Seasonal solar irradiance forecasting using artificial intelligence techniques with uncertainty analysis

Abstract

Renewable integration in utility grid is crucial in the current energy scenario. Optimized utilization of renewable energy can minimize the energy consumption from the grid. This demands accurate forecasting of renewable contribution and planning. Most of the researches aim to find a suitable forecasting model in terms of accuracy and error metrics. However, the uncertainty and variability in these forecasts are also significant. This work combines point forecast with interval forecast to provide comprehensive information about the forecast uncertainty. In this work, solar irradiance forecasting is carried out using artificial intelligence (AI) techniques. Forecasting is done using seasonal autoregressive moving average with exogenous factors (SARIMAX), support vector regression (SVR), long short term memory (LSTM) techniques and performance is evaluated. SVR model exhibited the best performance with R 2 values of 0.97 and 0.96 for winter and summer respectively and 0.85 for monsoon and post-monsoon seasons. This is followed by forecast error distribution studies and uncertainty analysis. For this, SVR forecast error data is fitted using laplace distribution. Uncertainty study is carried out using confidence intervals and coverage rates. Excellent coverage rates are obtained for various confidence levels for all seasons, indicating the appropriate fitting of error distribution. For the narrow 85% confidence band, coverage rates of 89%, 95%, 90%, and 88% are obtained for winter, summer, monsoon and post-monsoon respectively. The work emphasizes the need for errordistribution studies, modeling of forecast errors and their application in providing reliable forecast intervals with the perspective of enhancing system reliability. Keywords Solar forecasting, Uncertainty analysisEnergy crisis is a serious concern all over the globe in the recent years. Global warming and climate crisis add to the problem. Energy needs are increasing day by day. Traditional fossil-fuel based energy generation has its own setbacks. The major contributor for global warming is fossil fuel combustion. Replacing fossil fuel energy with renewable energy resources has several advantages. Renewable resources like solar and wind are easily available, and also pollution free at source. The economic benefits of renewable energy resources are also large. Renewable energy integration in the power and energy market is the primary solution to address the energy and climate crisis 1 . As against the conventional, centralized technology, distributed generation involves energy generation at or near user ends, mainly multiple renewable resources.The concept of microgrid is gaining significance globally. Microgrids are low voltage grids, comprising of distributed energy sources which can operate both in grid-connected and disconnected mode. It consists of energy sources, storage units, and loads with a well-defined electrical boundary. Microgrids can operate along with the utility grid or can operate independently. These greatly support the integration of r...