A Voltage Regulator for Power Quality Improvement in Low-Voltage Distribution Grids

ABSTRACT:

This paper presents a voltage-controlled DSTATCOM-based voltage regulator for low voltage distribution grids. The voltage regulator is designed to temporarily meet the grid code, postponing unplanned investments while a definitive solution could be planned to solve regulation issues. The power stage is composed of a three-phase four-wire Voltage Source Inverter (VSI) and a second order low-pass filter. The control strategy has three output voltage loops with active damping and two dc bus voltage loops. In addition, two loops are included to the proposed control strategy: the concept of Minimum Power Point Tracking (mPPT) and the frequency loop. The mPPT allows the voltage regulator to operate at the Minimum Power Point (mPP), avoiding the circulation of unnecessary reactive compensation. The frequency loop allows the voltage regulator to be independent of the grid voltage information, especially the grid angle, using only the information available at the Point of Common Coupling (PCC). Experimental results show the regulation capacity, the features of the mPPT algorithm for linear and nonlinear loads and the frequency stability.

KEYWORDS:

1.      DSTATCOM

2.      Frequency Compensation

3.      Minimum Power Point Tracker

4.      Power Quality

5.      Static VAR Compensators

6.      Voltage Control

7.      Voltage Regulation

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 Fig. 1. Low voltage distribution grid under analysis with the voltage regulator

EXPECTED SIMULATION RESULTS:

Fig. 2. Dc bus voltages during the DSTATCOM initialization

Fig. 3. PCC voltages without compensation for linear loads

Fig. 4. PCC voltages with compensation for linear loads

Fig. 5. Voltage regulator currents for linear loads

Fig. 6. Grid, load and voltage regulator currents for linear loads

Fig. 7. PCC voltages without compensation for nonlinear loads

Fig. 8. PCC voltages with compensation for nonlinear loads

Fig. 9. Voltage regulator currents for nonlinear loads

Fig. 10. Grid, load and voltage regulator currents for nonlinear loads

Fig. 11. PCC rms value with linear loads

Fig. 12. Processed apparent power with linear loads

Fig. 13. Voltage regulator currents with mPPT enabled for linear loads

Fig. 14. PCC rms value with nonlinear loads

Fig. 15. Processed apparent power with nonlinear loads

Fig. 16. Voltage regulator currents with mPPT enabled for nonlinear loads

Fig. 17. Total dc bus voltage, PCC voltage, grid voltage and voltage regulator current waveforms of a-phase with mPPT enabled with grid swell

Fig. 18. (a) Total dc bus voltage, PCC voltage, grid voltage and voltage regulator current waveforms of a-phase and (b) detail of total dc bus voltage performance with mPPT enabled with grid sag

CONCLUSION:

This paper presents a three phase DSTATCOM as a voltage regulator and its control strategy, composed of the conventional loops, output voltage and dc bus regulation loops, including the voltage amplitude and the frequency loops.

Experimental results demonstrate the voltage regulation capability, supplying three balanced voltages at the PCC, even under nonlinear loads.

The proposed amplitude loop was able to reduce the voltage regulator processed apparent power about 51 % with nonlinear load and even more with linear load (80%). The mPPT algorithm tracked the minimum power point within the allowable voltage range when reactive power compensation is not necessary. With grid voltage sag and swell, the amplitude loop meets the grid code. The mPPT can also be implemented in current-controlled DSTATCOMs, achieving similar results.

The frequency loop kept the compensation angle within the analog limits, increasing the autonomy of the voltage regulator, and the dc bus voltage regulated at nominal value, thus minimizing the dc bus voltage steady state error. Simultaneous operation of the mPPT and the frequency loop was verified.

The proposed voltage regulator is a shunt connected solution, which is tied to low voltage distribution grids without any power interruption to the loads, without any grid voltage and impedance information, and provides balanced and low-THD voltages to the customers.

REFERENCES:

[1] ANEEL National Electric Power Distribution System Procedures – PRODIST, Module 8: Energy Quality. Revision 07, 2014.

[2] M. Mishra, A. Ghosh and A. Joshi, “Operation of a DSTATCOM in voltage control mode,” IEEE Trans. Power Del., vol. 18, no. 1, pp. 258-264, Jan. 2003.

[3] G. Ledwich and A. Ghosh, “A flexible DSTATCOM operating in voltage or current control mode,” IEE Proc.-Gener., Transmiss. Distrib., vol. 149, n. 2, pp. 215-224, Mar. 2002.

[4] T. P. Enderle, G. da Silva, C. Fischer, R. C. Beltrame, L. Schuch, V. F. Montagner and C. Rech, “D-STATCOM applied to single-phase distribution networks: Modeling and control,” in Proc. IEEE Ind. Electron. Soc. Annu. Conf., Oct. 2012, pp. 321 - 326.

[5] C. Kumar and M. Mishra, “Energy conservation and power quality improvement with voltage controlled DSTATCOM,” in Proc. Annu. IEEE India Conf., Dec. 2013 pp. 1-6.

A Power Quality Improved Bridgeless Converter-Based Computer Power Supply

ABSTRACT:

Poor power quality, slow dynamic response, high device stress, harmonic rich, periodically dense, peaky, distorted input current are the major problems that are frequently encountered in conventional switched mode power supplies (SMPSs) used in computers. To mitigate these problems, it is proposed here to use a nonisolated bridgeless buck-boost single-ended primary inductance converter (SEPIC) in discontinuous conduction mode at the front end of an SMPS. The bridgeless SEPIC at the front end provides stiffly regulated output dc voltage even under frequent input voltage and load variations. The output of the front end converter is connected to a half-bridge dc–dc converter for isolation and also for obtaining different dc voltage levels at the load end that are needed in a personal computer. Controlling a single output voltage is able to regulate all the other dc output voltages as well. The design and simulation of the proposed power supply are carried out for obtaining an improved power quality that is verified through the experimental results.

KEYWORDS:

1.      Bridgeless converter

2.      Computer power supply

3.      Input current

4.      Power factor correction (PFC)

5.      Power quality

SOFTWARE: MATLAB/SIMULINK

SCHEMATIC  DIAGRAM:

Fig. 1. Schematic diagram of the PFC converter based SMPS.

EXPECTED SIMULATION RESULTS:

Fig. 2. (a) Performance of the computer power supply at rated condition. (b) Input current and its harmonic spectrum at full load condition. (c)Waveform across various components of the bridgeless converter.

Fig. 3. (a) Performance of the computer power supply at light load condition.

(b) Input current and its harmonic spectrum at light load condition.

CONCLUSION:

A bridgeless nonisolated SEPIC based power supply has been proposed here to mitigate the power quality problems prevalent in any conventional computer power supply. The proposed power supply is able to operate satisfactorily under wide variations in input voltages and loads. The design and simulation of the proposed power supply are initially carried to demonstrate its improved performance. Further, a laboratory prototype is built and experiments are conducted on this prototype. Test results obtained are found to be in line with the simulated performance. They corroborate the fact that the power quality problems at the front end are mitigated and hence, the proposed circuit can be a recommended solution for computers and other similar appliances.

REFERENCES:

[1] D. O. Koval and C. Carter, “Power quality characteristics of computer loads,” IEEE Trans. Ind. Appl., vol. 33, no. 3, pp. 613–621, May/Jun. 1997.

[2] A. I. Pressman,K.Billings, and T. Morey, Switching Power SupplyDesign, 3rd ed. New York, NY, USA: McGraw Hill, 2009.

[3] B. Singh, B. N. Singh, A. Chandra, K. Al-Haddad, A. Pandey, and D. P. Kothari, “A review of single-phase improved power quality AC-DC converters,” IEEE Trans. Ind. Electron., vol. 50, no. 5, pp. 962–981, Oct. 2003.

[4] K. Mino, H. Matsumoto, Y. Nemoto, S. Fujita, D. Kawasaki, R. Yamada, and N. Tawada, “A front-end converter with high reliability and high efficiency,” in Proc. IEEE Conf. Energy Convers. Congr. Expo., 2010, pp. 3216–3223.

[5] J.-S. Lai, D. Hurst, and T. Key, “Switch-mode supply power factor improvement via harmonic elimination methods,” in Proc. IEEE 6th Annu. Appl. Power Electron. Conf. Expo., 1991, pp. 415–422.

An Intelligent Speed Controller for Indirect Vector Controlled Induction Motor Drive

ABSTRACT:

This paper presents the speed control scheme of indirect vector controlled induction motor (IM) drive. PWM controlling scheme is based on Voltage source inverter type space vector pulse width modulation (SVPWM) and the Conventional-PI controller or Fuzzy-PI controller is employed in closed loop speed control. Decoupling of the stator current into torque and flux producing (d-q) current components model of an induction motor is involved in the indirect vector control. The torque component Iq current of an IM is developed by an intelligent based Fuzzy PI controller. Based on settling time and dynamic response the performance of Fuzzy Logic Controller is compared with that of the PI Controller to sudden load changes. It’s provides better control of motor torque with high dynamic performance. The simulated design is tested using various tool boxes in MATLAB. Simulation results of both the controllers are presented for comparison.

KEYWORDS:

1.      Indirect Vector Control (IVC)

2.      Space Vector Pulse Width Modulation (SVPWM)

3.      PI Controller

4.      Fuzzy Logic Controller (FLC)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 Block diagram of a proposed scheme

EXPECTED SIMULATION RESULTS:

Fig.2 Starting response

Fig.3 Step response

Fig.4 Speed response for with and without load impact

Fig.5 Torque response for with and without load impact

CONCLUSION:

In this paper the concept of fuzzy logic has been presented and the SVM based indirect vector controlled induction motor drive is simulated using both PI and Fuzzy PI controller. The results of both controllers under the dynamics conditions are compared and analyzed. The simulation result support that the FLC settles quickly and has better performance than when PI controller.

REFERENCES:

[1] Bimal K.Bose, “Modern Power Electronics and AC Drives”, Pearson education.

[2] Leonhand.W, ‘Control of Electrical Drives’, Springer Verlag 1990.

[3] Yang Li Yinghong, Chen Yaai and Li Zhengxi “A Novel Fuzzy Logic Controller for Indirect Vector Control Induction Motor

[4] Drive” Proceeding of the 7th World Congress on Intelligent and Automation Jun 25 – 27, 2008, Chongqing,China, pp. 24-28

[5] R.A. Gupta, Rajesh Kumar, S.V.Bhangale “Indirect Vector Controlled Induction Motor Drive with Fuzzy Logic based Intelligent Controller”, ICTES,UK,December 2007,pp.368-373.

Fuzzy Efficiency Enhancement of Induction Motor Drive

ABSTRACT:

Efficiency improvement of motor drives is important not only from the viewpoints of energy loss and hence cost saving, but also from the perspective of environmental pollution. Several efficiency optimization methods for induction motor (IM) drives have been introduced nowadays by researchers. Distinctively, artificial intelligence (AI)-based techniques, in particular Fuzzy Logic (FL) one, have been emerged as a powerful complement to conventional methods. Design objectives that are mathematically hard to express can be incorporated into a Fuzzy Logic Controller (FLC) using simple linguistic terms. The merit of FLC relies on its ability to express the amount of ambiguity in human reasoning. When the mathematical model of a process does not exist or exists with uncertainties, FLC has proven to be one of the best alternatives to move with unknown process. Even when the process model is well-known, there may still be parameter variation issues and power electronic systems, which are known to be often approximately defined.

The purpose of this paper is to demonstrate that a great efficiency improvement of motor drive can be achieved and hence a significant amount of energy can be saved by adjusting the flux level according to the applied load of an induction motor by using an on-line fuzzy logic optimization controller based on a vector control scheme. An extensive simulation results highlight and confirm the efficiency improvement with the proposed algorithm.

KEYWORDS

1.      Induction Motor Drive

2.      Indirect Field Oriented Control (IFOC)

3.      Efficiency Enhancement

4.      Losses Minimization

5.      Optimization

6.      Fuzzy Logic

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1, Block diagram of the optimization system

EXPECTED SIMULATION RESULTS:

Fig.2, Motor Performances Comparison

Fig.3, Motor efficiency evolution with motor load

CONCLUSION:

This paper aims to improve the induction motor drive efficiency that leads to a significant amount of energy saving. This efficiency enhancement is carried out by adjusting the flux level depending on the applied load of an induction motor by using an on-line fuzzy logic optimization controller based on a vector control scheme. A series of the induction motor drive performances are obtained with a variable load under this proposed algorithm. The application of the proposed algorithm yields to a series of simulation performances of the induction motor drive with a variable load. They present the IM drive efficiency evolution with a certain load profile with the suggested losses minimization strategy based on fuzzy control and the conventional field oriented control. The comparison between these two control schemes reveals that the achieved results are of a great interest. Indeed, the fuzzy control contributes with a great deal to the efficiency improvement for all operating speeds particularly in light load region. This contribution conducts to a paramount energy saving and hence to environment protection.

REFERENCES:

[1] I. Boldea, A. Nasser, The Induction Machine Design Handbook, CRC Press Inc; 2nd Revised Edition, 2009.

[2] Jinchuan. Li and all, “A new Optimization Method on Vector Control of Induction Motors”, Electric Machines and Drives, 2005 IEEE International Conference, 15-18 May 2005, pp.1995-2001.

[3] H. Sepahv and, Sh. Ferhangi, “Enhancing Performance of a Fuzzy Efficiency Optimizer for Induction Motor Drives”, Power Electronics Specialists Conference, 2006. PESC '06. 37th IEEE, 18-22 June.2006, pp.1-5.

[4] Branko Blanusa and all, “An Improved Search Based Algorithm for Efficiency Optimization in the Induction Motor Drives”, XLII Konferencija- za ETRAN, Hercy-Novi, 2003.

[5] D. S. Kirischen, D. W. Novoty and T. A. Lipo, “Optimal Efficiency Control of an Induction Motor Drive”, IEEE Transaction on Energy Conversion, Vol. EC-2, N° 1, March 1987, pp.70-76.

Efficiency Optimization of Induction Motor Drive in Steady- State using Artificial Neural Network

ABSTRACT:

Induction motors have good efficiency at rated conditions, but at partial loads if operated with rated flux, they show poor efficiency, Motors in such conditions waste a lot of electricity, results in increased operational cost, hence significant loss of revenue, if run for long duration, Because of robustness, good power/mass relation, low cost and easy maintenance throughout its life cycle, induction motors, particularly squirrel cage induction motors are vastly used in industries. Because of the huge number of operational units worldwide, they consume a considerable amount of electrical energy, so even a minute efficiency improvement may lead to significant contributions in global electricity consumption, revenue saving and other environmental aspects. This paper uses key concepts of loss model control (LMC) and search control (SC) together for efficient operation of induction motors used in various industrial applications, where aforesaid load conditions may occur for prolonged durations. Based on the induction motor loss model in d-q frame, and using classical optimization techniques, done earlier, an optimal Ids expression in terms of machine parameters and load parameters is used to estimate optimal Ids values for various load conditions, offline, and finally tabulated. Based on which, an artificial neural network (ANN) controller is designed, taking torque and speed as input and Ids as output. The ANN controller reproduces the optimal Ids * value, as per load conditions, in feed-forward manner, and thus eliminates run-time computations and perturbations for optimal flux. The ANN training is performed in MATLAB and the results have shown the superb accuracy of the model. Dynamic and steady-state performances are compared for conventional vector control (constant Ids) and proposed optimal control (optimal Ids) operations. Excellent dynamic as well as superior efficiency performance (1-18%) at steady- state, is observed in optimal flux operation, for load torque above 60% of rated, in simulation, for a wide range of speed, by the proposed method. Also, the method is easy to implement for real - time industrial facilities, fast response, ripple free operations, and offers higher energy savings ratio as compared to useful output power, in comparison with similar works done earlier.

KEYWORDS:

1. Energy-efficiency
2. Induction motor drive
3. Vector control
4. Optimal control
5. Efficiency optimization
6. ANN

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig. 1(a). MATLAB model for efficiency validation, (b) Id,* values at different speeds

EXPECTED SIMULATION RESULTS:

Fig. 2(a) Efficiency- vs- Load-Torque at 120 rad/s, (b) %age Power saving - vs- Speed

Fig. 3. Speed, Torque, Input power and Efficiency performance at for a load cycle of (150 N -m, 120 radls) for 4 sec, (200 N -m, 150 rad/s) for 3 sec, and (150 Nm, 90 rad/s) for 3 sec.

Fig. 4. Switching state performances at sample 120 rad/sec speed at a load cycle of 16 seconds.

CONCLUSION:

In this work, it is verified that the optimal flux operation is superior to that of vector control method under steady - state condition, in terms of efficiency enhancement and hence energy-saving. In general 1 - 18% efficiency improvement is observed on 50 HP, 60 Hz motor, at different load-torques (above 60%) and speeds, in Simulink environment. Efficiency improvement margin is seen degraded below 60% of rated load, and conventional vector control performs better. This can be seen as shortcoming of proposed method. The dynamic performance is seen satisfactory, similar to vector control or even better, in terms of overshoot, undershoot and settling time, speed and torque tracking accuracy is little bit deviated, but still the proposed approach is extremely suitable for such an application where maintaining speed and torque very precisely is not a critical issue, such as an induction motor drive used in an industrial HV AC applications [7, Bose 2004]. A lot of electricity can be saved with this minute compromise in speed and torque accuracy, since it offers higher amount of energy savings as compared to existing methods, hence a great contribution towards social and environmental aspects. The proposed method can be easily implemented on other induction motor drive systems also, for which the steady-state speed-vs.torque load characteristics are already known or can be predicted. The offline optimization as done here, is a limitation, as the optimal flux trajectories are only valid for one specific application, can also be considered as drawback. But, the proposed hybrid approach eliminates the need of run-time computation complexity in traditional loss model controller (LMC), so less hardware installations required in implementation, hence cost-effective. Also, since no run-time perturbations happening as it usually happen in conventional search control (SC), so no torque ripples, hence less wear and tear of induction motor drive.

REFERENCES:

[1] A. H. M. Yatim and W. M. Utomo, "To develop an efficient variable speed compressor motor system," Universiti Teknologi Malaysia (UTM), Skudai, Malaysia, 2007.

[2] R. Hanitsch, "Energy efficient electric motors," University of Technology, Berlin, Germany, 2000. 

[3] Y. Yakhelef, "Energy efficiency optimization of induction motors," Boumerdes University, Boumerdes, Algeria, 2007.

[4] M. W. Turner, V. E. McCormick and J. G. Cleland, Efficiency optimization control of AC induction motors: Initial laboratory results, United States Environmental Protection Agency, Research and Development, National Risk Management Research Laboratory, 1996.

[5] T. Fletier, W. Eichhammer and 1. Schleich, "Energy efficiency in electric motor systems: Technical potentials and policy approaches for developing countries," United Nations Industrial Development, Vienna, 2011.

Efficiency Optimization of Induction Motor Drive at Steady-State Condition

ABSTRACT: 

Induction motors are workhorse of industries due to its power/mass relation, efficiency, low cost and nearly maintenance free operation in its life cycle. However motors with low efficiency waste a lot of energy that will increase its operational cost. As a result of high energy consumption and the huge number of operating units, even a small increase in efficiency improvement has significant effect on the entire energy consumptions and operational cost. This paper uses key features ofloss model control (LMC) and search control (SC) together for estimation and reproduction of optimal flux component of current (Ids), for optimal efficiency operation of induction motor. At first, a d-q loss model of induction motor is used to derive a loss-minimization expression considering core saturation. The loss expression is used to derive optimalIds expression and then Ids is estimated for various load profiles and finally tabulated. Based on those tabulated values, a look-up table in MATLAB is designed, and thus optimal Ids* value can be reproduced, depending upon run-time load profile, in feed-forward manner, and thus eliminates run-time loss model complex computation. Efficiency is compared for conventional vector control (constant Ids) and proposed optimal control (optimal Ids) operations. Superior efficiency performance (1-18%) is observed in optimal flux operation at steady-state, for load torque above 60% in simulation, for wide range of speed. The proposed hybrid concept is easy to implement, run-time computation free operation, ripple free operation, and offers higher power saving ratio with respect to useful output power.

KEYWORDS:
1. Induction motor drive
2. Efficiency optimization
3. Vector control
4. Optimal control
5. Look-up table

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1. MATLAB model for efficiency validation

EXPECTED SIMULATION RESULTS:

Fig. 2. Speed, Torque and Efficiency perfonnance at (a) at rated load torque (200N-m) at 120 radis speed, 12% efficiency rise, (b) at 3/4th rated load torque (150Nm) at 120 radis speed, 5% efficiency rise

Fig 3. Ids* values at different speeds

Fig. 4  Efficiency- vs- Load-Torque at 120 radis, (b) Efliciency- vs- Speed

Fig. 5 Input Power- vs- Speed, (b) %age power saving- vs- speed

CONCLUSION:

In this work, it is verified that the optimal flux operation is superior to that of vector control method under steady - state condition, in terms of efficiency enhancement and hence energy-saving. In general I - 18% improvement is observed on 50 HP, 60 Hz motor, at different load-torques (above 60%) and speeds, in simulink environment. Efficiency improvement margin is seen degraded below 60% of rated load, and conventional vector control performs better. This can be seen as shortcoming of proposed method. The dynamic performance is seen satisfactory (similar to vector control), but speed and torque tracking accuracy is degraded a bit, but still the proposed approach is extremely suitable for such an application where maintaining speed and torque very precisely is not a critical issue, such as an induction motor drive used in an industrial HV AC applications. A lot of electricity can be saved with this minute compromise in speed and torque, since it offers higher amount of energy savings as compared to existing methods, hence a great contribution towards social and environmental aspects. The proposed method can be easily implemented on other induction motor drive systems also, for which the steady-state speed-vs.-torque load characteristics are already known or can be predicted. Also, the proposed hybrid approach eliminates the need of runtime computation complexity in traditional loss model controller (LMC), so less hardware installations required in implementation, hence cost-effective. Also, since no runtime perturbations happening as it usually happen in conventional search control (SC), so no torque ripples, hence less wear and tear of induction motor drive.

 REFERENCES:

[I] A. H. M. Yatim and W. M. Utomo, "To develop an efficient variable speed compressor motor system," universiti teknologi Malaysia (UTM), Skudai, Malasia, 2007.

[2] R. Hanitsch, "Energy efficienct electric motors," university of technology berlin, germany, 2000.

[3] Y. Yakhelet: "Energy efficiency optimization of induction motors," Boumerdes University, Boumerdes, Algeria, 2007.

[4] M. W. Turner, V. E. McCormick and 1. G. Cleland, Efficiency optimization control of AC induction motors: Initial laboratory results, United States Environmental Protection Agency, Research and Development, National Risk Management Research Laboratory, 1996.

[5] T. Fletier, W. Eichhammer and 1. Schleich, "Energy efficiency in electric motor systems: Technical potentials and policy approacehs fir developing countries," United Nations Industrila Development, Vienna,2011.