{"id":"W3110803906","doi":"10.17762/de.vi.969","title":"Convergence Adjustment Method Based on Approximate Power Flow and Voltage Stability","year":2020,"lang":"en","type":"article","venue":"Design Engineering","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convergence (economics); Sensitivity (control systems); Voltage; Computer science; Control theory (sociology); Stability (learning theory); Power flow; Electric power system; Newton's method; Mathematical optimization; Power (physics); Process (computing); Mathematics; Engineering; Electronic engineering; Nonlinear system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001563419,0.0006369918,0.0008123028,0.00130409,0.0006434565,0.001089996,0.0008150968,0.0005625292,0.003539297],"category_scores_gemma":[0.005215243,0.0003244878,0.0007274161,0.0008416726,0.0006008539,0.001602756,0.0007311463,0.00108223,0.0006558479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005526303,"about_ca_system_score_gemma":0.001135707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003976194,"about_ca_topic_score_gemma":0.001971773,"domain_scores_codex":[0.9990188,0.0002846221,0.00006524675,0.000184117,0.0003968896,0.00005029694],"domain_scores_gemma":[0.9987929,0.0004220626,0.0001000793,0.00008492309,0.0005675781,0.00003242178],"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":[0.0001772871,0.00006905914,0.003165113,0.0002920379,0.00009228672,0.0001121409,0.0003963223,0.5789047,0.01050573,0.04229614,0.003187393,0.3608018],"study_design_scores_gemma":[0.000009146567,0.0000238986,0.000290821,0.000008877568,0.000008149203,0.00003173348,0.0000129354,0.9956701,0.0008783652,0.002055847,0.0009998595,0.00001030549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005722933,0.0001137998,0.9918302,0.00005121977,0.00005391792,0.00004376595,0.00001241726,0.0002349909,0.00193687],"genre_scores_gemma":[0.5272912,0.0006520177,0.4626225,0.00009648082,0.0001865294,0.0004191527,0.0001632121,0.0003122368,0.00825663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003976194,"threshold_uncertainty_score":0.01184011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02395869507967792,"score_gpt":0.2136391458783473,"score_spread":0.1896804507986694,"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."}}