Development of PSS tuning rules using multi-objective optimization

Mohandes, Baraa; Abdel-Magid, Y.L.; Boiko, Igor

doi:10.1016/j.ijepes.2018.01.041

Cited by 19 publications

(8 citation statements)

References 19 publications

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“…The parameter t p is considered 5 seconds. 55 In fact, the ISEUS shows how long it takes for the range of oscillations to be less than ±4% of the final value. The calculation of the ISEUS index is shown in Figure 9.…”

Section: The Objective Functions and Constraintsmentioning

confidence: 99%

“…When the final value of post‐faults oscillation after permitted time ( t p ), is not less than ±4%, the penalty as a coefficient, is used to remove the states. The parameter t p is considered 5 seconds . In fact, the ISEUS shows how long it takes for the range of oscillations to be less than ±4% of the final value.…”

Section: The Objective Functions and Constraintsmentioning

confidence: 99%

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Multi objective design of type II fuzzy based power system stabilizer for power system with wind farm turbine considering uncertainty

Nakhi

Kamarposhti

2019

Int Trans Electr Energ Syst

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Summary In this paper, the impacts of uncertainties in a multi‐machine power system with high penetration of wind farms are studied. The uncertainties associated with generation units, transmission system and demands are considered as the most important sources of uncertainty. So, an innovative optimized type II fuzzy power system stabilizer (PSS) is proposed to decrease uncertainties and increase the power system dynamic stability margin. Membership of the proposed stabilizer is optimized by multi objective particle swarm optimization algorithm using integral of square error until settling and figure of demerit as objective functions. The simulation results verified the performance of the proposed PSS in all operation conditions.

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Section: The Objective Functions and Constraintsmentioning

confidence: 99%

Section: The Objective Functions and Constraintsmentioning

confidence: 99%

Multi objective design of type II fuzzy based power system stabilizer for power system with wind farm turbine considering uncertainty

Nakhi

Kamarposhti

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

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“…Tests were conducted using the single machine infinite bus system, with only one generator. In 2018, [25] proposed to explore the process of tuning controllers for conditions using control theory. Tests were conducted using the twoarea symmetrical system.…”

Section: Introductionmentioning

confidence: 99%

Mayfly Optimization Algorithm Applied to the Design of PSS and SSSC-POD Controllers for Damping Low-Frequency Oscillations in Power Systems

Fortes

Martins

Costa

et al. 2022

International Transactions on Electrical Energy Systems

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In this paper, it is proposed to apply the mayfly optimization algorithm (MOA) to perform the coordinated and simultaneous tuning of the parameters of supplementary damping controllers, i.e., power system stabilizer (PSS) and power oscillation damping (POD), that actuate together with the automatic voltage regulators of the synchronous generators and the static synchronous series compensator (SSSC), respectively, for damping low-frequency oscillations in power systems. The performance of the MOA is compared with the performances of the genetic algorithm (GA) and particle swarm optimization (PSO) algorithm for solving this problem. The dynamics of the power system is represented using the current sensitivity model, and, because of that, a current injections model is proposed for the SSSC, which uses proportional-integral (PI) controllers and the residues of the current injections at the buses, obtained from the Newton–Raphson method. Tests were carried out using the New England system and the two-area symmetrical system. Both static and dynamic analyses of the operation of the SSSC were performed. To validate the proposed optimization techniques, two sets of tests were conducted: first, with the purpose of verifying the performance of the most effective algorithm for tuning the parameters of PSSs, PI, and POD controllers, and second, with the purpose of performing studies focused on small-signal stability. The results have validated the current injections model for the SSSC, as well as have indicated the superior performance of the MOA for solving the problem, accrediting it as a powerful tool for small-signal stability studies in power systems.

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“…In [3], a new control design in the frequency domain is proposed by using a Nyquist diagram. In [4], the authors have presented a systemic tuning of the PSS for different input signals using a double-objective optimization function. In [5], a design method for the parameters of the PSS controllers is proposed, through a modified Heffron-Phillips model which allows the definition of the PSS structure and the tuning of the multi-machine electric power systems parameters.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Particle Swarm Optimization (PSO) Algorithm for Tuning of Power System Stabilizers in Multimachine Electric Power Systems

et al. 2020

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The application of artificial intelligence-based techniques has covered a wide range of applications related to electric power systems (EPS). Particularly, a metaheuristic technique known as Particle Swarm Optimization (PSO) has been chosen for the tuning of parameters for Power System Stabilizers (PSS) with success for relatively small systems. This article proposes a tuning methodology for PSSs based on the use of PSO that works for systems with ten or even more machines. Our new methodology was implemented using the source language of the commercial simulation software DigSilent PowerFactory. Therefore, it can be translated into current practice directly. Our methodology was applied to different test systems showing the effectiveness and potential of the proposed technique.

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Development of PSS tuning rules using multi-objective optimization

Cited by 19 publications

References 19 publications

Multi objective design of type II fuzzy based power system stabilizer for power system with wind farm turbine considering uncertainty

Multi objective design of type II fuzzy based power system stabilizer for power system with wind farm turbine considering uncertainty

Mayfly Optimization Algorithm Applied to the Design of PSS and SSSC-POD Controllers for Damping Low-Frequency Oscillations in Power Systems

Implementation of Particle Swarm Optimization (PSO) Algorithm for Tuning of Power System Stabilizers in Multimachine Electric Power Systems

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