{"id":"W2609397731","doi":"10.1109/tsg.2017.2697360","title":"A Novel Dynamic Power Routing Scheme to Maximize Loadability of Islanded Hybrid AC/DC Microgrids Under Unbalanced AC Loading","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Qatar National Research Fund; University of Waterloo","keywords":"Microgrid; Control theory (sociology); Voltage droop; Converters; Distributed generation; Controller (irrigation); Power (physics); AC power; Computer science; Power flow; Engineering; Electric power system; Voltage; Control (management); Voltage regulator; Electrical engineering; Renewable energy","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002344938,0.0003291206,0.0004371803,0.0001695137,0.0003444913,0.0001143531,0.0003913667,0.0001261868,0.0001320498],"category_scores_gemma":[0.00002014364,0.0003422281,0.0002244043,0.0001531086,0.00007909102,0.0003064579,0.00000634028,0.000347586,0.0000548664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001973075,"about_ca_system_score_gemma":0.00004142072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001107731,"about_ca_topic_score_gemma":0.0001576649,"domain_scores_codex":[0.9983925,0.00002262871,0.0004886612,0.0004067505,0.0002260237,0.0004634818],"domain_scores_gemma":[0.9986854,0.00006783865,0.0001211827,0.0008417495,0.0001352242,0.0001486733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002059175,0.000226443,0.0001746059,0.00007526374,0.000238471,0.000003499763,0.000224857,0.432957,0.556067,0.000009042844,0.0001486902,0.00966918],"study_design_scores_gemma":[0.004955614,0.0002190005,0.01015452,0.0003281132,0.0001843183,0.00005194785,0.0001497036,0.510123,0.4716451,0.00006407571,0.0009491399,0.001175492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2904454,0.00006415432,0.7064766,0.0001943216,0.00175551,0.0003477415,0.0002068852,0.0002168792,0.0002925598],"genre_scores_gemma":[0.9912395,0.00006147153,0.008311396,0.0000897694,0.00007011768,0.00004718753,0.00001219392,0.00006299666,0.0001053932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.700794,"threshold_uncertainty_score":0.999903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035021340369197,"score_gpt":0.2284649717699379,"score_spread":0.218114758366246,"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."}}