*2.2. Weather Data*

Primary weather data collected from field observations are the most optimal weather data to explain real-world weather conditions. While this fundamental data is somewhat inexpensive due to the requirement of a real-time measuring device, it is also highly costly. Furthermore, to use the observation data as a component of the energy load forecasting system, the observation data must be delivered to the forecasting system continuously, which necessitates the usage of a reliable measuring instrument. For this work, we will employ reanalysis weather data instead of real-time data as input for a machine learning model to be used as a feature in the electricity load forecasting system. This study uses the reanalysis weather data from the European Centre for Medium-Range Weather Forecasts, often known as the ECMWF, collected from the ERA5 model [30]. Since 1979, hourly weather data has been available, with spatial resolution varying between 0.25◦ and 0.75◦. Weather parameters such as temperature, solar radiation, wind speed, rainfall rate, pressure, and relative humidity are investigated in this study.

To determine the quality of ERA5 weather parameter data, we compared the reanalysis data with observation data collected on Bali Island using an Automatic Weather Station (AWS) that has a temporal grid of 20 min. The AWS is positioned at latitude and longitude 115.167◦ E and 8.75◦ S. This study employs the most recent reanalysis ERA5 data from the nearest accessible grid to the AWS site, located at 115.00◦ E and 8.50◦ S, as shown in Figure 3. Indeed, the locations are quite a distance apart from one to another. Nonetheless, as seen in Figure 4, we compare many weather parameters from the ERA5 with the observed AWS data to identify any differences. We examine four meteorological factors: rainfall rate, solar radiation, temperature, and wind speed in Figure 4 during June 2019.

**Figure 3.** Location of Automatic Weather Station (AWS) in Ngurah Rai, Bali, and location of point for ERA5 data, in Bali Island, Indonesia.

**Figure 4.** *Cont*.

**Figure 4.** Comparison of weather data from ERA5-ECMWF (red line with triangle) and Automatic Weather Station or AWS (blue line) for: (**a**) Rainfall Rate; (**b**) Solar Radiation; (**c**) Temperature; (**d**) Wind speed.

As shown in Figure 4, the solar radiation and wind speed, in particular, show a relatively similar trend between ERA5 and the observation data from AWS. In contrast, the other two parameters, i.e., the temperature and the rainfall rate, show a similar trend but with a different magnitude between ERA5 and the observation data from AWS. Because a significant distance separates the ERA5 point and the AWS point locations, this disparity might be caused by differences in local temperature and rainfall rates that are potentially highly different. The ERA5 data offers a good representation of the trend of meteorological parameters for Bali Island when compared to other data sources.
