Research on PV Module Price Prediction Based on VMD-LSTM

As the utilization of fossil fuels and environmental pollution increase, countries are actively promoting the use of clean energy sources such as solar and wind power. However, due to supportive policies and the low barriers to entry in the photovoltaic (PV) industry, there is intense competition among PV manufacturers, leading to a reduction in the prices of PV modules. To foster the healthy development of the PV industry and ensure fairness and justice within the sector, this paper establishes a VMD-SSA-LSTM forecasting method. First, VMD (Variational Mode Decomposition) is used to decompose the price information of PV modules; second, SSA (Singular Spectrum Analysis) is applied to optimize the parameters within the LSTM (Long Short-Term Memory) network; finally, the method combines historical prices of components such as solar cells and photovoltaic glass to predict the future prices of the modules. The experimental results indicate that the forecasting method developed in this paper has high accuracy and can provide guidance for the future development of the PV industry, thus promoting the development and utilization of solar energy.