power quality issues. Certain power quality issues not addressed include voltage distortions, flicker, neutral current compensation etc. This power quality issues can be addressed by modification of topology and control algorithm according to the requirements in the distribution system.

The PV-UAPF system provides dual benefit of distributed generation as well as improving power quality of the distribution system.

 REFERENCES:

[1] N. R. Tummuru,M. K. Mishra, and S. Srinivas, “Dynamic energy management of hybrid energy storage system with high-gain pv converter,” IEEE Transactions on Energy Conversion, vol. 30, no. 1, pp. 150–160, March 2015.

[2] B. Singh, A. Chandra, K. A. Haddad, Power Quality: Problems and Mitigation Techniques. London: Wiley, 2015.

[3] S. Devassy and B. Singh, “Control of solar photovoltaic integrated upqc operating in polluted utility conditions,” IET Power Electronics, vol. 10, no. 12, pp. 1413–1421, Oct 2017.

[4] S. Devassy and B. Singh, “Performance analysis of proportional resonant and adaline-based solar photovoltaic-integrated unified active power filter,” IET Renewable Power Generation, vol. 11, no. 11, pp. 1382– 1391, 2017.

[5] L. Ramya and J. Pratheebha, “A novel control technique of solar farm inverter as pv-upfc for the enhancement of transient stability in  power grid,” in 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS), Feb 2016, pp. 1–7.

A Comparative Study of Energy Management Schemes for a Fuel-Cell Hybrid Emergency Power System of More-Electric Aircraft

ABSTRACT:  

This paper presents a comparative analysis of different energy management schemes for a fuel-cell-based emergency power system of a more-electric aircraft. The fuel-cell hybrid system considered in this paper consists of fuel cells, lithium-ion batteries, and supercapacitors, along with associated dc/dc and dc/ac converters. The energy management schemes addressed are state of the art and are most commonly used energy management techniques in fuel-cell vehicle applications, and they include the following: the state machine control strategy, the rule-based fuzzy logic strategy, the classical proportional–integral control strategy, the frequency decoupling/fuzzy logic control strategy, and the equivalent consumption minimization strategy. The main criteria for performance comparison are the hydrogen consumption, the state of charges of the batteries/supercapacitors, and the overall system efficiency. Moreover, the stresses on each energy source, which impact their life cycle, are measured using a new approach based on the wavelet transform of their instantaneous power. A simulation model and an experimental test bench are developed to validate all analysis and performances.

KEYWORDS:

1.      Batteries

2.      Dc–dc converters

3.      Energy management

4.      Fuel cells

5.      Hybridization

6.      Optimization

7.      Supercapacitors

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1 Proposed system block diagram using AFLC

 EXPERIMENTAL RESULTS:

Fig. 2. DC/DC converter model validation. (a) Fuel-cell boost converter. (b) Battery boost converter. (c) Battery buck converter.

Fig. 3 DC/AC converter model validation.

Fig. 4. Simulation and experimental results for all EMS schemes. (a) Simulation results for state machine control. (b) Experimental results for state machine

control. (c) Simulation results for rule-based fuzzy logic. (d) Experimental results for rule-based fuzzy logic. (e) Simulation results for classical PI control.

(f) Experimental results for classical PI control. (g) Simulation results for frequency decoupling and fuzzy logic. (h) Experimental results for frequency decoupling

and fuzzy logic. (i) Simulation results for ECMS. (j) Experimental results for ECMS.

CONCLUSION:

This paper has presented a performance comparison of different energy management schemes for a fuel-cell hybrid emergency system of MEA. The hybrid system is modeled and  validated with experiments. Five state-of-the-art commonly used energy management schemes are studied through simulations and experimental tests on a 14-kW fuel-cell hybrid  system. The same initial condition is used for all the schemes, and the experimental results are close to simulations. The criteria for performance comparison are the hydrogen consumption, the battery SOC, the overall efficiency, and the stress seen by each energy source. The latter is measured using a new approach based on wavelet transform. Compared with the other schemes, the state machine control scheme provided slightly better efficiency (80.72%) and stresses on the battery  and supercapacitor (σ of 21.91 and 34.7, respectively). The classical PI control scheme had the lowest fuel consumption (235 g of H2 consumed) and more use of the battery energy (SOC between 70%–51%). As expected, the lowest fuel-cell stress (σ of 12.04) and the lowest use of the battery energy (SOC between 70%–59%) were achieved with the frequency decoupling and fuzzy logic scheme but at the expense of more fuel consumption (245 g of H2 consumed) and lower overall efficiency (79.32%). The dc-bus or supercapacitor voltage was maintained nearly constant (≈270 Vdc) for all the schemes. To conclude, the energy management system suitable for MEA should be a multischeme EMS, such that each scheme is chosen based on a specific criterion to prioritize. As an example, depending on the operating life of each energy source, the EMS can be chosen to either minimize the stress on the fuelcell system, the battery system, or the supercapacitor system, hence maximizing the life cycle of the hybrid power system. In addition, if the target is to reduce the fuel consumption, the strategy based on the classical PI or ECMS could be selected. An alternative is to design a multiobjective optimization EMS  to optimize all the performance criteria, which is the next topic for further studies.

REFERENCES:

[1] P. Thounthong and S. Rael, “The benefits of hybridization,” IEEE Ind. Electron. Mag., vol. 3, no. 3, pp. 25–37, Sep. 2009.

[2] P. Thounthong, S. Rael, and B. Davat, “Control strategy of fuel cell and supercapacitors association for a distributed generation system,” IEEE  Trans. Ind. Electron., vol. 54, no. 6, pp. 3225–3233, Dec. 2007.

[3] Z. Amjadi and S. Williamson, “Power-electronics-based solutions for plug-in hybrid electric vehicle energy storage and management systems,” IEEE Trans. Ind. Electron., vol. 57, no. 2, pp. 608–616, Feb. 2010.

[4] G. Renouard-Vallet, M. Saballus, G. Schmithals, J. Schirmer, J. Kallo, and A. K. Friedrich, “Improving the environmental impact of civil aircraft  by fuel cell technology: Concepts and technological progress,” Energy  Environ. Sci., vol. 3, no. 10, pp. 1458–1468, 2010.

[5] G. Renouard-Vallet, M. Saballus, G. Schmithals, J. Schirmer, J. Kallo, and A. K. Friedrich, “Fuel cells for aircraft applications,” ECS Trans., vol. 30, no. 1, pp. 271–280, 2011.

Control and operation of a solar PV-battery grid-tied system in fixed and variable power mode

ABSTRACT:  

In this work, a simple phase-locked loop – less control is presented for a single-stage solar photovoltaic (PV) – battery-grid-tied system. As compared to traditional solar PV systems, the system has reduced losses due to the absence of boost converter and a flexible power flow due to the inclusion of a storage source (battery). The synchronous reference frame theory is used to generate the pulses for switching the voltage-source converter (VSC), while maximum power is extracted from the solar PV array by using perturb and observe-based maximum power point tracking technique. The inherent feature of shunt active filtering by the VSC has also been incorporated in this system. Test results for the system operation under fixed power and variable power mode are studied on a prototype developed in the laboratory. During fixed power mode, a fixed amount of power is fed to the grid, whereas in variable power mode the power fed to the grid varies. Test results obtained are in accordance with the IEEE-519 standard. This work is a basis for the upcoming power market, where solar PV consumers can manage the generated electricity and maximise their profit by selling the power to the grid judiciously.

SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:

Fig.1 Proposed topology

EXPERIMENTAL RESULTS:

Fig. 2 Performance of the system at steady state under fixed power mode

(b) vgab, iga, ila and iaspv, (c) Vdc, Ipv, Vbat and Ibat

Fig. 3 Impact of a decrease in load and insolation level during fixed power mode

(a)     vgab, iga, ila and iaspv, (b) Vdc, Ipv, Vbat and Ibat. Impact of a decrease in solar insolation during fixed power mode (c) vgab, iga, Ipv and iaspv, (d) Vdc, Ipv, Vbat and Ibat

Fig. 4 Impact of increase in solar insolation during fixed power mode

(a)     vgab, iga, Ipv and iaspv, (b) Vdc, Ipv, Vbat and Ibat. Performance of the system at steady state under variable power mode

Fig. 5 Performance of the system at steady state under variable power mode

 (d) Grid power

Fig. 6 Impact of load unbalancing and solar variations on solar PV-battery-grid-tied system

(a)     vgab, igc, ilc and icspv, (b) Vdc, Ipv, Vbat and Ibat. Impact of solar variation on solar PV-battery-grid-tied system (c) vgab, iga, ila and Ipv, (d) Vpv, Vbat, Ibat and iaspv

Fig. 7 Impact of solar variation and battery disconnection on solar PV-battery-grid-tied system

 (c) vgab, iga, ila and iaspv, (d) Vdc, Ipv, Vbat and Ibat

CONCLUSION:

A solar PV-battery-grid-tied system has been implemented in this work. P&O-based MPPT technique has been used to extract maximum power from the solar PV array, while SRF theory has been used to control the VSC. No PLL has been used here, the grid voltage vector angle with the α-axis, has been utilised to obtain the reference grid currents. The system's operation under fixed power mode is analysed, wherein a fixed amount of power is fed to the grid irrespective of the insolation and load variation. The battery gets charged/discharged in order to adjust these variations. Moreover, during the variable power mode, under load disconnection and solar insolation increase, the power fed to the grid increases. Even if the battery gets disconnected, the power generated by the solar PV array is fed to the grid and the load without any issue. Moreover, all these test results obtained are in accordance to an IEEE-519 standard.

REFERENCES:

[1] Esram, T., Chapman, P.L.: ‘Comparison of photovoltaic array maximum power point tracking techniques,’ IEEE Trans. Energy Convers., 2007, 22, (2), pp. 439–449

[2] Deshpande, A., Patil, S.L., Deopare, H.: ‘Comparative simulation of conventional maximum power point tracking methods’. Proc. Int. Conf. Computing, Communication and Automation (ICCCA), 2016, pp. 1025–1028

[3] Sahu, H.S., Nayak, S.K.: ‘Numerical approach to estimate the maximum power point of a photovoltaic array,’ IET Gener. Transm. Distrib., 2016, 10, (11), pp. 2670–2680

[4] Libo, W., Zhengming, Z., Jianzheng, L.: ‘A single-stage three-phase grid connected  photovoltaic system with modified MPPT method and reactive power compensation,’ IEEE Trans. Energy Convers., 2007, 22, (4), pp. 881– 886

[5] Jain, S., Agarwal, V.: ‘A single-stage grid connected inverter topology for solar PV systems with maximum power point tracking,’ IEEE Trans. Power Electron., 2007, 22, (5), pp. 1928–1940