论文标题
研究Covid-19对使用天气正常化的大学宿舍的电力消耗的影响
Investigation of the Impacts of COVID-19 on the Electricity Consumption of a University Dormitory Using Weather Normalization
论文作者
论文摘要
这项研究调查了COVID-19大流行对美国南部大学宿舍建筑物的电力消耗的影响。该大学宿舍建筑的历史电力消耗数据以及校园内气象站的天气数据，该数据从2017年1月1日至2020年7月31日收集，用于分析。利用了四个逆数据驱动的预测模型，即人工神经网络，长期短期记忆复发性神经网络，极端的梯度增强和轻度梯度提升机，以说明天气状况的影响。结果表明，与由于Covid-19的校园关闭期间的预测值相比，物镜的总消耗量降低了近41％（约276,000 kWh（约合942 mmbtu））。此外，每日载荷比（DLR）也有很大变化。通常，DLR从2020年3月下半年从80％逐渐下降到近40％，在4月，5月和2020年6月的30％至60％之间保持相对稳定的水平，然后在2020年7月慢慢恢复到正常容量的80％。
This study investigated the impacts of the COVID-19 pandemic on the electricity consumption of a university dormitory building in the southern U.S. The historical electricity consumption data of this university dormitory building and weather data of an on-campus weather station, which were collected from January 1st, 2017 to July 31st, 2020, were used for analysis. Four inverse data-driven prediction models, i.e., Artificial Neural Network, Long Short-Term Memory Recurrent Neural Network, eXtreme Gradient Boosting, and Light Gradient Boosting Machine, were exploited to account for the influence of the weather conditions. The results suggested that the total electricity consumption of the objective building decreased by nearly 41% (about 276,000 kWh (942 MMBtu)) compared with the prediction value during the campus shutdown due to the COVID-19. Besides, the daily load ratio (DLR) varied significantly as well. In general, the DLR decreased gradually from 80% to nearly 40% in the second half of March 2020, maintained on a relatively stable level between 30% to 60% in April, May, and June 2020, and then slowly recovered to 80% of the normal capacity in July 2020.
