{"id":"W4239280722","doi":"10.32920/ryerson.14644032","title":"Modeling of Doubly Fed Induction Generators for Distribution System Power Flow Analysis","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Induction generator; Control theory (sociology); Robustness (evolution); Turbine; AC power; Wind power; Engineering; Grid; Electric power system; Control engineering; Voltage; Computer science; Power (physics); Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000166434,0.0001897236,0.0004462406,0.0001517269,0.00003758145,0.0000880472,0.00009559547,0.0002991251,0.00002460164],"category_scores_gemma":[0.00001045212,0.0001913877,0.0003516794,0.0003109133,0.000004597103,0.00006942912,0.00005185322,0.0001412821,5.410989e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002003322,"about_ca_system_score_gemma":0.00003425269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007298781,"about_ca_topic_score_gemma":0.00004586732,"domain_scores_codex":[0.9989967,0.00002012788,0.0004412953,0.0002594504,0.0001390673,0.0001433612],"domain_scores_gemma":[0.999258,0.000007714968,0.00006750047,0.0002799946,0.0003476133,0.0000391366],"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":[0.00001096736,0.00000842225,0.00001541519,0.0003090983,0.000923836,2.465212e-7,0.0000568145,0.9969071,0.0006019666,0.00006676545,0.00004510805,0.00105427],"study_design_scores_gemma":[0.0002032141,0.00000642814,0.00001105805,0.00004990646,0.0007756762,5.105733e-7,0.0001433251,0.9951397,0.003470582,0.000006576081,0.00001471997,0.0001782861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1071231,0.0008793427,0.8904517,0.000009207363,0.000768171,0.0002842917,0.0002010278,0.0002055234,0.00007768171],"genre_scores_gemma":[0.9759598,0.0000914322,0.01957587,0.000002357772,0.0001233497,0.00008248213,0.00413272,0.00002421823,0.000007815437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8708758,"threshold_uncertainty_score":0.7804562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009322022476249902,"score_gpt":0.1964421314892918,"score_spread":0.1871201090130419,"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."}}