## 3 Results and Discussion
### Future Generation Forecasting  
Long-term electricity forecasting studies can include the peak load forecasting as well as electricity generation forecasting as in the current study [18]. Each of the two forecasting approaches contributes to providing different information for the experts and reveals a comprehensive overview of the electricity grid. One of the common misconceptions is that the generated electricity's annual peak occurs on the same day as the annual peak load. However, this may not be true for all datasets and case studies due to several factors. These factors can be attributed to the nature of the annual peak load date, resulting from the high consumer consumption at a specific time due to temperature, the time during the day, and consumption pattern. The annual peak generation is associated with these factors during the whole day and not at a specific time. As a result, the annual peak load dates are not identical with the annual peak generation dates. Table 5 provides a comparison between the peak load dates, from [18], and the peak generation of this study in Kuwait between 2015-2020. It is evident that forecasting the peak load and the peak generation would be advantageous to policymakers to prepare for the expected loads in terms of logistics needed for the electrical generation. Moreover, it would help in making decisions for expanding the electricity grid and to assess the need for boosting from the current interconnected GCC power grid. The long-term electric generation forecasting for the year 2020-2030 of the five models, and the actual data are tabulated in Table 11. The forecasted data of the annual electrical generation of the five models are plotted in Figure 6. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Year**} & \multirow{2}{*}{**Date**} & \multirow{2}{*}{**Peak Load**} & \
\begin{tabular}{c} **Generation of** \\ **the Same Date** \\ \end{tabular} &
\begin{tabular}{c} **Peak** \\ **Generation** \\ \end{tabular} & \multirow{2}{*}{**Date**} \\ \hline
2015 & 30 August 2015 & 12,810 & 279,228 & 279,228 & 30 August 2015 \\
2016 & 15 August 2016 & 13,390 & 288,058 & 290,304 & 2 August 2016 \\
2017 & 26 July 2017 & 13,800 & 290,288 & 299,694 & 14 August 2017 \\
2018 & 10 July 2018 & 13,910 & 284,718 & 300,231 & 12 July 2018 \\
2019 & 27 June 2019 & 14,420 & 318,531 & 318,531 & 27 June 2019 \\
2020 & 30 July 2020 & 14,960 & 317,677 & 326,437 & 31 July 2020 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The annual peak load and the matching generation and the annual peak generation and date. Figure 6: The long-term annual electrical generation forecasting of the five models. According to the forecast of the triple seasonality of the Holt-Winters model, the annual electric generation in Kuwait will reach about 92,535,555 kWh by the year 2030. This forecasted value is around 23% higher than the actual generation in 2019. The other models are higher in the forecasted annual electrical generation, which reaches up to 102,262,507 kWh in single seasonality of Holt-Winters models, which is higher by 36% than the generation of 2019. The management needs to assess the needed facility or equipment needed for such a generation to be established and prepared. The forecasted monthly consumptions of the coming two years for different models are depicted in Table 10 and Figure 7. In addition to the study's primary aim, analyzing the monthly electrical generation can provide mid-term information for the logistics needed for this generation. The highest generation is clearly in two months, July and August, where Kuwait has its harshest weather temperature and humidity. Moreover, the higher electrical generation period of each year is between May and September. The maximum monthly electrical generation in 2021 is July for all the models, whereas August is the maximum in 2022 for the PSR, PMR, and HWSS models, and July 2022 is the maximum for the HWDS and HWTS models.