The invention relates to a wind power plant energy storage system configuration method based on a Wiener random process. The method comprises the following steps: step 1, calculating the output powerof a wind power plant; step 2, calculating the maximum value of the energy variation of an energy storage system according to the output power of the wind power plant obtained in the step 1, and counting probability density data of the power variation at different time intervals; step 3, introducing a Wiener random process in the calculation process of the energy variation of the energy storage system; step 4, determining the power configuration of the energy storage system based on a Wiener random process; and step 5, determining energy configuration of the energy storage system based on a Wiener random process. According to the invention, the selection process of energy storage power and energy is unified.

Wind power plant energy storage system configuration method based on Wiener random process

The invention discloses an annular frequency risk estimation method considering second-level air speed correlation for a wind power plant. An output power of the wind power plant is closely related tofluctuation characteristic of air speed, the annular requirement and the second-level requirement are difficult to be simultaneously met by a traditional method, the annular average air speed moduleis additionally arranged by the method on the premise of considering frequency deviation of air speed correlation within known short time, the annular random average air speed considering time correlation and Weibull distribution is simulated, more accurate annular second-level correlation air speed is built, and the frequency deviation is calculated according to the air speed. By the method, thetime scale requirement is met, and meanwhile, the time length requirement also can be met.

Annular frequency risk estimation method considering second-level air speed correlation for wind power plant

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Annular frequency risk estimation method considering second-level air speed correlation for wind power plant