{"id":"W2887457333","doi":"10.1049/iet-rpg.2018.5392","title":"Load frequency control by de‐loaded wind farm using the optimal fuzzy‐based PID droop controller","year":2018,"lang":"en","type":"article","venue":"IET Renewable Power Generation","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Voltage droop; PID controller; Control theory (sociology); Automatic frequency control; Controller (irrigation); Fuzzy logic; Computer science; Fuzzy control system; Control engineering; Engineering; Control (management); Temperature control; Electrical engineering; Voltage regulator; Telecommunications; Voltage","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006574116,0.0003737801,0.0004042742,0.00008526612,0.0003194724,0.0002639171,0.0002947257,0.0002478222,0.0001896487],"category_scores_gemma":[0.00008689066,0.0003062689,0.0001393886,0.000249241,0.00009315638,0.0002238747,0.00001532187,0.0001897649,0.00006816968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000405866,"about_ca_system_score_gemma":0.0002081839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001058145,"about_ca_topic_score_gemma":0.0003625395,"domain_scores_codex":[0.9978191,0.0001879607,0.0005383209,0.0003745751,0.0004372957,0.0006427378],"domain_scores_gemma":[0.9988418,0.00007699363,0.0001312333,0.0004984364,0.0003039754,0.0001475767],"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":[0.00003511656,0.00002155951,0.0001812999,0.000006677665,0.00009678661,0.000002427984,0.0001614393,0.3080849,0.6790116,0.00002912249,0.01225693,0.0001120661],"study_design_scores_gemma":[0.003835037,0.0001390308,0.00005039634,0.00002347625,0.00008875888,0.00001465081,0.000033755,0.8650656,0.118972,0.00004461862,0.01134594,0.0003866778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4217734,0.003425043,0.5611514,0.0005621042,0.002744253,0.001387175,0.0001059955,0.0005067354,0.0083439],"genre_scores_gemma":[0.9952378,0.000004257314,0.0016322,0.0005855257,0.001794198,0.00006873808,0.00003597835,0.00008712243,0.0005541883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5734644,"threshold_uncertainty_score":0.999939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298687864236729,"score_gpt":0.2214461466476125,"score_spread":0.2084592680052453,"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."}}