The relationship between energy demand and variables such as economic
activity and weather is well established. However, this paper aims to explore
the connection between energy demand and other social aspects, which receive
little attention. Through the use of natural language processing on a large
news corpus, we shed light on this important link. This study was carried out
in five regions of the UK and Ireland and considers multiple horizons from 1 to
30 days. It also considers economic variables such as GDP, unemployment and
inflation. We found that: 1) News about military conflicts, transportation, the
global pandemic, regional economics, and the international energy market are
related to electricity demand. 2) Economic indicators are more important in the
East Midlands and Northern Ireland, while social indicators are more useful in
the West Midlands and the South West of England. 3) The use of these indices
improved forecasting performance by up to 9%.

通过对大量新闻语料库进行自然语言处理，本研究探讨了能源需求与社会其他方面的联系，并发现军事冲突、交通运输、全球大流行、地区经济和国际能源市场等因素与电力需求有关。此外，研究还发现在英国的五个地区，经济指标对于东米德兰兹和北爱尔兰而言更为重要，而社会指标对于西米德兰兹和英格兰西南部更为有用。此外，利用这些指标可以提高预测性能最多达到 9%。