Genetic algorithms. Power systems applications

Solomonese, Florin; Bărbulescu, Constantin; Kilyeni, Stefan; Litcanu, Marcela

doi:10.1109/hsi.2013.6577856

Cited by 1 publication

(1 citation statement)

References 18 publications

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“…It can handle any kind of objective function and constraints without many mathematical requirements. The population strategy enables GA to search near optimal solutions from various parts and directions simultaneously within a search space [19]. GA uses random choice and probabilistic decision to guide the research, where the population improves towards near-optimal point from generaton to generation.…”

Section: B Genetic Algorithm (Ga)mentioning

confidence: 99%

Performance Comparison between PSO and GA in Improving Dynamic Voltage Stability in ANFIS Controllers for STATCOM

Nguyen

Cao³

et al. 2019

Eng. Technol. Appl. Sci. Res.

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One of STATCOM’s advantages is its quick response to disturbances in the power systems. The controller of STATCOM is commonly a PID controller. However, the PID controller is usually only highly effective at one or some operation points. In order to improve operational efficiency of the controller of STATCOM, the proposed ANFIS-PSO and ANFIS-GA controllers have been studied and applied to the studied power system. To demonstrate the performance of the proposed controllers, simulations of the voltage response in time-domain were performed in MATLAB to evaluate the effectiveness of the designed controllers for STATCOM. The simulation results showed that the proposed controllers can be used to improve the system stability as well as the voltage quality more effectively than the conventional PID controller. The ANFIS PSO controller carried out the best response after the occurrence of a three-phase short circuit fault.

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Section: B Genetic Algorithm (Ga)mentioning

confidence: 99%