A method for ultra-short-term prediction of solar irradiance in clear and cloudy weather

Abstract

The invention relates to a method for ultra-short-term prediction of solar irradiance in clear and cloudy weather, which is based on an all-sky imager (TSI-880) ground cloud picture, including cloud retrieval of real-time ground-based cloud images, using the cloud image retrieved from the time-series cloud cover to predict the cloud image; Then, the multiple linear regression equation is constructed by using the cloud amount and clear sky factor data of n time cloud pictures before t time. Finally, the cloud amount data of t + Delta t time cloud pictures in the future are substituted into theregression model to obtain the forecast clear sky factor, and then the forecast surface irradiance of the corresponding future time is calculated. The invention can effectively predict the variation of the ground solar irradiance caused by the movement and change of the clouds in the clear and cloudy weather condition in real time, overcomes the shortcomings of the existing solar radiation prediction method such as randomness, uncertainty, large error and the like in the clear and cloudy weather condition, and realizes the advantages of good real-time performance and high accuracy.

Description

technical field [0001] The invention relates to the technical field of solar irradiance forecasting, in particular to an ultra-short-term forecasting method for solar irradiance in sunny and cloudy weather. Background technique [0002] The ever-increasing demand for energy and significant changes in the climate environment pose new challenges to the development of renewable energy. Solar energy is the largest available energy source on the earth so far, and it is a clean, non-polluting renewable energy source. Its development and utilization is the focus of sustainable energy development. An important form of solar energy utilization is photovoltaic power generation. The most direct meteorological factor that determines the power of photovoltaic power generation is ground solar irradiance, which directly affects the reliability of photovoltaic power generation. However, ground solar irradiance varies with seasons. The weather and weather show obvious periodic and random ch...

AI Technical Summary

Problems solved by technology

Most of the first two (1) and (2) do not directly use cloud information, and it is difficult to predict the sudden change in regional irradiance caused by cloud cover changes or clouds blocking the sun.

Type (3) can provide information from the current day to the next few days, but there are obvious deviations and random errors in the irradiance estimation

The microscopic physical characteristics of cloud particles are complex, while the spatial resolution of numerical weather prediction models is rough (usually tens to hundreds of km 2 ), the initial conditions are uncertain, and the description of the underlying surface is mostly empirical parameters of the grid point range, which cannot effectively simulate clouds with strong convection or short life cycle. Therefore, when using the numerical weather prediction model to predict irradiance It is difficult to predict the location, distribution and irradiance effects of clouds in a specific area

The (4) type of satellite cloud image has low temporal and spatial resolution and a large temporal and spatial coverage, making it difficult to quantitatively invert small-scale clouds and extract the characteristics of low-altitude clouds, and the influence of the underlying surface on the cloud image radiance is unknown. When forecasting solar radiation in a specific area, it needs to be downscaled, and the forecasting accuracy is limited

[0005] It can be seen that the above-mentioned existing forecasting methods are all due to various reasons, and cannot well forecast the situation of the ground solar irradiance caused by the change of cloud amount and cloud position in the case of partly cloudy weather, which makes the solar irradiance forecast result error Large, poor real-time performance, low accuracy