Multi-scene probability optimal scheduling method for calculating wind electricity volatility

Abstract

The invention provides a multi-scene probability optimal scheduling method for calculating wind electricity volatility. The multi-scene probability optimal scheduling method comprises the steps that wind power forecast error distribution curves of each time period are obtained according to analysis of wind power forecast errors by historical data, wind power in each time period is dispersed into at least three wind power states according to the wind power forecast error distribution curves, a state probability matrix of the wind power corresponding to each time period is set up, the probability f (k) occurring in a scene K is obtained according to the state probability matrix, the scene K which enables the generating cost of an electrical power system in a scheduling cycle to be minimum and meets a constraint condition is determined, and according to the target function, the considered fluctuation range of the wind electricity forecast power and the occurring probability as a feasible scheme are applied to a generation plan which comprises the electrical power system of a wind generator set, and the whole generation cost can be minimum under the circumstance of long time operation as much as possible.

Description

technical field [0001] The invention relates to the field of power systems, in particular to a multi-scenario probabilistic optimal scheduling method considering wind power volatility. Background technique [0002] At present, conventional wind power output prediction results are generally deterministic point predictions, which only give an exact value, and the prediction accuracy of wind farm output is not high. [0003] In a system with large-scale wind power grid-connected, the fluctuation of wind power output brings great challenges to the traditional power generation scheduling based on the reliability of power supply and the predictability of load, and the formulation of power generation plan becomes difficult. In response to the above situation, one method is to use wind power as a negative load. In order to ensure the safe and stable operation of the system, the impact of wind power output fluctuations on the system is often dealt with by increasing the reserve capac...

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Problems solved by technology

Although this method considers the fluctuation of wind power to a certain extent, the fitting effect of the prediction error model is poor. At the same time, when the prediction error occurs, it still only uses the predicted wind power as a reference for the dispatch plan, and cannot track the prediction error well. change trend, the volatility problem has not been well resolved

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