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Probabilistic Frequency Stability Analysis Considering Dynamics of Wind Power Generation With Different Control Strategies

Zhaoyuan Wang, Siqi Bu

2024IEEE Transactions on Power Systems22 citationsDOI

Abstract

Most existing studies on probabilistic frequency stability analysis ignore the dynamics of wind power generations (WPGs) and thus result in inaccurate analysis results especially when the fast frequency response of WPGs is expected. This paper proposes a method of probabilistic frequency stability analysis that considers the dynamics of WPGs with different control strategies. Firstly, a multi-interval sensitivity (MIS) method is proposed to simulate the frequency response, thereby significantly saving the simulation time. Then, a multi-element low-rank approximation (MELRA) uncertainty propagation analysis method suitable for large-scale uncertainty analysis is proposed. And the introduction of multi-element effectively improves the accuracy. In addition, by applying the Gaussian mixture model (GMM), the limitations of moment-based uncertainty propagation analysis methods are discussed, demonstrating the comparative superiority of the proposed method. Also, the necessity of considering the dynamics of WPGs in frequency stability analysis is revealed by analyzing the differences of frequency response with and without dynamics of WPGs using different control strategies. The performance of the proposed method is verified on the IEEE 68-bus system and the provincial large-scale power system.

Topics & Concepts

Wind powerProbabilistic logicAutomatic frequency controlControl theory (sociology)Stability (learning theory)Electric power systemAutomatic Generation ControlElectricity generationPower controlControl (management)Computer sciencePower (physics)EngineeringControl engineeringMathematicsStatisticsTelecommunicationsPhysicsElectrical engineeringMachine learningQuantum mechanicsArtificial intelligenceWind Turbine Control SystemsPower Systems and Renewable Energy
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