{"id":"W4313549804","doi":"10.1109/epec56903.2022.10000104","title":"An Improved Droop Controller for Virtual Synchronous Generators","year":2022,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Voltage droop; Control theory (sociology); Controller (irrigation); Converters; Computer science; Inertia; Permanent magnet synchronous generator; Automatic frequency control; MATLAB; Power (physics); Electric power system; Control engineering; Engineering; Voltage regulator; Control (management); Voltage; Electrical engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002505042,0.0006192913,0.0004976345,0.0004100255,0.000233368,0.000734792,0.0008875563,0.0004607708,0.001824316],"category_scores_gemma":[0.0004902757,0.0001597554,0.0002950483,0.0002779843,0.0002873936,0.0005403341,0.0004270393,0.0006732441,0.0004498415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002222144,"about_ca_system_score_gemma":0.0002842035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009937476,"about_ca_topic_score_gemma":0.0009472526,"domain_scores_codex":[0.9997929,0.0000334856,0.00001690013,0.00004889489,0.00009058322,0.00001723685],"domain_scores_gemma":[0.9998276,0.00003890015,0.00002722618,0.00002233548,0.0000725013,0.00001143511],"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":[0.0005628576,0.0001680998,0.0005666587,0.0005094627,0.0001161815,0.0005958726,0.0002418547,0.5842432,0.1194929,0.02337117,0.004442217,0.2656895],"study_design_scores_gemma":[0.00006334332,0.0002739172,0.0003126285,0.00001837404,0.0000247437,0.0001290277,0.00001143705,0.9794897,0.01087361,0.001418745,0.007362265,0.0000221468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03028898,0.000609675,0.9601222,0.0000856343,0.0002060719,0.0000890799,0.00007049939,0.001115503,0.007412434],"genre_scores_gemma":[0.9432626,0.0003619269,0.05203708,0.00008119698,0.00008469732,0.0001055185,0.0001064925,0.00004843876,0.003912079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001824316,"threshold_uncertainty_score":0.006102979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002977218888106184,"score_gpt":0.1798204770317497,"score_spread":0.1768432581436436,"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."}}