The　COVID-19　pandemic　has　caused　fluctuations　in　electricity　demand,　altering　people＇s　lifestyles　and　electricity　usage　patterns,　thereby　affecting　the　accuracy　of　demand　predictions.　However,　existing　studies　on　electricity　forecasting　have　not　adequately　considered　the　incorporation　of　COVID-19-related　features　and　the　analysis　of　electricity　usage　characteristics　across　different　regions　of　the　UK.　Therefore,　this　paper,　based　on　data　of　the　UK＇s　national　electricity　demand,　conducts　an　analysis　around　the　scenario　of　a　large-scale　health　emergency　in　society.　We　explore　the　changing　patterns　and　regional　characteristics　of　electricity　consumption　during　the　COVID-19　pandemic,　comparing　the　forecast　results　before　and　during　the　pandemic　to　illustrate　its　impact　on　the　UK＇s　electricity　demand.　By　introducing　COVID-19-related　features　into　the　models,　we　compare　the　forecast　results　before　and　after　their　inclusion.　The　results　indicate　that　the　COVID-19　pandemic　has　had　a　certain　impact　on　the　electricity　prediction　in　the　UK,　leading　to　a　22.8%　decrease　in　prediction　accuracy.　However,　the　models＇　correlation　improved　with　the　inclusion　of　COVID-19-related　features,　resulting　in　a　13.2%　enhancement　in　prediction　accuracy　compared　to　the　previous　models.　Additionally,　the　study　summarizes　other　factors　influencing　electricity　demand,　such　as　power　imports/exports　and　clean　energy　usage,　as　considerations　for　electricity　distribution　planning.　This　contributes　to　improving　the　accuracy　of　predicting　the　UK＇s　electricity　demand　during　COVID-19　pandemic,　enabling　the　government　to　adjust　power　dispatching　plans　reasonably　based　on　relevant　factors,　achieving　rational　distribution　and　efficient　scheduling　of　power　resources.　©　2024,　The　Author(s),　under　exclusive　licence　to　Springer-Verlag　GmbH　Germany,　part　of　Springer　Nature.