{"id":"W4286377370","doi":"10.1109/tsg.2022.3192910","title":"A Coordinated Restoration Method of Hybrid AC/DC Distribution Network for Resilience Enhancement","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China; Engineering and Physical Sciences Research Council; National Natural Science Foundation of China","keywords":"Interconnection; Bottleneck; Computer science; Resilience (materials science); Topology (electrical circuits); Network topology; Mathematical optimization; Control theory (sociology); Engineering; Mathematics; Computer network; Electrical engineering; Embedded system; Control (management)","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":[0.0004802622,0.0001669502,0.0002065846,0.00007026691,0.000354127,0.000016779,0.0001485083,0.00003629508,0.0001248895],"category_scores_gemma":[0.000009204491,0.0002034309,0.0001251358,0.0004748424,0.00003009239,0.0001563855,0.000002313451,0.0002453571,0.000009484424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004667584,"about_ca_system_score_gemma":0.00003984385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000277607,"about_ca_topic_score_gemma":0.00001377257,"domain_scores_codex":[0.9987132,0.00009450244,0.000378336,0.0002476763,0.0002660053,0.0003002954],"domain_scores_gemma":[0.9993742,0.0001190136,0.00007637597,0.000267094,0.0001030091,0.00006034142],"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":[0.0002027529,0.0001206303,0.000005452307,0.00003995706,0.00004537811,0.000001242056,0.00002910897,0.9610831,0.01895858,0.00009581605,0.01540733,0.004010709],"study_design_scores_gemma":[0.0008807414,0.0008843776,0.0001196291,0.0000333283,0.0001063085,0.00001737034,0.00006473638,0.4817686,0.4802039,0.0001487465,0.03542909,0.0003432005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02743077,0.00004610743,0.966454,0.00009647199,0.002688779,0.0005944071,0.00243341,0.000187441,0.00006864805],"genre_scores_gemma":[0.9925733,0.00001864207,0.005893565,0.0000212419,0.00008335501,0.0005962472,0.0006889837,0.0000267993,0.00009791547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9651425,"threshold_uncertainty_score":0.8295671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152915682076571,"score_gpt":0.2501092268550649,"score_spread":0.2385800700342992,"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."}}