{"id":"W3016565306","doi":"10.1109/icps48983.2019.9067613","title":"Load Frequency Control of an Autonomous Microgrid Using Robust Fuzzy PI Controller","year":2019,"lang":"en","type":"article","venue":"2019 8th International Conference on Power Systems (ICPS)","topic":"Frequency Control in Power Systems","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microgrid; Control theory (sociology); Automatic frequency control; PID controller; Fuzzy logic; Fuzzy control system; Controller (irrigation); Robust control; Computer science; Control engineering; Pi; Control (management); Control system; Engineering; Mathematics; Temperature control; Electrical engineering; Artificial intelligence; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008426681,0.0006420588,0.001118063,0.0004239868,0.00005977618,0.0002803473,0.001241292,0.000375976,0.0007835049],"category_scores_gemma":[0.00009074764,0.0006264742,0.0002641739,0.0001849224,0.0001048815,0.0007164346,0.00004648632,0.0004659563,0.0008982774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008780643,"about_ca_system_score_gemma":0.0004135139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001623913,"about_ca_topic_score_gemma":0.00008347904,"domain_scores_codex":[0.9957736,0.0002320414,0.001475146,0.0007186948,0.001117423,0.0006830706],"domain_scores_gemma":[0.9969743,0.0001819715,0.0005405631,0.000929748,0.001124809,0.000248546],"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":[0.0005884179,0.0005253489,0.00772843,0.0006548229,0.002735256,0.0001108853,0.001783537,0.2931495,0.4933376,0.1948061,0.003893792,0.0006863013],"study_design_scores_gemma":[0.007118246,0.0006361259,0.001171524,0.00112937,0.00009449333,0.0001703408,0.0004726058,0.9807875,0.001099854,0.000403269,0.005614309,0.001302419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5679514,0.006045355,0.04367542,0.0002539092,0.0512774,0.004988088,0.001888434,0.001220742,0.3226992],"genre_scores_gemma":[0.9975135,0.00003309466,0.0002653719,0.00009611522,0.0002821184,0.0000857921,0.00004484853,0.0001242868,0.001554832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6876379,"threshold_uncertainty_score":0.9998797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02140852192216056,"score_gpt":0.2403115917321134,"score_spread":0.2189030698099528,"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."}}