Original scientific paper
https://doi.org/10.1080/00051144.2024.2325314
Optimal design of automatic generation control based on BBPSO-tuned PI for a restructured environment
P. M. Karthikeyan
; Department of Electrical and Electronics Engineering, Anna University, Chennai, India
S. Baghya Shree
; Department of Electrical and Electronics Engineering, Anna University Regional Campus, Madurai, India
*
* Corresponding author.
Abstract
This paper intends to model an AGC regulator for a restructured environment using Bare Bone
Particle Swarm Optimization (BBPSO). The gain-controlled Proportional–Integral (PI) Controller
is designed here to enhance the performance of the BBPSO algorithm along with Gaussian
distribution. The practical difficulty in handling the area control error to zero is the sudden variations in load. In practice, the tremendous contribution of deregulation in the power sector
causes volatility in frequency and tie-line power deviations. To ensure the robustness of the proposed controller, three different cases of power system transactions have been considered. The
performance has been validated by comparing it with Real Coded Genetic Algorithm-tuned PI
controller (RCGA-PI) and Differential Evolutionary Algorithm-tuned PI controller (DE-PI) for the
five area Thermal-Thermal generation test system. Moreover, the dynamic performance of an
extensive range of demands and disturbances of all areas like settling time and overshoot against
parametric precariousness has been done on the proposed test system.
Keywords
AGC; deregulated power system; BBPSO-tuned PI controller; GRC
Hrčak ID:
326207
URI
Publication date:
11.3.2024.
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