Performance Improvement of DVR by Control of Reduced-Rating with A Battery Energy Storage

ABSTRACT:

Voltage injection methods for DVRs (Dynamic Voltage Restorers) and operating modes are resolved in this paper. Using fuzzy logic control DVR with dc link& with BESS systems are operated. Power quality problems mainly harmonic distortion, voltage swell & sag are decreased with DVR using Synchronous Reference Theory (SRF theory) with the help of fuzzificaton waveforms are observed.

KEYWORDS:

1.      Dynamic Voltage Restorer

2.      Unit Vector

3.      Power quality

4.      Harmonic distortion

5.      Voltage Sag

6.      Voltage Swell

7.      Fuzzy logic controller

8.      Matlab/simulink software

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1.Block Diagram of DVR

 EXPECTED SIMULATION RESULTS:

Fig.2 Voltage waveforms at common coupling point (PCC) and load during harmonic distortion

Fig.3. the dc voltage injection from BESS connected DVR system at voltage swelling period

Fig.4. DVR waveforms during voltage sag at time of voltage in phase injection

Fig.5 Amplitude of load voltages and PCC voltages w.r.t time

Fig 6.DVR waveforms during harmonic distortion at the time of voltage in phase injection

CONCLUSION:

By applying different voltage injection schemes the role of DVR has been shown with a latest control technique. The presentation of DVR has been balanced with various schemes with a reduced-rating VSC. For getting the control of DVR, the reference load voltages have been determined with the help of unit vectors, for which the error of voltage insertion is reduced. By using SRF theory the reference DVR voltages have been determined. In the end, the result derived are that the in phase voltage insertion with PCC voltage reduces the DVR rating but at the same time at its DC bus the energy source is wasted.

REFERENCES:

[1] Math H.J. Bollen, Understanding Power Quality Problems- Voltage Sags and Interruptions, IEEE Press, New York, 2000.

[2] A. Ghosh and G. Ledwich, Power Quality Enhancement using Custom Power devices, Kluwer Academic Publishers, London, 2002

[3] Eddy C. Aeloíza, Prasad N. Enjeti, Luis A. Morán, Oscar C. Montero- Hernandez, and Sangsun Kim, “Analysis and Design of a New Voltage Sag Compensator for Critical Loads in Electrical Power Distribution Systems”, IEEE Trans. on Ind. Appl., vol. 39, no. 4, pp 1143-1150, Jul/Aug 2003.

[4] J. W. Liu, S.S. Choi and S. Chen, “Design of step dynamic voltage regulator for power quality enhancement”, IEEE Trans. on Power Delivery, vol. 18, no.4, pp. 1403 – 1409, Oct. 2003.

[5] Arindam Ghosh, Amit Kumar Jindal and Avinash Joshi, “Design of a capacitor supported dynamic voltage restorer for unbalanced and distorted loads” IEEE Trans. on Power Delivery, vol.19, no. 1, pp. 405-413, Jan 2004.

Performance Analysis of DVR, DSTATCOM and UPQC For Improving The Power Quality With Various Control Strategies

ABSTRACT:

Here, we have studied the voltage quality improvement methods by using Dynamic Voltage Restorer (DVR), Distribution Static Synchronous Compensator (D-STATCOM) and Unified Power Quality Conditioner (UPQC) using two different controller Strategies. The controllers used are Proportional Integral Controller (PIC) and Fuzzy Logic Controller (FLC). A PI Controller calculates an error value as the difference between a measured variable and desired set point. The fuzzy logic controller has real time inputs measured at every sample time, named error and error rate and one output named actuating signal for each phase. The input signals are fuzzified and represented in fuzzy set notations as functions. The defined 'If ... Then .. .' rules produce output actuating signals and these signals are defuzzified to analog control signals for comparing with a carrier signal to control PWM inverter.

KEYWORDS:

1.      Dynamic Voltage Restorer (DVR)

2.      Distribution Static Synchronous Compensator (D-STATCOM)

3.      Unified Power Quality Conditioner (UPQC)

4.      Power Quality

5.      PI Controller

6.      Fuzzy Controller and MATLAB

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig 1. The equivalent circuit diagram of DVR

Fig 2. The equivalent circuit diagram of DST A TCOM

Fig 3.The circuit diagram of UPQC

EXPECTED SIMULATION RESULTS:

Fig 4. Input voltage and input current waveform without compensation

Fig 5. Load voltage and load current waveform without compensation

Fig 6. load voltage and load current waveform after compensation(DVR)

Fig 7. Output load voltage without compensation

Fig 8. Output load voltage with compensation using FLC

Fig 9.load voltage and load current waveform after compensation (D-STATCOM)

Fig 10. Load voltage and load current waveform after compensation (D-STATCOM)

Fig 11. Load voltage and load current waveform for UPQC with PI Controller.

Fig 12 Load voltage and load current waveform with compensation

CONCLUSION:

In this paper, we have studied the series, shunt and series shunt compensators. Performance analysis has been done by comparing the power quality using each compensator. The performance of DVR has been analyzed with PI controller the load voltage during fault is almost equal to the desired load voltage. Load current magnitude is almost equal but still there are some imbalances between the phases for a small duration of time. DVR have been found to regulate voltage under Fuzzy Logic controller. It is clear that DVR reduces harmonics from load voltage very effectively and makes it smooth. Hence, it is concluded that DVR has a huge scope in improving power quality in distribution systems. DSTATCOM is proved to compensate voltage levels under faulty conditions. Using PI controller, harmonics have been reduced considerably. But current got unbalanced for the entire duration of time. By using the Fuzzy Logic Controller instead of the PI Controller gives better transient response. The DC Link voltage is suddenly increased above the reference value. And it is brought back to its reference value. A good voltage control is also achieved by implementing Fuzzy logic control. Also the steady state is reached faster. The control strategies of UPQC were described and compared with respect to its performance through simulation. The power quality issues are almost reduced. The closed loop control schemes of current control, for the proposed UPQC have been investigated. Total harmonic distortion was analyzed and it describes that the UPQC with fuzzy controller provides more efficiency than the other strategies.

 REFERENCES:

[1] Smriti De)'. Comparison of DVR and D-STATCOM for Voltage (",)uality Improvement, [JET AE (ISSN 2250- 2459), Vol 4, Issue 10, October 2014, PP 187-193.

[2] Ganeshkumar.A, Ananthan.N, Performance Comparison Of UPQC For Improving The Power Quality With Various Controllers Strategy ,IJETCSE, Vol 13 Issue 2, March2015,PP 12-17.

[3] Shipra Pandey, Dr. S.Chatterji, Ritula Thakur. Fuzzy Controlled DSTATCOM for Voltage Sag Compensation and DC-Link Voltage Improvement. [JEECS , ,Vol 3, Issue I, April 2014.

[4] C. Sankaran "Power Quality", CRC Press 2002.

[5] N.G. Hingorani and L Gyugyi, Understanding FACTS - Concepts and Technology OF Flexible AC Transmission Systems, IEEE Press, New York, 2000.

Compensation Of Voltage Sag And Harmonics By Dynamic Voltage Restorer Without Zero Sequence Blocking

 ABSTRACT:

amic Voltage Restorer (DVR) is a power electronic device to protect sensitive loads from voltage sag. Commonly, sensitive loads are electronic-based devices which generate harmonics. This paper presents fuzzy polar based DVR as voltage sag restorer and harmonics compensator without zero sequence blocking. Research presented in this paper uses d-q-0 axis method considering of the value of neutral axis, because the method works very well if the neutral axis value is zero. Result shows that this method can compensate voltage sag with a compensation error of 0.99%. Using this method, DVR may reduce voltage THD from 10.22% to 0.66%.

KEYWORDS:

1.      DVR

2.      Voltage sag

3.      Harmonics

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig.1 Dynamic voltage restorer

EXPECTED SIMULATION RESULTS:

Fig. 2 Distorted voltages at bus C

Fig. 3 Voltage at bus C after DVR

Fig.4 70% sag at bus C caused by phase-phase-ground fault

Fig.5 70% sag at bus C (caused by phase-phase- ground fault) restored by DVR

 CONCLUSION:

The simulation of a DVR using MATLAB has been presented. Simulation results show that DVR can restore both the voltage sag and voltage harmonics. The efficiency and effectiveness in voltage sag restoration and voltage harmonics compensation showed by the DVR makes it an interesting power quality device compared to other custom power devices. Under normal condition, DVR is able to decrease voltage THD from 10.22 % to 0.66%. And using the proposed method, DVR can restore asymmetrical voltage sag without zero blocking transformer. The average error of DVR voltage sag compensation is 0.99.

REFERENCES:

[1] Hiyama, T., 1994, “Robustness of Fuzzy Logic Power System Stabilizers Applied to Multimachine Power Systems”, IEEE Trans. on Energy Conversion, Vol. 9, No.3, pp.451-45.

[2] Fransisco Jurado, manuel Valverde, May 2003, “Voltage Correction By Dynamic Voltage Restorer Based on Fuzzy Logic Controller”, IEEE Transaction on Industrial Electronics.

[3] Margo P. M. Hery P. M. Ashari, Imanda, 2005, “ Dynamic Voltage Restorer Using Y connected Boost Transformer Controlled by Back propagation Neural Network”, SMELDA, Malang.

[4] Margo P.M. Hery P.M. Ashar,, T. Hiyama, September 2007, “Balanced voltage sag correction using DVR based on Fully polar controller”, ICICIC 2007 Conference Proceedings, Kumamoto Japan.

[5] C. Meyer, R. W. De Doncker, Y. W. Li, and F. Blaabjerg, “Optimized control strategy for a medium-voltage DVR—Theoretical investigations and experimental results”, IEEE Trans. Power Electron., vol. 23, no. 6, pp. 2746–2754, Nov. 2008.

Balanced Voltage Sag Correction Using Dynamic Voltage Restorer Based Fuzzy Polar Controller

ABSTRACT:

Many controllers based fuzzy logic have been applied on electric power system. Frequently, time response of the fuzzy controllers is slowly, because the number of membership functions are too many. Many research are proposed to minimize the number of membership function, such as fuzzy polar controller method. By using this method, number of membership function can be minimized, so the time response of the controller become faster. This paper presents the Dynamic Voltage Restorer (DVR) based Fuzzy Polar Controller Method to compensate balanced voltage sag. Simulation results show that this proposed method can compensate balanced voltage sag better than PI controller.

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 Fig. 1. Block diagram of DVR

EXPECTED SIMULATION RESULTS:

Fig. 2. 50% of voltage sags at bus A

Fig. 3. 50% sags correction using DVR based PI

Controller

Fig. 4. 50% sags correction using DVR based fuzzy

polar controller

CONCLUSION:

DVR based PI Controller can maintain 50% voltage sags at 110 % and 30% voltage sags at 98%. DVR based Fuzzy Polar Controller can maintain 50% voltage sags at 100 % and 30% voltage sags at 97%. According to the error average of all simulations, are shown that the performance of DVR based Fuzzy Polar Controller better than DVR based PI Controller. Further study for unbalance correction is being worked to prove the effectiveness of the proposed controller.

REFERENCES:

[1] Francisco Jurado ”Neural Network Control For Dynamic Voltage Restore” IEEE Transaction on Industrial Electronic. Vol 51,No.3, June 2004

[2] Margo Pujiantara, M Herry P, M Ashari, Imanda “Dynamic Voltage Restorer Using Y connected Boost Transformer Controlled by Backpropagation Neural Network” SMELDA, Malang 2005

[3] Fransisco Jurado, manuel Valverde :Voltage Correction By Dynamic Voltage Restorer Based on Fuzzy Logic Controller”: IEEE Transaction on Indutrial Electronics, may 2003.

[4] Thomas H. Ortmeyer and T. Hiyama, “Frequency Response Characteristics of The Fuzzy Polar Power System Stabilizer”, IEEE Transactions on Energy Conversion, Vol. 10, No.2, June 1995.

[5] S.S Min, K.C. Lee, J.W. Song and K.B. Cho, “A fuzzy current controller for field-oriented controlled induction machine by fuzzy rule”, in Proc. IEEE PESC, Toledo, Spain, 1992, pp. 265-270.