使用Facebook Prophet进行全球新冠肺炎疫苗接种背景下的负荷预测

Kevinaldo Barevan, Abdul Halim
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引用次数: 0

摘要

电力负荷预测是电力系统可靠、稳定、经济运行的重要环节。负荷预测过程在小时到年的范围内进行。本研究的重点是短期负荷预测(STLF),在一般情况下,天气条件和人类活动的影响非常大。在本研究中,我们将进一步研究Covid-19大流行对电力负荷变化的影响,即疫苗数量和社区流动性水平。对疫苗效果的研究是这一研究的新热点。在电力负荷预测中,将使用修改后的Facebook Prophet方法。这一修订的目的是使大流行的影响能够包括在模型中。为了验证该模型的有效性,以宾夕法尼亚州电力负荷数据为例进行了研究。2021年加入疫苗接种变量后,MAPE值为15.26%。使用的数据量可能会影响预测过程和MAPE结果。因此,与其他研究相比,MAPE值是相当好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load Forecasting in the Context of Global Covid-19 Vaccination Using Facebook Prophet
Forecasting the electrical energy load is a very important initial stage in the operation of the electricity system so that the system works reliably, stably, and economically. The load forecasting process is carried out in the range of hours to years. This study focuses on short-term load forecasting (STLF) where in general the effects of weather conditions and human activities are very influential. In this study, we will study further the effects of the Covid-19 pandemic, namely the number of vaccines and the level of community mobility on changes in electrical loads. The study of the effect of the vaccine is the new point of this research. In electrical load forecasting, the revised Facebook Prophet method will be used. This revision is intended so that the effects of the pandemic can be included in the model. To test the effectiveness of the proposed model, a case study of the Pennsylvania electrical load data was carried out. In 2021 with the addition of the vaccination variable, the MAPE value is 15.26%. The amount of data used could possibly affect the forecasting process and MAPE results. So, the MAPE value is quite good when compared to other studies.
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