Wind power climbing event probability prediction method and system based on Bayesian network

Abstract

The invention discloses a wind power climbing event probability prediction method and system based on a Bayesian network, and the method comprises the steps: mining the dependency relationship betweena wind power climbing event and related meteorological influence factors such as wind speed, wind direction, temperature, air pressure, humidity, and the like, and building a Bayesian network topological structure with the highest fitting degree with sample data; quantitatively describing a conditional dependency relationship between the climbing event and each meteorological factor, estimating the value of each conditional probability in a conditional probability table at each node of the Bayesian network, and forming a Bayesian network model for predicting the wind power climbing event together with a Bayesian network topological structure; deducing the probability of occurrence of each state of the climbing event according to the numerical weather forecast information of the mastered prediction time; the value of the corresponding conditional probability at each node is adaptively adjusted, so that the inferred conditional probability result of each state of the climbing event is optimized, and the compromise between the reliability and the sensitivity of the prediction result is realized.

Description

technical field [0001] The invention belongs to the field of wind power prediction, and in particular relates to a method and system for predicting the probability of a wind power ramp event based on a Bayesian network. Background technique [0002] With the continuous growth of the penetration rate of wind power in the power system, the inherent randomness, volatility and uncertainty of wind power output have increasingly severe impacts on the safe and stable operation of the power grid, economic dispatch and protection control. A large change in the active output of a wind farm in a short period of time is called a wind power ramp event. my country's grid-connected wind power has the characteristics of large-scale and high concentration. When the penetration power of wind power exceeds a certain value, unexpected wind power ramp-up events will directly lead to the imbalance of power generation and consumption in the power system, which will easily cause the system frequenc...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that the existing wind power climbing event prediction technology is greatly affected by the accuracy of wind power prediction and has poor adaptability to the incompleteness of training samples and the inaccuracy of data measurement prediction scenarios, this application provides a Bayesian-based Probability prediction method of wind power ramp event based on Bayesian network and a probability prediction system of wind power ramp event based on Bayesian network

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