Photovoltaic power generation short-term power rolling prediction method based on support vector machine algorithm

Abstract

The present invention relates to a photovoltaic power generation short-term power rolling prediction method based on a support vector machine algorithm. The generated power of a similar day and the current weather forecast of a predicated day are taken as the input amount of a prediction model, the photovoltaic power generation of the next day is predicated, after the next day is coming, the real output power of each predication point of the next day and the prediction power are continuously rolled forwards for comparison with the collection of the real power data, and when the predication points do not satisfy a given predication precision requirement, the real power of the current day and the real measurement weather data are taken as input data to establish a new PSO-SVM predication model so as to perform correction prediction of the power of the later-period predication points. The predication precision can be improved.

Description

Technical field [0001] The invention belongs to the technical field of photovoltaic power generation power prediction, and relates to a short-term power rolling prediction method of photovoltaic power generation. Background technique [0002] Photovoltaic power generation has the advantages of less pollution and flexible scale, and has been widely used. However, because the photovoltaic power generation system is obviously affected by environmental factors, it has the characteristics of uncertainty, volatility, and intermittentness, which is not conducive to the safe dispatch and energy management of the power grid, and increases the operation risk of the power grid. Therefore, predicting the short-term power of photovoltaic power generation can more comprehensively reflect the uncertainty of photovoltaic power generation, which is of great significance for grid planning and stable operation. [0003] The current forecasting methods for photovoltaic power generation power are most...

AI Technical Summary

Problems solved by technology

However, since the photovoltaic power generation system is significantly affected by environmental factors, it has characteristics such as uncertainty, volatility, and intermittency, which is not conducive to the safe dispatch and energy management of the power grid, and increases the operational risk of the power grid.

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