Real-time predicting method for output of wind electric field

Abstract

The invention relates to a real-time predicting method for output of a wind electric field, which aims at providing a real-time predicting method for output of a wind electric field, which has high predicting precision, strong practicality and short predicting reaction time. The output of the wind electric field is predicted through predicting the wind speed of the wind electric field, and the invention aims to provide reliable basis for a power network to make a schedule plan. The technical problem for solving the problem is as follows: the real-time predicting method for output of a wind electric field is characterized by comprising the following steps of: a. simulating a large-scale circulation field and a meteorological field by a number weather reporting mode according to the real-time refreshed meteorological grid point initial data, and deducing the wind resource state of the representative point; b. sending the wind resource state obtained from the step a to an output calculating model; c. deducing the output of the whole wind electric field by using the output calculating model, and furthermore, deducing the output of a wind electric field group. The invention is mainly used in the wind energy utilizing field, predicts the electric generation amount of a large wind electric generating field, and provides basis for the power network schedule.

Description

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AI Technical Summary

Benefits of technology

In this patented system, there were three main technical features that improved the performance of wind turbines by providing an efficient way to estimate their operating states accurately over long periods without requiring expensive equipment such as hydroelectricity meters. These improvements resulted in better overall energy production while reducing environmental impact caused by fossil fuel usage.

Problems solved by technology

This patented technical problem addressed in this patents relates to improving the accuracy and reliability of wind generators during peak hours when they produce less than optimal amounts of generated current due to environmental factors such as sunlight or temperature fluctuate over time. Current techniques involve estimating future values based only on past measurements from previous periods but without considering their potential effectiveness at different timescales.

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