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Abstract
The emergence of flexible AC transmission technology provides a new technical means for ensuring the reliable grid connection and stable operation of wind farms. Among them, the static reactive power generator has a fast response speed, which can accurately compensate for the reactive power of the wind farm and improve the power factor; this is widely used in wind farms. To obtain accurate static var generator (SVG) parameters to meet the reliability requirements of a power system, we propose an adaptive estimation method that considers the wind speed fluctuation of wind farms. First, analyzing the dynamic SVG characteristics allowed us to establish a mathematical model. Then, the corresponding relationship between the sensitivity values of the parameters to be identified and the fluctuating wind speed was established, and low and high wind speed models were constructed. Finally, for accurate estimation considering wind speed fluctuation, the parameter initial values are obtained by combining the low wind speed and high wind speed model identification parameters, and we introduce the multimode hybrid estimation of the SVG parameters, providing a new method for accurately identifying the SVG model parameters. The simulation results of the parameter estimation demonstrate the accuracy and stability of the proposed method.
Highlights
Reactive power compensation is essential in wind farms to achieve regional voltage stability and wind power accommodation. e rapid development of new power transmission technologies based on flexible AC transmission system (FACTS) equipment has provided a new way to ensure reliable grid connection and the stable operation of wind farms [1]
An static var generators (SVG) is known as a static var compensator (STATCOM), which is a dynamic reactive power compensation device based on a self-commutated power semiconductor bridge converter
To accurately estimate SVG parameters, we propose an adaptive estimation method that considers the wind speed fluctuation of wind farms. e performance of the proposed method is verified using parameter estimation simulations
Summary
Reactive power compensation is essential in wind farms to achieve regional voltage stability and wind power accommodation. e rapid development of new power transmission technologies based on flexible AC transmission system (FACTS) equipment has provided a new way to ensure reliable grid connection and the stable operation of wind farms [1]. Erefore, when identifying the parameters of the static reactive power generator, it is necessary to select the appropriate observation quantity according to the specific disturbance for parameter identification. E chicken swarm algorithm can eliminate the strict requirements of traditional identification algorithms for system linearity and is suitable for the parameter identification of wind farm static reactive power generator models [16, 17]. In this regard, this study proposes a multimode hybrid identification algorithm based on the chicken flock algorithm. Correlated observations are selected to identify low and high wind speed models, and the identified optimal parameters are used as the initial parameter values of the multimode hybrid identification algorithm. The wind farm SVG model parameters for estimation were Kdp, Kdi, Kqp, Kqi, KPI, KII, and L
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