A short-term photovoltaic output power prediction method based on soa-wnn

Abstract

The present invention relates to a kind of photovoltaic short-term output power forecasting method based on SOA-WNN, and its technical feature is: comprise the following steps: Step 1, construct the similar day selection principle based on Pearson's similarity coefficient, determine the topological structure of wavelet neural network; Step 2. Use the crowd search algorithm to optimize the weights of the wavelet neural network and the parameters in the wavelet basis function with the minimum output error as the fitness function; step 3. Based on the wavelet neural network parameter optimization in step 2, the similar day data samples are brought to Modeling is carried out in the wavelet neural network, and the short-term photovoltaic output power prediction value is obtained. The invention integrates the wavelet analysis and the BP neural network, can improve the inherent defects of the original algorithm, and utilizes the advantages of the crowd search method in speed and global search to improve the wavelet neural network.

Description

technical field [0001] The invention belongs to the technical field of photovoltaics, and relates to a photovoltaic short-term output power prediction method, in particular to a photovoltaic short-term output power prediction method based on SOA-WNN. Background technique [0002] With the rapid development of social economy, energy consumption has increased sharply, fossil energy is becoming exhausted, and the environmental pollution caused by the burning of fossil fuels has brought serious threats to the ecological balance of the earth and human life. Therefore, the construction of large-scale Photovoltaic power plants to meet human needs for energy is the current development trend. As a new type of green renewable energy, solar energy is the most ideal renewable energy compared with other new energy sources. Especially in recent decades, with the continuous advancement of science and technology, photovoltaic and related industries have become one of the fastest growing in...

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Problems solved by technology

[0008] However, since photovoltaic power generation is affected by solar radiation intensity, battery module temperature, weather, clouds and some random factors, the system operation process is an unbalanced random process, and its power generation and output power are highly random and uncontrollable. It is particularly prominent that this power generation method will inevitably bring a series of problems to the security and management of the grid after it is connected to the grid, so it is particularly important to be able to predict the output of the photovoltaic system more accurately in advance

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