Variable speed wind turbine generator participation system frequency modulation method

Abstract

The invention discloses a variable speed wind turbine generator participation system frequency modulation method. The method comprises the steps that firstly, a wind turbine generator group is grouped to obtain multiple wind turbine generator sets; the frequency control dead zone and system frequency offset of each wind turbine generator set are set; then, when the system frequency offset exceeds the frequency control dead zone, wind turbine generator frequency control is triggered, and the frequency modulation operation mode is entered; the frequency modulation increment and frequency modulation time sequence of each wind turbine generator set are calculated; the frequency modulation increment and the frequency modulation time sequence are issued to each wind turbine generator set; finally, whether the system frequency of each wind turbine generator set exceeds the minimum point or not is judged; if yes, the wind turbine generator set exits from the frequency modulation operation mode; if not, according to the frequency modulation time sequence, frequency modulation operation is performed till the end. According to the variable speed wind turbine generator participation system frequency modulation method, on the basis of the wind power plant participation system frequency modulation time sequence control strategy, the wind turbine generator sets are coordinated for frequency modulation active power increment and time sequence exit, and the potential of variable speed wind turbine generator participation system frequency modulation is sufficiently excavated.

Description

technical field [0001] The invention relates to the technical field of new energy power generation, in particular to a method for variable-speed wind turbines participating in system frequency regulation. Background technique [0002] At present, most of the research on wind power forecasting focuses on the forecasting of wind power expectation. However, due to the strong dispersion of wind power random law, taking this as the forecast result will inevitably make the scheduling decision-making results unrealistic or even unfeasible. For this reason, it is necessary to increase the analysis of the possible fluctuation range and corresponding probability of wind power power in the forecasting process (hereinafter collectively referred to as fluctuation range analysis). Because the fluctuation interval analysis can give the probability distribution of wind power fluctuations in the future, it is helpful for decision makers to better understand the uncertainties and risks that m...

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Problems solved by technology

Because the fluctuation interval analysis can give the probability distribution of wind power fluctuations in the future, it is helpful for decision makers to better understand the uncertainties and risks that may exist in future changes, and to make more reasonable decisions, such as hypothetical predictions The errors obey the multivariate Gaussian distribution and the Beta distribution respectively, and the estimation of the distribution parameters is implemented to obtain the probability distribution function of the prediction error, which has positive significance for scheduling decisions, but it is difficult to find a distribution function consistent with the assumption in practice

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