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作 者:Vera van Zoest Karl Lindberg Fouad El Gohary Cajsa Bartusch
机构地区:[1]Department of Information Technology,Uppsala University,P.O.Box 337,Uppsala 75105,Sweden [2]Department of Systems Science for Defence and Security,Swedish Defence University,P.O.Box 27805,Stockholm 11593,Sweden [3]Department of Civil and Industrial Engineering,Uppsala University,P.O.Box 534,Uppsala SE-75121,Sweden
出 处:《Energy and AI》2023年第4期514-521,共8页能源与人工智能(英文)
基 金:This study is funded by the Swedish Energy Agency(Ener-gimyndigheten),as part of the E2B2 research program(project number P2021–00187).
摘 要:The COVID-19 pandemic has had drastic effects on societies around the world.Due to restrictions or recom-mendations,companies,industries and residents experienced changes in their routines and many people shifted to working from home.This led to alterations in electricity consumption between sectors and changes in daily patterns.Understanding how various properties and features of load patterns in the electricity network were affected is important for forecasting the network’s ability to respond to sudden changes and shocks,and helping system operators improve network management and operation.In this study,we quantify the extent to which the COVID-19 pandemic has led to shifts in the electricity consumption patterns of different sectors in Sweden.The results show that working from home during the pandemic has led to an increase in the residential sector’s total consumption and changes in its consumption patterns,whereas there were only slight decreases in the industrial sector and relatively few changes in the public and commercial sectors.We discuss the reasons for these changes,the effects that these changes will have on expected future electricity consumption patterns,as well as the effects on potential demand flexibility in a future where working from home has become the new norm.
关 键 词:Electricity consumption COVID-19 Smart meter data Regression model Demand response
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