CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Control Performance Standard based Load Frequency Control of a two area Reheat Interconnected Power System considering Governor Dead Band nonlinearity using Fuzzy Neural Network

by R.francis, I.a.chidambaram
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 15
Year of Publication: 2012
Authors: R.francis, I.a.chidambaram
10.5120/6988-9584

R.francis, I.a.chidambaram . Control Performance Standard based Load Frequency Control of a two area Reheat Interconnected Power System considering Governor Dead Band nonlinearity using Fuzzy Neural Network. International Journal of Computer Applications. 46, 15 ( May 2012), 41-48. DOI=10.5120/6988-9584

@article{ 10.5120/6988-9584,
author = { R.francis, I.a.chidambaram },
title = { Control Performance Standard based Load Frequency Control of a two area Reheat Interconnected Power System considering Governor Dead Band nonlinearity using Fuzzy Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 15 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 41-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number15/6988-9584/ },
doi = { 10.5120/6988-9584 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:39:50.930847+05:30
%A R.francis
%A I.a.chidambaram
%T Control Performance Standard based Load Frequency Control of a two area Reheat Interconnected Power System considering Governor Dead Band nonlinearity using Fuzzy Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 15
%P 41-48
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The frequency control of reheat interconnected two area power systems are mainly characterized by non-linearity and uncertainty. A hybrid neural network and fuzzy control is proposed for load frequency control in the power systems considering governor dead band (GDB) non-linearity. Fuzzy with neural network is employed to forecast the control input requirement and system's future output, based on the current Area Control Error (ACE) and the predicted change-of-ACE. The Control Performance Standard (CPS) criterion is adopted to the fuzzy controller design, thus improves the dynamic quality of system. The system was simulated and the output responses of frequency deviations in area 1 and area 2 and tie-line power deviations for 1% step-load disturbance in area 1 were obtained. The comparison of frequency deviations and tie-line power deviations for the two area interconnected thermal power system considering GDB nonlinearity with Redox Flow Batteries (RFB) reveals that the system with hybrid fuzzy neural controller enhances a better stability than that of system with integral controller.

References
  1. Shayeghi. H, Shayanfar. H. A, Jalili. A,"Load frequency control strategies state of the art survey for the researcher", Energy conservation and Management. Vol 50(2); pp. 344-353, 2009.
  2. I. A. Chidambaram and S. Velusami, "Design of decentralized biased controllers for load-frequency control of interconnected power systems considering governor dead band non-linearity", IEEE International Conference (INDICON 2005), Chennai, pp. 521-525, 2005.
  3. C. S. Indulkar and Baldev Raj, "Application of fuzzy controller to automatic generation control," Electric Machines and Power System, Vol 23 (2), pp. 209–220, 1995.
  4. Erturul Cam and Ihan Kocaarslan, "Load Frequency Control in two area power systems using fuzzy logic controller", Energy conversion and Management Vol. 46, pp. 233-243, January 2005.
  5. F. Beau fays, Y. Abdel-Magid, and B. Widrow, "Application of neural networks to load frequency control in power systems," IEEE Transaction on Neural Networks, Vol. 7, pp. 183–194, 1994
  6. Panda, Sidhartha Panda and Cemal Ardil, "Automatic Generation Control of Interconnected Power System with Generation Rate Constraints by Hybrid Neuro Fuzzy Approach", World Academy of Science, Engineering and Technology Vol 52, pp. 543-548, 2009.
  7. Y. L. Karnavas and D. P. Papadopoulos, "AGC for autonomous power system using combined intelligent techniques," Electric Power Systems Research, Vol. 62, No: 3, pp. 225–239, 2002.
  8. M. J. Yao, R. R. Shoults and R. Kelm , "AGC Logic Based on NERC's New Control Performance Standard and Disturbance Control Standard," IEEE Transactions on Power Systems,, Vol. 15,No. 2, pp. 852–857,2000.
  9. George Gross and Jeong Woo Lee, "Analysis of Load Frequency Control Performance Assessment Criteria", IEEE Transactions on Power Systems, Vol. 16, No. 3, pp. 520-525, 2001.
  10. I. A. Chidambaram, R. Francis,"Automatic Generation Control of two area interconnected power system based on cps using fuzzy neural network", IEEE conference, IEEE International Conference (ICETECT 2011), Nagarkovil, pp 200-205, 2011.
  11. Enomoto K, Sasaki T, Shigematsu T, Deguchi H,"Evaluation study about redox flow battery response and its modeling". IEEE Transaction on Power System Engineering, Vol 122-B (4), pp. 554–560, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Automatic Generation Control Governor Dead Band Control Performance Standards Redox Flow Batteries.

Powered by PhDFocusTM