Wind power prediction system for extreme scene

Abstract

The invention discloses a wind power prediction system for an extreme scene in the field of wind power prediction, and the system comprises a data collection server, a database server, a switch, a PCworkstation, a wind power prediction server, and a power grid dispatching center. The data acquisition server is connected with the numerical weather forecasting system, the anemometer tower, the booster station SCADA server, the fan SCADA server and the three-dimensional laser radar measurement system through a communication network, and the data acquisition server is connected with the PC workstation, the wind power prediction server and the database server through a switch through the communication network; and the switch is connected with the power grid dispatching center through the datainterface server. By increasing the input information amount, reducing the prediction deviation and adopting a physical, statistical and learning combined prediction method, a combined prediction model with small prediction error and high calculation efficiency is established, the calculation of economic dispatching is enhanced by selecting an extreme scene of a load, and a central scene sample isconsidered, so that the economy of the system is ensured.

Description

technical field [0001] The invention relates to the technical field of wind power forecasting, in particular to a wind power forecasting system for extreme scenarios. Background technique [0002] Wind power generation is an energy utilization technology that converts wind energy into electrical energy through wind turbines. It is currently the fastest-growing and most potential "green energy" in the field of new energy development. The wind power forecasting technology refers to the forecasting of the output power of wind farms within a certain period of time in the future, so as to arrange dispatching plans. This is because wind energy is an unstable energy source with random fluctuations. The integration of large-scale wind power into the system will definitely bring new challenges to the stability of the system. The power production dispatching organization needs to know the wind power output power in the next few hours. According to the time scale of wind farm output ...

AI Technical Summary

Problems solved by technology

[0009] The biggest problem in wind power forecasting is the large forecasting error, which greatly reduces the practicability of each forecasting method. Analyzing the source of errors in the whole process, based on the existing wind power forecasting, there are still problems as follows:

[0010] 1. The input data is single. At present, many forecasting systems mainly include numerical weather forecast processing modules and wind power module variables as input data. Wind energy is also affected by surrounding environmental factors and physical factors, which will inevitably bring some deviations to the forecast.

[0011] 2. The single forecasting model only considers the general scene information, because some possible load scenarios are not considered, especially some extreme load scenarios, and the uncertainty caused by the load prediction error of the extreme load scenarios is not considered

It brings great challenges to the economics and reliability of the grid, such as frequency drop, overloading of transmission lines, cascading failures even when the system is under heavy load conditions, etc.

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