Short-term photovoltaic power generation prediction method considering correlation degree of weather and meteorological factors

Abstract

The invention discloses a short-term photovoltaic power generation prediction method considering the correlation degree of weather and meteorological factors. The method comprises the following steps:1, rejecting bad data through an iForest algorithm; 2, respectively calculating Pearson correlation coefficients R of the photovoltaic power generation power and the five meteorological factors underfour weather types, and normalizing the Pearson correlation coefficients R; 3, performing fuzzy clustering on the five meteorological factors of the to-be-measured day, and obtaining a correlation coefficient of the historical day and the to-be-measured day; 4, a correlation coefficient normalization value is introduced, and the correlation degree between a historical day and a to-be-measured dayis solved; and 5, taking the historical day with high correlation degree as historical data, inputting the historical data and the meteorological factors of the day to be measured into the improved ACO-BP neural network, and finally obtaining a predicted value of the solar photovoltaic power generation to be measured; and 6, determining a neural network correlation coefficient, and performing simulation. The method aims to improve the photovoltaic power generation prediction precision, improves the practicality of a prediction model, and plays a great role in the combination of scheduling andprediction.

Description

technical field [0001] In the technical field of new energy power generation prediction, the present invention specifically proposes a short-term photovoltaic power generation prediction method that takes into account the correlation between weather and meteorological factors. Background technique [0002] With the huge increase in world energy consumption and the rapid reduction of coal and other resources, human demand for clean and renewable energy is increasing. As a clean, environmentally friendly and renewable new energy, solar energy has become One of the important choices for energy saving and emission reduction. A large number of photovoltaic systems are connected to the grid, and their own intermittent and random problems will have a negative impact on the stability of the grid connected to it. Therefore, accurate prediction of photovoltaic power generation plays an irreplaceable and important role in rational dispatching of power grids, peak shaving and valley fi...

AI Technical Summary

Problems solved by technology

By proposing the correlation between different weather and meteorological factors and photovoltaic power generation, the problem of low accuracy in historical day selection is solved; and the bad data in the collected data is eliminated through the iForest algorithm

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