{"id":"W7106283972","doi":"10.1016/j.egyr.2025.11.057","title":"Using spatial-temporal flexibility of data center building in energy management of distribution grid coupled with multi-energy hubs and energy storage","year":2025,"lang":"en","type":"article","venue":"Energy Reports","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Data center; Flexibility (engineering); Grid; Energy consumption; Distribution center; Energy (signal processing); Energy storage; Energy management; Distribution (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003788556,0.000507071,0.0003414333,0.0002242166,0.000398762,0.0008292075,0.000724581,0.0004527576,0.001476103],"category_scores_gemma":[0.0005069002,0.0002824813,0.0006995038,0.0005477241,0.0005899506,0.001356925,0.0007605691,0.0006135263,0.00009307685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008197055,"about_ca_system_score_gemma":0.0006431285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008920455,"about_ca_topic_score_gemma":0.01103117,"domain_scores_codex":[0.9997475,0.00008018185,0.00001127907,0.00005437366,0.00005986959,0.00004685176],"domain_scores_gemma":[0.9998492,0.0000604439,0.00003271384,0.0000154585,0.00002792887,0.00001432524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000245011,0.000008128797,0.0004428605,0.00002022555,0.00001293147,0.00008460553,0.00001802717,0.9864222,0.001003045,0.008702831,0.0001076698,0.003153121],"study_design_scores_gemma":[0.000003157086,0.00001643698,0.00018093,0.000002777157,0.000006045886,0.00001475848,0.00001710927,0.9968521,0.000297198,0.002244334,0.0003605285,0.00000460498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1061808,0.0005063536,0.881068,0.0003474145,0.00006326986,0.00004285325,0.000159477,0.0001457692,0.01148604],"genre_scores_gemma":[0.9843898,0.0002172087,0.01389098,0.00001912832,0.00001351411,0.00002528059,0.00004123758,0.00001630878,0.001386561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008920455,"threshold_uncertainty_score":0.01773709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0200246820932741,"score_gpt":0.2560596278798501,"score_spread":0.2360349457865761,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}