Method for constructing photovoltaic power station generation capacity short-term prediction model based on multiple neural network combinational algorithms

Abstract

The invention provides a method for constructing a photovoltaic power station generation capacity short-term prediction model based on multiple neural network combinational algorithms and belongs to the technical field of photovoltaic power generation, power grid connection technology and solar energy photovoltaic forecasting. The method overcomes the problem that a usually-used algorithm for constructing the photovoltaic power station generation capacity short-term prediction model is single and is likely to fall into local optimization, further resulting in big measurement error of the prediction model. The technical construction method of the invention is realized as follows: firstly using four different neural network algorithms to construct sub-models for neural network prediction; secondly screening and classifying weather information and analyzing the suitability of the various sub-models for neural network prediction; giving weighted parameter values of the sub-models in a combined model according to the suitability to further make the combined neural network model for prediction suitable for different weather conditions and then completing the construction of the photovoltaic power station generation capacity short-term prediction model. The method is mainly used for photovoltaic power station grid connection short-term prediction.

Description

technical field [0001] The invention belongs to the fields of photovoltaic power generation and grid-connected technology, and solar photovoltaic power generation forecast. Background technique [0002] With the rapid development of the world economy, the demand for energy is increasing day by day, and the traditional non-renewable energy sources (coal, oil, natural gas, etc.) The advantages of large size, renewability, and wide distribution range have become research hotspots all over the world. In my country, solar photovoltaic power generation has become an important way of solar energy application, and the scale and quantity of grid-connected photovoltaic power plants are constantly increasing. The output of photovoltaic power generation system is affected by factors such as weather and solar radiation intensity, which is fluctuating and intermittent. It is an uncontrollable factor for grid connection and will affect the safety and stability of the power system. Theref...

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Problems solved by technology

[0004] The present invention solves the problem that the existing photovoltaic power plant power generation prediction model uses a single algorithm, has poor applicability in different weathers, and is prone to fall into local optimum, which in turn leads to large measurement errors of the prediction model.

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