The　operation　and　maintenance　(O&M)　of　buildings　plays　an　important　role　in　ensuring　that　the　buildings　work　normally,　as　well　as　reducing　the　damage　caused　by　functional　errors.　There　are　obvious　problems　in　the　traditional　O&M　modality,　and　an　effective　way　to　solve　them　is　to　make　the　model　smarter.　In　this　paper,　a　digital　twin　framework　for　building　operation　is　proposed,　which　consists　of　two　key　components:　a　digital　twin　O&M　model　and　a　machine　learning　algorithm.　The　process　of　establishing　the　digital　twin　model　is　introduced　in　detail,　and　the　method　is　explained　according　to　the　structure,　equipment,　and　energy　consumption　characteristics　of　the　model.　A　mechanism　of　fusing　the　digital　twin　and　machine　learning　algorithm　is　proposed　and　the　prediction　process　based　on　an　artificial　neural　network　(ANN)　is　shown.　Finally,　based　on　a　systematic　summary　of　the　modeling　process　and　fusion　mechanism,　the　development　path　and　overall　structure　of　the　intelligent　O&M　system　utilizing　digital　twins　is　proposed.