*5.1. OP-ELM Results*

The different experiments were conducted with different OP-ELM models, as described in Section 3. The lowest obtained errors per experiment are captured in Table 1. It was found that the OP-ELM model developed using variables for Experiment 2 and 50 hidden nodes achieved the lowest errors. This model achieved an sMAPE of 10.21%, MAE of 11.57%, and RMSE of 14.65%. These performance results are in bold in Table 1. This model was, therefore, developed without the demand as an input. Experiments 4 and 5's lowest obtained errors were higher than the lowest obtained errors in the other three experiments. The exclusion of the installed capacity, in Experiments 4 and 5, was observed to lead to an increase in the errors. In these experiments, the sMAPE increased by over 90% in comparison to the sMAPE in the other experiments. This increase in the errors was also observed to be approximately twice the observed errors in Experiment 2.


**Table 1.** OP-ELM experiments results.

A statistical significance test was conducted to determine if the results with the lowest errors from each experiment had a significant difference from the results with the overall lowest errors. The statistical significance test results are captured in Table 2. From the significance test results, a *p*-value of less than 0.05 was observed. Thus, the results are significantly different from each other. The exclusion of the demand, therefore, increases model forecasting error.

**Table 2.** OP-ELM models' lowest errors statistical significance test.

