A novel model for solar radiation prediction
Energy for fulfilling basic community/individual needs has come to constitute the first article of expectation in all contemporary societies. The exploitation of renewables notably solar in electricity generation has brought relief to the fulfilment of energy demand especially among susceptible communities. In this paper yearly minimum solar radiation of Kano (12.05°N; 08.2°E; altitude 472.5 m; 3 air density 1.1705 kg/m3) for 46 years is used to generate a prediction model that fits the data using autoregressive moving average (ARMA) and a new model termed autoregressive moving average process (ARMAP). Comparison between the ARMA and ARMAP models showed a tremendous improve in the sum of square error reduction between the actual data and the forecasted data by 47%.
mean absolute percentage error; solar radiation; sum of square error; root mean square error; time series;
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