A Probability Prediction Method and System for Wind Power Ramping Events Based on Bayesian Network

Abstract

A method and system for predicting the probability of wind power ramp events based on Bayesian networks. According to the observed sample data, the dependent relationship between wind power ramp events and related meteorological factors such as wind speed, wind direction, temperature, air pressure, and humidity is mined , build the Bayesian network topology structure with the highest degree of fitting to the sample data; quantitatively describe the conditional dependence between the climbing event and each meteorological factor, and estimate the conditional probability of each conditional probability in the conditional probability table at each node of the Bayesian network value, together with the Bayesian network topology to form a Bayesian network model for forecasting wind power ramping events; based on the numerical weather forecast information at the time of prediction, the conditional probability of each state of the ramping event can be inferred; adaptively Adjust the value of the corresponding conditional probability at each node, so as to optimize the inferred conditional probability results of each state of the climbing event, and achieve a compromise between the reliability and sensitivity of the prediction results.

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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