{"id":"W2944258215","doi":"10.1109/tpwrs.2019.2916227","title":"Energy Management of AC–DC Hybrid Distribution Systems Considering Network Reconfiguration","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Control reconfiguration; Schedule; Mathematical optimization; Integer programming; Energy management; Energy management system; Linear programming; Computer science; Distributed generation; Power (physics); Energy (signal processing); Engineering; Algorithm; Electrical engineering; Mathematics; Renewable energy; Embedded system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001516854,0.0001915051,0.000292066,0.00007443214,0.00006490362,0.00006909146,0.00009308475,0.00008480725,0.00004721177],"category_scores_gemma":[2.948078e-7,0.000200917,0.00009285111,0.0001840794,0.00001277297,0.0001768807,7.142667e-7,0.0001020484,0.00005694376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001291515,"about_ca_system_score_gemma":0.000009541279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000576448,"about_ca_topic_score_gemma":0.000003501648,"domain_scores_codex":[0.9988083,0.00005303924,0.0004904006,0.0002092825,0.0001895455,0.00024939],"domain_scores_gemma":[0.9994249,0.00003727689,0.00009768696,0.0003115808,0.00007227711,0.00005630524],"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":[0.00002226805,0.00002194014,0.000008004272,0.0002510525,0.0001970924,0.000003341589,0.00002929846,0.9962484,0.0008637026,0.0005533066,0.0007204733,0.001081182],"study_design_scores_gemma":[0.0008811786,0.0001013539,0.0000409814,0.0006893174,0.00009542099,0.00004113601,0.0002087411,0.9695879,0.006520426,0.000008738185,0.02145281,0.0003720589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006999849,0.001283265,0.9818878,0.000008359615,0.006895022,0.0004801899,0.00009783291,0.0002502357,0.002097495],"genre_scores_gemma":[0.9987507,0.0004260908,0.00006401393,0.000005942749,0.00003217756,0.0000992354,0.00004762787,0.00003503273,0.0005391146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9917509,"threshold_uncertainty_score":0.8193159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004967920776952539,"score_gpt":0.168468009054409,"score_spread":0.1635000882774564,"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."}}