ANALYSIS OF POWER QUALITY DISTURBANCES USING SIGNAL PROCESSING TECHNIQUES

1. ANALYSIS OF POWER QUALITY DISTURBANCES USING SIGNAL PROCESSING TECHNIQUES

2. Overview • Abstract • Project Description • Objective • Simulation Model/System Studied • Project Methodology • Procedure • Algorithm • Conclusion

3. Abstract This project presents an algorithm and approach that is able to provide the detection and location of the power quality disturbances. Here, the events like voltage sag, voltage swell, and transients are analyzed using S transform and the energy distribution are found for the power quality disturbances using Parseval’s Theorem. The PQD is also been analyzed by both phase spectrum and amplitude spectrum. The events are simulated using MATLAB SIMULINK software. The advantage of the algorithm is it has both time-frequency localization and thus has the visual observation of power quality disturbance.

4. Project Description • OBJECTIVE • To detect and analyse the power quality disturbances that occur in a three phase power system due to the contribution of the network impedances and types of customers’ connected loads.

5. What is PQD? Any electrical power problem manifested in voltage, current, or frequency deviations that results in failure or mis-operation of customers’ operation.

6. Need for the study of PQD… • Variations in the power quality, even for a very short time, that were not a concern before can be very costly in terms of process shut-downs and electrical equipment malfunctions in manufacturing plants. • Modern day customers demand high power quality for improved production output as well as for maintaining an optimal operating cost.

7. Classification of PQD The power quality disturbances that we are going to predict in this project are • Sag • Swell • Transients

8. SAG • A voltage sag is a momentary (less than a few seconds) decrease in voltage outside the normal tolerance. • The starting of heavy loads, lightning and power system faults causes voltage sags.

9. SWELL • A voltage swell is a momentary increase in voltage outside the normal tolerance. • Voltage swells are caused by sudden decreases or the turning off of heavy loads.

10. Transients • Sudden, brief increase in current or voltage in a circuit that can damage sensitive components and instruments. • These disturbances are shorter than sags or swells, and are caused by sudden changes in the power system.

11. Simulation Model(System studied)

12. Procedure of proposed approach PARSEVAL’S THEOREM Applying DSP techniques-Wavelet Transforms 0 SAG Feature Extraction Technique Classification of PQD 1 SWELL 2 TRANSIENTS From power quality recorders-Data acquisition systems NOTE: Magnitude Levels: Sag<Swell<Transients

13. Algorithm of proposed project Extraction of PQD N Applying DSP Techniques(WT) Features Extraction using Parseval’s Theorem YES If Energy Density(ED) is at NORMAL value(EDN) Take no action N NO NO If ED < EDN YES Sag is present. So take necessary action N C

14. Algorithm of proposed project C If ED > EDN YES Swell is present. So take necessary action NO If ED > EDSwell NO YES Oscillatory transients is present. So take necessary action N

15. SOFTWARE USED: MATLAB • APPLICATION: It can be used at various domains in the power system.

16. Simulated Model

17. Transient Simulink Model

18. Simulink Output

19. TRANSIENT Waveforms obtained from M-File after applying WAVELET TRANSFORM

20. Transient waveform-PHASE A

21. Transient waveform-PHASE B

22. Transient waveform-PHASE C

23. Conventional and proposed system • Automatic prediction of PQD and prediction accuracy is increased • Solves both data volume and lack of expertise problems • Damage to the equipments due to breaking down of insulation can be eradicated.

24. Conclusion • In this project, a novel approach to perform data detection and analysis using s-transform technique is presented. • This proposed method will be useful to the PQMS for performing the real-time detection and analysis of the recorded power quality disturbances.

25. THANK YOU