A novel application of ALO-based fractional order fuzzy PID controller for AGC of power system with diverse sources of generation

Author:

Patel Nimai Charan1,Sahu Binod Kumar2,Bagarty Durgesh Prasad3,Das Pranati4,Debnath Manoj Kumar2ORCID

Affiliation:

1. Department of Electrical Engineering, Government College of Engineering, Keonjhar, Odisha, India

2. Department of Electrical Engineering, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India

3. Department of Electrical Engineering, College of Engineering and Technology, Bhubaneswar, Odisha, India

4. Department of Electrical Engineering, Indira Gandhi Institute of Technology, Sarang, Odisha, India

Abstract

The operation and control of the modern power system has become complex and difficult due to the incessant penetration of nonconventional energy sources integrated to the power grid and the structural variation of power system with continuing escalation of power demand in recent years. This entails the implementation of intelligent control strategy for satisfactory operation of the power system. Hence, a fractional order fuzzy proportional integral derivative (FOFPID) controller is suggested in this article for automatic generation control of two unequal area interconnected power system with diverse generating units such as thermal, hydro, diesel and wind power plants. The dynamic performance of the system is investigated by using proportional integral derivative (PID), fractional order PID (FOPID), fuzzy PID (FPID) and fractional order fuzzy PID (FOFPID) controllers separately. The parameters of these controllers are optimised by using ant lion optimiser algorithm with integral time absolute error as the objective function. The supremacy of the proposed controller is established by contrasting the results with FPID, FOPID and PID controllers. It is also observed that FPID controller gives superior result than PID and FOPID controllers. Further it is found that the result of FOPID controller is better than the integer order PID controller. Finally robustness analysis is performed to confirm the robustness of the proposed controller against parametric variations and random loading of the system.

Publisher

SAGE Publications

Subject

Electrical and Electronic Engineering,Education

Reference30 articles.

1. Elgard OI. Electric energy systems theory. New York: McGraw-Hill, 1982, pp. 299–362.

2. Comparative performance investigation of optimal controller for AGC of electric power generating systems

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