{"id":"W1673327244","doi":"10.1109/pesgm.2015.7286334","title":"PMU analytics for decentralized dynamic state estimation of power systems using the Extended Kalman Filter with Unknown Inputs","year":2015,"lang":"en","type":"article","venue":"","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Phasor; Extended Kalman filter; Phasor measurement unit; Control theory (sociology); Kalman filter; Electric power system; Context (archaeology); Computer science; Rotor (electric); Synchronous motor; Fault (geology); Control engineering; AC power; Permanent magnet synchronous generator; Engineering; Power (physics); Voltage; Control (management)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003141844,0.0001220029,0.00020662,0.00005242362,0.00003032238,0.00004329607,0.00009591499,0.00003854257,0.00001389678],"category_scores_gemma":[0.00003692581,0.00007658805,0.00003683689,0.0001750717,0.00003075858,0.0001288348,0.00001085381,0.00004086455,0.000001384173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001249227,"about_ca_system_score_gemma":0.0000458798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002333528,"about_ca_topic_score_gemma":0.00005501749,"domain_scores_codex":[0.9991741,0.00004345218,0.0003245946,0.0001120241,0.0001726154,0.0001732585],"domain_scores_gemma":[0.9993423,0.00004760243,0.00007223328,0.0002662992,0.0001985027,0.00007306028],"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":[0.00003119144,0.00001510351,0.0001556746,0.00009232763,0.0000501578,2.947546e-7,0.0005016987,0.9985962,0.00007021486,0.0003307474,0.0001265605,0.00002981203],"study_design_scores_gemma":[0.0006374544,0.00003829689,0.0001946058,0.00003635552,0.00002823297,0.000004961701,0.0001718719,0.9980793,0.0002526605,0.00004402429,0.0004054198,0.0001068399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05908908,0.00008315098,0.939155,0.00002660144,0.0002442519,0.0005297098,0.00002357546,0.0001028272,0.0007457603],"genre_scores_gemma":[0.9878237,0.000003021277,0.01193621,0.000009553097,0.000001000142,0.00001408121,0.00001755813,0.00002155486,0.0001732744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9287347,"threshold_uncertainty_score":0.312317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02352735301321285,"score_gpt":0.2634387444771245,"score_spread":0.2399113914639117,"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."}}