CFP last date
20 December 2024
Reseach Article

Applications of Non-Linear Controllers for Improving Distribution Networks Performances

by Abdul-Jabbar Fathel Ali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 50
Year of Publication: 2019
Authors: Abdul-Jabbar Fathel Ali
10.5120/ijca2019918707

Abdul-Jabbar Fathel Ali . Applications of Non-Linear Controllers for Improving Distribution Networks Performances. International Journal of Computer Applications. 181, 50 ( Apr 2019), 57-70. DOI=10.5120/ijca2019918707

@article{ 10.5120/ijca2019918707,
author = { Abdul-Jabbar Fathel Ali },
title = { Applications of Non-Linear Controllers for Improving Distribution Networks Performances },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2019 },
volume = { 181 },
number = { 50 },
month = { Apr },
year = { 2019 },
issn = { 0975-8887 },
pages = { 57-70 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number50/30546-2019918707/ },
doi = { 10.5120/ijca2019918707 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:09:48.654436+05:30
%A Abdul-Jabbar Fathel Ali
%T Applications of Non-Linear Controllers for Improving Distribution Networks Performances
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 50
%P 57-70
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Power quality is a problem that leads to financial issues. Many surveys have been shown that poor power quality causes large economic losses to industrial sectors and large amount of power is wasted due to power quality problems like sags, swells, harmonics, flickers etc. The present work considers, the modeling and simulation of a dynamic voltage restorer (DVR), which is achieved using MATLAB/Simulink. Faults are created with the proposed systems, and the disturbances are initiated at a duration of 0.8 sec till 0.95 sec. Comparison of the performances of the Fuzzy neural and Fuzzy logic based DVR are presented. Results are showed that Fuzzy logic controller is able to restore the load voltage to the nominal value in both linear and non linear loads quickly and efficiently. But when the 2nd and 3rd harmonics are superimposed on the voltage sag and voltage swell by the application of 3-ph programmable source, the fuzzy logic controller fails to restore and reduce the harmonic content to an acceptable values which is according to IEEE standard 3% for the individual voltage and 5% for the three phase voltage. While the Fuzzy neural controller has been very powerful and efficient to restore the load voltage to the pre-sag value and make it smooth under different cases of faults and nonlinear load conditions and keep the harmonics within the permissible limits in all cases.

References
  1. A.Ghosh and G.Ledwich,"power quality enhancement using custom power devices".springer science and business media 2012
  2. N.G.Hingiram,"Introducing custom power" spectrum IEEE, vol.32, pp. 41-48, 1995.
  3. C.Sancaran, power quality. CRC press, 2001.
  4. Bollen, MHJ 2001, 'Understanding power quality problems-voltage sags and interruptions', IEEE Press series on power Engineering, NewYork.
  5. Ramachandaramurthy, VK, Fitzer, C, Arulampalam, A, Zhan, C, Barnes, M & Jenkins, N 2002, 'Control of Battery supported dynamic voltage restorer'. IEEE Proceedings on Generation Transmission and Distribution, vol. 149, no. 5, pp. 533-542.
  6. Omar, R & Rahim, NA 2012, ' Voltage unbalanced compensation using dynamic voltage restorer based on super capacitor ' , Electrical Power and Energy Systems, vol, 43, no. 1, pp. 573-581.
  7. Wang, B & Venkataramanan, G 2009, 'Dynamic voltage restorer utilizing a matrix converter and fly wheel energy storage' , IEEE Transactions on Industry Applications, vol . 45 , no. 1 , pp. 1360- 1364.
  8. Amutha, N & Kumar, BK 2013, 'Improvement fault ride-through capability of wind generation system using DVR' , Electrical Power and Energy System , vol. 46, no. 1 , pp. 326-333 .
  9. Ramasamy, M& Thangavel, S2013 , 'Experimental verification of PV based Dynamic voltage Restorer (PV-DVR) with significant energy conservation', Electrical Power and Energy System, vol. 49, no. 1, pp. 296-307.
  10. Newman, MJ, Holmes, DG, Nielsen, JG & Blaabjerg, F 2005, 'Adynamic voltage restorer based on a four-leg voltage source converter, IET Generation, Transmission and Distribution, vol. 3, no. 5, pp. 437-447
  11. Jimichi, T, Fujita, H & Akagi, H 2008, 'An approach to eliminating DC magnetic flux from the series transformer of a dynamic voltage restorer ', IEEE Transactions on Industry Applications, vol. 44, no. 3, pp. 809-818.
  12. Teke, A 2011, 'Unified power quality conditioner: Design , simulation and experimental analysis', Ph.D. thesis, Cukarova University of Natural an Applied Sciences Jimichi, T, Fujita, H & Akagi, H 2008, 'An approach to eliminating DC magnetic flux from the series transformer of a dynamic voltage restorer ', IEEE Transactions on Industry Applications, vol. 44, no. 3, pp. 809-818.
  13. http://www.mathworks.com/parktransformation.html
  14. S. Yasunobu and S. Miyamoto. Automatic train operation by predictive fuzzy control. In M. Sugeno , editor, Industrail Applications of fuzzy control, pages 1-18. North-Holland, Amsterdam, 1985.
  15. M. Sugeno. Current projects in fuzzy control. In Workshop on fuzzy Control System and Space Station Applications,pages 65-77, Huntington Beach, CA, 14-15 November 1990
  16. Tang H, Tan CK, Yi Z(2007) Neural network: computational models and applications. Stud Com Intell, vol 53. Springer, Berlin.
  17. http://www.mathworks.com/neural.html
  18. Jang JSR (1993) ANFIS: adaptive network-based fuzzy inference systems. IEEE Trans Sys Man Cybern 23:665-685.
  19. Jang JS, Sun CT (1995) Neuro-fuzzy modeling and control. Proc IEEE 83(3):378-406 McCulloch WS, Pitts WH (1943) A logical calculus of the ideas immanent in nervous activity. Bull Math Biophys 5:115-133.
Index Terms

Computer Science
Information Sciences

Keywords

Non-Linear Controller Fuzzy Neural Power Quality Improvement Sags Swells DVR