Forecasting method for solar photovoltaic electricity generation amount based on SVM (support vector machine) - Markov combination method

Abstract

The invention discloses a forecasting method for a solar photovoltaic electricity generation amount based on the SVM (support vector machine) - Markov combination method. The method comprises the following steps of (1) selecting the solar radiant strength, daily maximum temperature, relative humidity and a wind speed as warning factors; (2) collecting a certain quantity of sample data according to the warning factors; (3) primarily establishing an SVM regression forecast model, carrying out training by utilizing the sample data, and determining an SVM model structure; (4) carrying out primary forecast of the photovoltaic electricity generation amount according to the SVM model structure obtained from the step (3); (5) carrying out rectification on a forecast result by applying the Markov method; (6) obtaining the forecast result. According to the forecasting method, the SVM is adopted to carry out the regression forecasting analysis, rectification on the forecast result is carried out through the Markov method, the method is coincided with the characteristics of photovoltaic electricity generation, advantages of the forecasting method and the Markov method are complemented, therefore a more accurate forecasting result is obtained, and reliable forecast on the photovoltaic electricity generation amount is realized.

Description

technical field [0001] The invention relates to the field of solar energy utilization research, in particular to a method for predicting solar photovoltaic power generation based on the SVM-Markov combination method. Background technique [0002] Today, traditional fossil fuels are increasingly depleted, and the environmental hazards caused by their combustion are becoming increasingly prominent. The energy crisis and environmental problems brought about by traditional fossil fuels have become the greatest challenges facing mankind. For the sustainable development of human society, countries all over the world have turned their attention to new energy and renewable energy, vigorously developing and placing high hopes on it, hoping to adjust and change the current energy structure and ensure human energy security. Compared with water energy, wind energy, geothermal energy, biomass energy, etc., solar energy has become the focus of people's attention because of its outstanding...

AI Technical Summary

Problems solved by technology

The above two methods have been applied in the prediction of photovoltaic power generation, but there are some limitations in the method. For example, for data information with strong regularity and periodicity, these two prediction methods can achieve high prediction accuracy, but photovoltaic Power generation has characteristics such as randomness and volatility. Using these two methods, the effect is often very poor and cannot meet practical needs

Images