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Journal of Intelligent Systems

Editor-in-Chief: Fleyeh, Hasan

CiteScore 2017: 0.96

SCImago Journal Rank (SJR) 2017: 0.193
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Volume 22, Issue 2


Four-Area Load Frequency Control of an Interconnected Power System Using Neuro-Fuzzy Hybrid Intelligent Proportional and Integral Control Approach

Surya Prakash Giri
  • Corresponding author
  • Sam Higginbottom Institute of Agriculture, Technology and Sciences, Department of Electrical Engineering, Shephard School of Engineering and Technology, Deemed University, Allahabad, Uttar Pradesh 211007, India
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/ Sunil Kumar Sinha
Published Online: 2013-05-16 | DOI: https://doi.org/10.1515/jisys-2012-0025


This article presents a novel control approach, hybrid neuro-fuzzy (HNF), for the load frequency control (LFC) of a four-area interconnected power system. The advantage of this controller is that it can handle nonlinearities, and at the same time, it is faster than other existing controllers. The effectiveness of the proposed controller in increasing the damping of local and inter-area modes of oscillation is demonstrated in a four-area interconnected power system. Areas 1 and 2 consist of a thermal reheat power plant, whereas Areas 3 and 4 consist of a hydropower plant. Performance evaluation is carried out by using fuzzy, artificial neural network (ANN), adaptive neuro-fuzzy inference system, and conventional proportional and integral (PI) control approaches. Four different models with different controllers are developed and simulated, and performance evaluations are carried out with said controllers. The result shows that the intelligent HNF controller has improved dynamic response and is at the same time faster than ANN, fuzzy, and conventional PI controllers.

Keywords: Load frequency control (LFC); adaptive neuro-fuzzy inference system (ANFIS); artificial neural network (ANN); fuzzy; proportional and integral (PI) controllers; area control error (ACE); tie-line


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About the article

Corresponding author: Surya Prakash Giri, Sam Higginbottom Institute of Agriculture, Technology and Sciences, Department of Electrical Engineering, Shephard School of Engineering and Technology, Deemed University, Allahabad, Uttar Pradesh 211007, India

Received: 2012-10-15

Published Online: 2013-05-16

Published in Print: 2013-06-01

Citation Information: Journal of Intelligent Systems, Volume 22, Issue 2, Pages 131–153, ISSN (Online) 2191-026X, ISSN (Print) 0334-1860, DOI: https://doi.org/10.1515/jisys-2012-0025.

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