Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 15, Issue 11, Pages 5792-5802Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2019.2905851
Keywords
Automatic generation control; Heuristic algorithms; Tuning; Optimization; Performance analysis; Power system dynamics; Automatic generation control (AGC); generation rate constraints (GRCs); gray wolf optimization (GWO) algorithm
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Funding
- National Key Research and Development Program of China [2016YFB0900500]
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The dynamic performance of automatic generation control (AGC) primarily relies upon the performance index criteria (PIC) being used to optimize the supplementary controller gains. Most of the previous AGC studies were focused on developing various intelligent controllers and meta-heuristic algorithms to improve the system dynamic performance of the AGC system. However, no significant efforts were made to formulate effective PICs in order to acquire better supplementary control and improved AGC dynamic performance. In this paper, a maiden attempt has been made and new hybrid-peak-area-based PICs have been proposed for the optimal tuning of supplementary controller gains. The proposed PICs have been implemented upon single area as well as standard New England IEEE 39 bus system. Sensitivity analysis has also been carried out to demonstrate the superiority of the proposed PICs for wide changes in AGC power system model parameters. The proposed PICs demonstrate better dynamic performance in comparison to existing PICs in terms of overshoot, subsequent oscillations, and settling time.
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