Abstract
Electrical generation forecasting is essential for management and policymakers due to the crucial data provided for resource planning. This research employs the Prophet model with single and multiple regressors to forecast the electricity generation in Kuwait from 2020 to 2030. In addition, multiple seasonality Holt–Winters models were utilized as a benchmark for comparative analysis. The accuracy, generalization, and robustness of the models were assessed based on different statistical performance metrics. The triple seasonality Holt–Winters model achieved superior performance compared with the other models with R2 = 0.9899 and MAPE = 1.76%, followed by the double seasonality Holt–Winters model with R2 = 0.9893 and MAPE = 1.83%. Moreover, the Prophet model with multiple regressors was the third-best performing model with R2 = 0.9743 and MAPE = 2.77%. The forecasted annual generation in the year 2030 resulted in 92,535,555 kWh according to the best performing model. The study provides an outlook on the medium- and long-term electrical generation. Furthermore, the impact of fuel cost is investigated based on the five forecasting models to provide an insight for Kuwait’s policymakers.
Highlights
Accurate electrical generation forecasting is essential for the management and policymakers of local and national power plants
The generalized Holt–Winters model with multiple seasonality and initialization methods is used for forecasting the electrical generation of Kuwait until 2030
The seasonality is initialized by the method presented by Brockwell and Davis [39] and adopted by the National Institute of Standards (NIST) which depends on calculating the weights of the data series against the multiple seasonality pattern values
Summary
Accurate electrical generation forecasting is essential for the management and policymakers of local and national power plants. In a recent study [18], the Prophet model outperformed the well-established Holt–Winters model in Kuwait’s long-term peak load forecasting. The use of this method in forecasting is expected to spread due to its robustness and accuracy. One of this study’s main contributions is to explore the use of the Prophet forecasting model, with single and multi-regressors, and the multi-seasonality Holt–Winters model for the long-term forecasting of electricity generation. The originality of this study is that it explores the performance of prophet model with multi-regressors in long-term forecasting of electricity generation. The generalizability and robustness of the Prophet and Holt–Winters methods for forecasting long-term electricity generation are explored and presented
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