Comparative Performance Analysis of Adaptive Tuned PID Controller for Multi-machine Power System Network

Author(s):  
Mahesh Singh ◽  
Aparajita Agrawal ◽  
Shimpy Ralhan ◽  
Rajkumar Jhapte
Author(s):  
Debasis Tripathy ◽  
Nalin Behari Dev Choudhury ◽  
Binod Kumar Sahu

Automatic generation control (AGC) is an automation scheme that regulates the output of several generators employed at different areas of an interconnected power system simultaneously in response to load variation in the most economical way. This article implements a fuzzy-two degree of freedom-PID controller considering derivative filter (F-2D-PIDF) optimally tuned through grasshopper optimization algorithms (GOA) for AGC of a three unequal area interconnected power system. Initially, comparative performance analysis is carried out for conventional PID controllers optimally designed by particle swarm optimization, teaching learning-based optimization and GOA techniques. After ensuring better performance from GOA based PID controller, the study extended to establish dominance of the proposed F-2D-PIDF controller over others like PID, PID with derivative filter (PIDF), two degree of freedom-PIDF, and fuzzy-PIDF for the same power system in presence and absence of nonlinearities with GOA framework. In all these above studies, a load perturbation of 0.01 p.u. is applied in area-1. Comparative performance analysis reveals that GOA based F-2D-PIDF controller outperforms other controllers in all aspects. Finally, robustness of the proposed controller verified by varying system parameters and loading condition.


This paper presents the application of fuzzy PID controller and fuzzy PID controller aided with derivative filter (fuzzy PIDF) to analyse the automatic generation control (AGC) issue of a two-area interconnected multi-unit thermal power system having reheat type turbine under deregulated market scenario. This paper, demonstrates the traditional AGC of two-area power system modified under different transactions like as POOLCO based transaction, transaction under bilateral agreement and contract violation transaction to study the system dynamics. Hybrid LUS (Local Unimodal Sampling) and TLBO (Teaching Learning Based Optimization) (LUS-TLBO) technique is proposed to optimize the input and output scaling factors i.e. gains of fuzzy PID controller and gains & filter co-efficient of the derivative filter of the proposed fuzzy PIDF controller under different transactions in the competing market. Comparative performance analysis is carried out to show the supremacy of the proposed fuzzy PIDF controller against proposed fuzzy PID controller and a recently published work on integral controller with Interline Power Flow Controller (IPFC) and Redox Flow batteries (RFB) units.


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