Distributed photovoltaic power station large fog weather visibility prediction method

Abstract

The invention relates to a distributed photovoltaic power station large fog weather visibility prediction method, and the distributed photovoltaic power station large fog weather visibility predictionmethod is characterized by comprising the following steps: step 1, establishing a large fog weather visibility calculation formula based on a conventional numerical weather forecast variable; step 2,evaluating the prediction effect of large fog weather visibility prediction by two evaluation methods of skill grading and forecast deviation; and step 3, evaluating and optimizing the key parametersin the large fog weather visibility calculation formula of the step 1. According to the method, a large fog weather visibility prediction technology which can adapt to a local area can be established, and the visibility forecast level of the large fog weather of a distributed photovoltaic power station is improved.

Description

technical field [0001] The invention belongs to the technical field of output forecasting of distributed photovoltaic power stations, and relates to the key technology of distributed photovoltaic power station output and numerical weather forecasting, in particular to a method for predicting the visibility of distributed photovoltaic power stations in foggy weather. Background technique [0002] The country vigorously promotes the layout of new energy. Driven by energy policies, distributed renewable energy power stations have been put into construction and operation on a large scale. The impact on the power grid is large, and the power grid is not easy to receive. As a result, new energy power stations often abandon wind and light, and cannot operate at full capacity. How to do a good job of connecting new energy power stations to the grid, the coordinated control and energy management of source, grid, load and storage are very critical, and this requires accurate distribut...

AI Technical Summary

Problems solved by technology

The first method has two disadvantages. One is that this method can only obtain the forecast results of the approximate range of visibility, and cannot obtain continuous forecast results. The second is that this method belongs to statistical forecasting and requires a large amount of historical data to calculate the correspondence between physical quantities and visibility levels. relationship, and due to the different characteristics of fog in different regions, this empirical relationship cannot be generalized

This method is not applicable to the current distributed photovoltaic power generation forecast for the visibility forecast demand

The second method currently only considers the influence of fog water content to establish a visibility prediction technology. Although it can give continuous prediction results, it does not consider the influence of another important factor, fog droplet concentration, on visibility.

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