Short-term Ultraviolet Index Forecasting Using ARIMA Model

Abstract

Solar energy is recognized as an ideal renewable energy. Solar photovoltaic power generation is an important way to use solar energy. Photovoltaic power generation can alleviate the existing energy crisis and alleviate various environmental problems. As a clean and renewable energy, photovoltaic power generation is playing a prominent role in smart micro-grid. The intensity of solar radiation is fluctuating, so the successful grid connection of solar power stations requires accurate power prediction. This paper focuses on the prediction of ultraviolet power index to solve the problem of power prediction of photovoltaic power station. Based on the analysis of cumulative autoregressive moving average model, the stationary of ultraviolet index time series was detected, the order of ultraviolet index model was estimated, and the ARIM A model of ultraviolet index was determined. The prediction accuracy of the model is determined by the root mean square error (RM SE) and mean absolute error (M AE).