F9501088619

Application of Fuzzy-PIDF Controller for AGC of A Two-Area Interconnected Thermal Power System under Deregulated Environment
Pradeep Kumar Mohanty¹, Binod Kumar Sahu^2
1Pradeep Kumar Mohanty, Department of Electrical Engineering, ITER, Siksha O Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India.
²Binod Kumar Sahu, Department of Electrical Engineering, ITER, Siksha O Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 3341-3351 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9501088619/2019©BEIESP | DOI: 10.35940/ijeat.F9501.088619
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Abstract: 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.
Keywords: Automatic Generation Control (AGC); fuzzy Proportional-Integral-Derivative (fuzzy PID); fuzzy PID with derivative filter (fuzzy PIDF); Local Unimodal Sampling (LUS); Teaching Learning Based Optimization (TLBO).