Adaptive fuzzy critic based control design for AGC of power system connected via AC/DC tie‐lines. Issue 2 (1st January 2017)

• Record Type: Journal Article
• Authors: Sharma, Gulshan; Ibraheem, ; Niazi, Khaleequr Rehman; Bansal, Ramesh C.
• Is Part Of: IET generation, transmission & distribution. Volume 11:Issue 2(2017)
• Page Start: 560
• Page End: 569
• Publication Date: 2017-01-01
• Subjects: fuzzy control -- automatic gain control -- learning (artificial intelligence) -- power system control -- dynamic response -- sensitivity analysis; adaptive fuzzy critic based control design -- AGC -- AC/DC tie‐line -- emotional learning control design -- automatic generation control -- two‐area power system -- artificial neurofuzzy regulator -- dynamic response -- load disturbance -- integral based control -- generation rate constraint -- sensitivity analysis; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2016.1164
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : This study presents the design of adaptive fuzzy critic based emotional learning control design for automatic generation control (AGC) of a two‐area power system interconnected via parallel AC/DC tie‐lines. The adaptive fuzzy critic evaluates the current system situation and provides the emotional signal so that the artificial neuro fuzzy regulator to modify its characteristic and reduce the critic stress. The adaptive fuzzy critic based emotional learning control design are implemented and the system dynamic responses are obtained considering 1% load disturbance in area‐1. A comparative study of performance of proposed control, fuzzy logic and conventional integral based control is carried out and presented with and without considering the system non‐linearities such as governor dead‐band and generation rate constraint. The proposed control design technique has been demonstrated as a superior one as compared with other techniques used for the AGC design in the study. Furthermore, the sensitivity analysis of the proposed control is also examined by varying the system parameters over the wide range from the nominal system values.