{"id":"W1549224792","doi":"10.1109/jestpe.2015.2432677","title":"A Sensorless Adaptive Maximum Power Point Extraction Method With Voltage Feedback Control for Small Wind Turbines in Off-Grid Applications","year":2015,"lang":"en","type":"article","venue":"IEEE Journal of Emerging and Selected Topics in Power Electronics","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Maximum power point tracking; Wind power; Anemometer; Control theory (sociology); Computer science; Power optimizer; Maximum power principle; Wind speed; Renewable energy; Voltage; Engineering; Electrical engineering; Control (management); Inverter","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":[0.0007448411,0.0002657145,0.0005429933,0.0003862309,0.00004136088,0.00004979701,0.000154263,0.0001648101,0.00000229468],"category_scores_gemma":[0.00008225493,0.000235905,0.00007059274,0.0005078863,0.00002028579,0.0002090508,0.000006405243,0.0007506175,6.010967e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003885061,"about_ca_system_score_gemma":0.0002131612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002325779,"about_ca_topic_score_gemma":0.0003838646,"domain_scores_codex":[0.9982827,0.0001005245,0.0006795109,0.0002144298,0.0002190817,0.0005037303],"domain_scores_gemma":[0.9987111,0.0001959654,0.0002523559,0.0001621722,0.0005402486,0.0001381628],"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":[0.005775135,0.001043704,0.01832971,0.0004414638,0.002292035,0.0002932335,0.01134651,0.8151522,0.1070535,0.004500614,0.004260752,0.02951116],"study_design_scores_gemma":[0.06918641,0.009498649,0.02506062,0.00147576,0.0008509041,0.00423293,0.005296122,0.6735784,0.02090061,0.01425176,0.1714107,0.004257135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5159041,0.006401829,0.4751705,0.0004581957,0.0007111808,0.0008972203,0.00001558656,0.000063378,0.0003780193],"genre_scores_gemma":[0.9951348,0.000114058,0.004129752,0.00003537042,0.0003983279,0.00003816164,0.000003137789,0.00005446042,0.00009193177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4792307,"threshold_uncertainty_score":0.9619926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192820043607933,"score_gpt":0.2477196592970841,"score_spread":0.2357914588610048,"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."}}