Adaptive Power System Stabilizer Design Using Optimal Support Vector Machines Based on Harmony Search Algorithm

Pahasa, Jonglak; Ngamroo, Issarachai

doi:10.1080/15325008.2013.856966

Cited by 10 publications

(3 citation statements)

References 33 publications

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“…Different techniques are mixed with robust technique to provide sufficient damping for small signal oscillation in power system such as periodic output feedback, pole placement method [21][22][23], variable structure method, quantitative feedback theory [24,25] and sliding mode control [26][27][28][29]. Tuning of power system stabilizer using fuzzy logic has been investigated in [30][31][32][33]. In [34][35][36] the optimal control, adaptive control, and polynomial control are utilized for damping improvement and the parameters are tuned using optimization techniques.…”

Section: -Introductionmentioning

confidence: 99%

Robust Damping Controller for Synchronous Generators under Operational Uncertainties

2022

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Power system stabilizers have been widely used to create sufficient damping against low-frequency oscillations in power systems. Due to appearing uncertainties in operational conditions of power systems, robust design of power system stabilizers is a crucial requirement for small signal stability. In this paper, a robust local damping controller is developed considering the possible uncertainties in operational conditions. The developed damping controller is optimized based on the H-infinity method in presence of uncertainties in electrical variables of the synchronous machine. In the proposed robust damping controller, only the practically available control signals such as the deviation of the rotor speed of the synchronous generators are used. To fulfill the robust and internal stabilities of the damping controller under a given horizon of operational uncertainties, a novel design based on the combination of the developed robust damping controller and the conventional power system stabilizer is introduced. Simultaneous damping of local oscillatory modes and the internal stability of the proposed robust controller is achieved via a multi-objective function. The efficacy of the proposed local dampingcontroller is compared with the conventional power system stabilizer and a damping controller that is designed using the pole placement approach.

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Section: -Introductionmentioning

confidence: 99%

Robust Damping Controller for Synchronous Generators under Operational Uncertainties

2022

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“…BA is a powerful algorithm at exploitation but has some insufficiency at exploration, thus it can easily get trapped into the local minimum solutions. Other methods are listed in Karnik et al (2011), Linda and Nair (2012), Khodabakhshian et al (2013), Pahasa and Ngamroo (2014), Shayeghi and Ghasemi (2014), Soliman (2016), Elazim and Ali (2016), Farah et al (2016) and Shafiullah et al (2017) for PSS parameter optimization. Good results may be obtained by these kinds of optimization approaches.…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization of power system stabilizers via kidney-inspired algorithm

Ekinci

Demirören

Hekimoğlu

2018

Transactions of the Institute of Measurement and Control

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This article describes the application of a new population-based meta-heuristic optimization algorithm inspired by the kidney process in the human body for the tuning of power system stabilizers (PSSs) in a multi-machine power system. The tuning problem of PSS parameters is formulated as an optimization problem that aims at maximizing the damping ratio of the electromechanical modes and the kidney-inspired algorithm (KA) is used to search for the optimal parameters. The efficacy of the KA-based PSS design was successfully tested on a well-known 16-machine, 68-bus power system. The obtained results are evaluated and compared with the other results obtained by the original particle swarm optimization (PSO) and the bat algorithm (BA) methods. From the detailed eigenvalue analysis, the nonlinear simulation studies and some performance indices it has been found out that for damping oscillations, the performance of the proposed KA approach in this study is better than that obtained by other intelligent techniques (PSO and BA). Moreover, the efficiency and the superior performance of the proposed method over the other two algorithms in terms of computation time, convergence rate and solution quality are confirmed.

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“…Although these methods utilise probabilistic transition rules instead of deterministic ones, they do not require the derivatives of the objective function and/or constraints. In this point of view many common approaches such as simulated annealing optimisation [3] particle swarm optimisation (PSO) [4], genetic algorithms (GAs) [5], bi-linear matrix inequality [6], differential evolution algorithm [7], harmony search algorithm [8], ant colony optimisation and bat search algorithm [9] have been used for overcoming the defects in the CPSS tuning. However, in the above-mentioned methods, the parameters of the classical lead lag filters are tuned with a linearised model of power system.…”

Section: Introductionmentioning

confidence: 99%

Fractional‐order lead‐lag compensator‐based multi‐band power system stabiliser design using a hybrid dynamic GA‐PSO algorithm

Abdulkhader

Jacob

Mathew

2018

IET Generation, Transmission & Distribution

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Adaptive Power System Stabilizer Design Using Optimal Support Vector Machines Based on Harmony Search Algorithm

Cited by 10 publications

References 33 publications

Robust Damping Controller for Synchronous Generators under Operational Uncertainties

Robust Damping Controller for Synchronous Generators under Operational Uncertainties

Parameter optimization of power system stabilizers via kidney-inspired algorithm

Fractional‐order lead‐lag compensator‐based multi‐band power system stabiliser design using a hybrid dynamic GA‐PSO algorithm

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