An interface design to use linear prediction filters for renewable energy systems

Production of the electricity must be planned well due to considerable increase of the energy demand. Accurate forecasting of the production of the electricity is one of the main objectives in planning. There are many estimation systems in the literature. Linear filters are widely used, especially in image processing. The mean square root error between the measured and predicted values can be calculated by the help of optimum filter coefficients. Once the optimum coefficients are calculated, the value of the next pixel can be obtained. The linear filter is now applied to renewable energy systems. Prediction of solar radiation is one of the recent applications of linear filters. However, application of linear filter approach is not the only application and this tool can also be used for other renewable energy related data. In this thesis study, it is aimed to develop an interface program to apply linear filters to the data obtained from an energy system. The interface program to be applied will allow the user to select different filter types, and these filters are aimed to calculate optimum coefficients taking into account the entire data. Also, according to others, the program visualizes and uses all the results. Predict success based on different metrics is aimed to be calculated by the software. It is aimed to test the program on prediction of solar radiation data. The results will be presented and discussed. By this way the users related to renewable energies will be able to benefit from the software by presenting their own data and by printing the results.