[:         "input": "Based on the historical load data, please predict the load consumption in the next day. The region for prediction is QLD. The start date of historical data was on 2019-10-29 that is Weekday, and it is not a public holiday. The data frequency is 30 minutes per point. Historical data covers 1 day. The date of prediction is on 2019-10-30 that is Weekday, and it is not a public holiday. Weather of the start date: the minimum temperature is 288.98; the maximum temperature is 297.67; the humidity is 68.0; the pressure is 1022.0.  Weather of the prediction date: the minimum temperature is 288.16; the maximum temperature is 299.94; the humidity is 56.0; the pressure is 1019.0. In 2019-10-29 00:00:00, the news that had the Long-Term Effect on Future Load Consumption is that Labor leader Anthony Albanese is set to reshape his party\u2019s policy arguments for greater efforts to limit climate change and present innovation as the hope of the economy. The region that may be influenced is National. The rationality is that Policy and regulation aimed at limiting climate change often involve long-term investments in energy efficiency and renewable energy infrastructure, which can lead to a decrease in load consumption as more sustainable energy sources are adopted and efficiency measures are implemented.In 2019-10-29 00:30:00, the news that had the Short-Term Effect on Today's Load Consumption is that Strawberry lovers are ready for delicious pickings as warmer weather ripens up the fruit in the Adelaide Hills farm. The region that may be influenced is SA. The rationality is that Seasonal factors such as warmer weather can lead to an increase in load consumption as more energy is used for cooling systems and refrigeration in agricultural sectors and food storage facilities.In 2019-10-29 07:07:00, the news that had the Real-Time Direct Effect on Today's Load Consumption is that A dozen businesses have been gutted by a massive fire at a Sydney factory, which has been burning for more than 16 hours. The region that may be influenced is NSW. The rationality is that Emergencies like a massive fire typically result in an immediate spike in load consumption due to the requirement for lighting, machinery, and other equipment used by first responders, as well as potential impact on the grid stability in the affected area.",