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Load Frequency Control Assessment of a PSO-PID Controller for a Standalone Multi-Source Power System

期刊

TECHNOLOGIES
卷 11, 期 1, 页码 -

出版社

MDPI
DOI: 10.3390/technologies11010022

关键词

differential evolution algorithm; genetic algorithm; particle swarm optimization; integral time absolute error; PID controller; cost function; load frequency control

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This paper presents the performance of load frequency control (LFC) for isolated multiple sources of electric power-generating units using a proportional integral derivative (PID) controller. A thermal, hydro, and gas power-generating unit are integrated into the system. The PID controller is proposed as a subordinate controller to stabilize system performance during sudden demands on the power system. The particle swarm optimization (PSO) algorithm is used to obtain optimal gain values for the PID controller, with various cost functions used to optimize controller gain parameters. The results show that the PSO-PID controller delivers a faster response compared to conventional methods, with significant improvements over GA and DE-based PID controllers.
The performance of load frequency control (LFC) for isolated multiple sources of electric power-generating units with a proportional integral derivative (PID) controller is presented. A thermal, hydro, and gas power-generating unit are integrated into the studied system. The PID controller is proposed as a subordinate controller to stabilize system performance when there is a sudden demand on the power system. The particle swarm optimization (PSO) algorithm is used to obtain optimal gain values of the proposed PID controller. Various cost functions, mainly integral time absolute error (ITAE), integral absolute error (IAE), integral squared error (ISE), and integral time squared error (ITSE) were used to optimize controller gain parameters. Furthermore, the enhancement of the PSO technique is proven by the performance comparison of conventional, differential evolution (DE) algorithm- and genetic algorithm (GA)-based PID controllers for the same system. The results show the PSO-PID controller delivers a faster settled response and the percentage improvement of the proposed technique over the conventional method is 79%, over GA is 55%, and over DE is 24% in an emergency in a power system.

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