Solar irradiance forecasting using global Positioning system(GPS) derived total electron content

Anthony, Angelin (2020) Solar irradiance forecasting using global Positioning system(GPS) derived total electron content. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Solar energy is one of the most significant energy sources and the only potential energy source capable of providing the world's required extra energy over the next few decades. Because of its intermittency due to whether variations, the integration of renewables such as solar energy into the electrical network is a challenge for grid operators. Conversely, the installed capacity of solar photovoltaic (PV) globally continues to rise. In Malaysia, the average monthly daily solar radiation is 4000- 5000W/m², with the average monthly sunshine duration ranging from 4 to 8 hours. Thus, forecasting is becoming an effective resource for network grid operators to control the output of solar photovoltaic (PV) energy. Solar radiation measurement will decrease when ionosphere Total Electron Content (TEC) decreases. This is because free electrons forming in the ionosphere is strongly dependent on the solar radiation. This project aims to investigate the interaction between Total Electron Content (TEC) and solar irradiance and further used in solar irradiance forecasting. In order to get TEC, GPS data was extracted in order to substitute in calculations. The interaction between TEC and solar irradiance was done using neural net fitting. The overall correlation coefficient, R obtained was 0.92 which is closer to 1 and indicated as a good fit. Further, the solar irradiation was forecasted using directly and indirectly methods using time series predictions, which is ARIMA and LSTM model. In order to compare the accuracy of model, Root Mean Square Error (RMSE) was calculated. As a result, ARIMA model was a best model to forecast solar irradiance with lower RMSE compared to LSTM model.

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