A prediction method of ultra-short-term photovoltaic power generation based on cloud cover simulation

Abstract

The invention provides a photovoltaic super-short-term generated power forecasting method based on cloud cover simulation. The method comprises the following steps that photovoltaic super-short-term generated power of a photovoltaic power station in the next four hours is forecasted according to a weather-type cloudless sky forecasting method; cloud cover information of the photovoltaic power station in the next four hours is simulated, forecasted data correction is carried out for horizontal plane irradiance attenuation caused by cloud, and forecasting of the photovoltaic super-short-term generated power of the photovoltaic power station is finished. The forecasting method has the greater advantages on the aspect of capturing the cloud cover shading information than a cloudless sky working condition photovoltaic power super-short-term forecasting model, and the effective time duration is greatly prolonged compared with that forecasted by a photovoltaic power super-short-term forecasting model based on a foundation cloud picture.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic power forecasting, and in particular relates to a forecasting method for ultra-short-term photovoltaic power generation based on cloud amount simulation. Background technique [0002] With the large-scale photovoltaic power plants connected to the grid in recent years, the randomness and volatility of the output power of photovoltaic power generation have affected the security, stability and economic operation of the grid. Accurate prediction of the output power of photovoltaic power plants can provide important decision support for power dispatching, coordinate the coordination of conventional power and photovoltaic power generation, effectively reduce the operating cost of the power system, and make full use of photovoltaic resources, thereby obtaining Greater economic and social benefits. However, the output power of the photovoltaic power generation system largely depends on the amount o...

AI Technical Summary

Problems solved by technology

Although the use of satellite cloud images is a good way to reveal the characteristics of regional cloud coverage, its temporal and spatial resolution is relatively low, and because the ground-based cloud images are shot in a small area, the spatial range of the shooting is limited, and the cloud clusters in the predicted Within a short period of time, the clouds in the sky have moved out of the collection range of the device, so it is difficult to use the real-time cloud image collection information to realize the ultra-short-term forecast for the next 4 hours. The model for photovoltaic power prediction based on ground cloud images will fail, and it will not be able to accurately predict power

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