Model of Power System Stabilizer Adapting to Multi-Operating Conditions of Local Power Grid and Parameter Tuning

Hu, Wenping; Ji, Liang; Jin, Yitao; Wu, Fuzhang

doi:10.3390/su10062089

Cited by 11 publications

(5 citation statements)

References 31 publications

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“…Power System Stabilizers (PSS) are a well-known and effective approach to dealing with low frequency oscillations [22]- [27]. PSS is applied to maintain the stability of the power system either as a single machine or interconnection [28]- [33]. PSS is designed with the nature of the system in mind.…”

Section: Introductionmentioning

confidence: 99%

A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer

Aribowo

2023

Journal of Robotics and Control

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Power system stabilizer (PSS) is applied to dampen system oscillations so that the frequency does not deviate beyond tolerance. PSS parameter tuning is increasingly difficult when dealing with complex and nonlinear systems. This paper presents a novel hybrid algorithm developed from incorporating chaotic maps into the sea-horse optimizer. The algorithm developed is called the chaotic sea-horse optimizer (CSHO). The proposed method is adopted from the metaheuristic method, namely the sea-horse optimizer (SHO). The SHO is a method that duplicates the life of a sea-horse in the ocean when it moves, looks for prey and breeds. In This paper, The CSHO method is used to tune the power system stabilizer parameters on a single machine system. The proposed method validates the benchmark function and performance on a single machine system against transient response. Several metaheuristic methods are used as a comparison to determine the effectiveness and efficiency of the proposed method. From the research, it was found that the application of the logistics Tent map from the chaotic map showed optimal performance. In addition, the application of the PSS shows effective and efficient performance in reducing overshoot in transient conditions.

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Section: Introductionmentioning

confidence: 99%

A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer

Aribowo

2023

Journal of Robotics and Control

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“…Ref. [7] has used a multi-objective function that is solved using nonlinear simplex function in order to design the power system stabilizer. A power system stabilizer for multi-operating conditions is designed using the probabilistic Eigen values in [8].…”

Section: Introductionmentioning

confidence: 99%

Regional Pole Placers of Power Systems under Random Failures/Repair Markov Jumps

El-Sheikhi¹,

Soliman

Ahshan

et al. 2021

Energies

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This paper deals with a discrete-time stochastic control model design for random failure prone and maintenance in a single machine infinite bus (SMIB) system. This model includes the practical values of failure/repair rate of transmission lines and transformers. The probability matrix is, therefore, calculated accordingly. The model considers two extreme modes of operations: the most reliable mode and the least reliable contingency case. This allows the control design which stochastically stabilizes the system under jump Markov disturbances. For adequate transient response, the proposed state feedback power system stabilizer (PSS) achieves a desired settling time and damping ratio by placing the closed-loop poles in a desired region. The control target should also be satisfied for load variations in either mode of operation. A sufficient condition is developed to achieve the control objectives via solving a set of linear matrix inequalities (LMI). Using simulation, the performance of the designed controller is tested for the system that prone to random failure/maintenance under various loading conditions. Simulation results reveal that the closed-loop poles reside within the desired region satisfying the required settling time and damping ratio under the aforementioned disturbances. The contributions of the paper are summarized as follows: (1) modeling of transition probability matrix under Markov Jumps using practical data, (2) designing a controller by compelling the closed poles into the desired region to achieve adequate dynamic performance under different load varying conditions.

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“…Depending on the PSS type and tuning strategy the number of tunable parameters may vary. For instance, a typical PSS consists by 6 (i.e., the gain and five time constants), yet, by strategically selecting certain time constants to be fixed, the parameters to be optimized can be halved [Shin et al (2010); Farah et al (2012); Hu et al (2018)]. Regardless, the high number of parameters makes the task of online tuning highly complex and difficult.…”

Section: Introductionmentioning

confidence: 99%

AI-Based Damping of Electromechanical Oscillations by Using Grid-Connected Converter

et al. 2021

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The proliferation of grid-connected converter interfaced energy sources in Smart Grids, enhance sustainability and efficiency as well as minimizing power losses and costs. However, concerns arise regarding the stability and reliability of future smart grids due to this wide integration of power electronic devices, which are recognized to affect the dynamic response of the system, especially during disturbances. For instance, apart from the lower damping of existing electromechanical modes, new low-frequency oscillations begin to appear. Yet, the ability of grid-connected converters to provide grid support functionalities can alleviate the aforementioned challenges. Relevant studies show that these functionalities can be enhanced even further, if information regarding the oscillation characteristics are available. Traditional methods for extracting modal information are very well suited for monitoring purposes, however, they pose certain limitations when considered for control applications. Therefore, this paper proposes a multi-band intelligent power oscillation damper (MiPOD) that exploits 1) the inherent characteristics of grid-connected converters to damp multiple power oscillations and 2) the modeling capabilities of Artificial Intelligence (AI) for predicting the frequency of electromechanical oscillations in the system, as operating conditions change. Essentially, the MiPOD integrates the AI model in the control loop of the converter to attenuate multiple modes of oscillation. The proposed controller is validated for different disturbances and randomly generated operating points in the two area system. Specifically, in this case the AI model is a Random Forest ensemble regressor that is developed for tracking two electromechanical modes. As it is shown, the MiPOD can improve the overall performance of the system under various contingency scenarios with only 6% of the corresponding total nominal capacity of synchronous generators. In addition, the monitoring and damping abilities of the MiPOD are demonstrated for a vast range of operating points just by tuning two parameters; the predicted oscillation frequencies of the local and inter-area mode.

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Model of Power System Stabilizer Adapting to Multi-Operating Conditions of Local Power Grid and Parameter Tuning

Cited by 11 publications

References 31 publications

A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer

A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer

Regional Pole Placers of Power Systems under Random Failures/Repair Markov Jumps

AI-Based Damping of Electromechanical Oscillations by Using Grid-Connected Converter

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