Application of fuzzy subtractive clustering for optimal transient performance of automatic generation control

Load-frequency control (LFC) strategy aims to extinguish oscillations of both the frequency and tie-line power deviations to restore the steady state of an electric grid after load change occurs. Classical controllers, e.g., ProportionalÀ Integral (PI) regulators, have been initially applied to deal with the LFC. However, the main control performances, such as overshoots and settling times, should be further optimized to maintain the frequency within the desired tolerances. This paper investigates a novel approach using two-stage controllers based on neural network and fuzzy logic technique to improve efficiently the control performances. A six-control-area-interconnected power system model is also built as the typical case study. Subsequently, the proposed controllers will be applied to this model to solve the LFC issue in two cases: with and without using superconducting magnetic energy storage (SMES) devices. In principle, such SMES units can compensate efficiently load variations in a power system, thus they can be used in the LFC strategy to achieve the optimal performances. Finally, simulation results, which are obtained under various load conditions, demonstrate evidently the superiority of the proposed control strategy for the efficient solution of the LFC problem.

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Subtractive Clustering and Particle Swarm Optimization Based Fuzzy Classifier

Salah

Nemissi

Séridi

et al. 2019

International Journal of Fuzzy System Applications

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Setting a compact and accurate rule base constitutes the principal objective in designing fuzzy rule-based classifiers. In this regard, the authors propose a designing scheme based on the combination of the subtractive clustering (SC) and the particle swarm optimization (PSO). The main idea relies on the application of the SC on each class separately and with a different radius in order to generate regions that are more accurate, and to represent each region by a fuzzy rule. However, the number of rules is then affected by the radiuses, which are the main preset parameters of the SC. The PSO is therefore used to define the optimal radiuses. To get good compromise accuracy-compactness, the authors propose using a multi-objective function for the PSO. The performances of the proposed method are tested on well-known data sets and compared with several state-of-the-art methods.

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Application of fuzzy subtractive clustering for optimal transient performance of automatic generation control

Cited by 3 publications

References 24 publications

Data-driven system health monitoring technique using autoencoder for the safety management of commercial aircraft

Data-driven system health monitoring technique using autoencoder for the safety management of commercial aircraft

A Novel Two-Stage NNFL Strategy for Load-Frequency Control Using SMES

Subtractive Clustering and Particle Swarm Optimization Based Fuzzy Classifier

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