{"id":"W4404799568","doi":"10.1016/j.apenergy.2024.124951","title":"Modeling and energy management of hangar thermo-electrical microgrid for electric plane charging considering multiple zones and resources","year":2024,"lang":"en","type":"article","venue":"Applied Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microgrid; Electric potential energy; Energy management; Automotive engineering; Electric power; Energy (signal processing); Engineering; Environmental science; Electrical engineering; Power (physics); Renewable energy; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002388171,0.0007296556,0.0006795278,0.0003530762,0.0005733595,0.00157647,0.001008568,0.0008491424,0.002173746],"category_scores_gemma":[0.0003075762,0.0003274863,0.0008159163,0.0004602021,0.0005778216,0.0006838562,0.0007327156,0.0005396125,0.0002881968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001289237,"about_ca_system_score_gemma":0.001320962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04959428,"about_ca_topic_score_gemma":0.03430397,"domain_scores_codex":[0.9998504,0.00004079096,0.000007591121,0.00003424164,0.00003475695,0.00003209782],"domain_scores_gemma":[0.9998915,0.00003111552,0.00002406775,0.000009027404,0.00003213243,0.00001203403],"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":[0.00001778702,0.00000857864,0.0004011792,0.00001687012,0.00001160706,0.00007635084,0.00001947313,0.9961278,0.0005545411,0.001604007,0.0001497765,0.001012137],"study_design_scores_gemma":[0.000002853302,0.00001237542,0.0001812621,0.000002329726,0.000005180279,0.000007035237,0.0000192942,0.9991373,0.00008846133,0.0003245442,0.0002167581,0.00000255373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4255781,0.001248948,0.4880272,0.0009595436,0.00016449,0.0002020057,0.001028889,0.0008865361,0.0819044],"genre_scores_gemma":[0.9875515,0.000344107,0.004149099,0.00003515421,0.00001313428,0.00007490287,0.0001411029,0.0000223198,0.007668778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04959428,"threshold_uncertainty_score":0.09861124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0054139733806756,"score_gpt":0.1752845509460747,"score_spread":0.1698705775653991,"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."}}