{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008670721,0.00008999833,0.0001158573,0.00004258624,0.0001334539,0.00003105466,0.0000981114,0.00002521201,0.0004109895],"category_scores_gemma":[0.000003942497,0.00008891345,0.00004855149,0.0000623587,0.00000545437,0.00007541251,0.00001288962,0.00006024121,0.00000412032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000605612,"about_ca_system_score_gemma":0.00001383699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008486478,"about_ca_topic_score_gemma":0.000009714224,"domain_scores_codex":[0.99951,0.0000137977,0.0001283809,0.0001204874,0.00005452707,0.0001728214],"domain_scores_gemma":[0.9997909,0.00001742932,0.00001322599,0.0001055527,0.00002258622,0.00005027228],"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":[0.00003451476,0.00002501089,0.00001252528,0.000003777897,0.00003813302,4.191358e-7,0.00006838424,0.9173527,0.0397771,0.0004735559,0.002107836,0.04010604],"study_design_scores_gemma":[0.001328552,0.0002106233,0.00001105749,2.475236e-7,0.00001282345,0.000001728384,0.00008325034,0.9844763,0.001690716,0.00002730837,0.01202982,0.0001276234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0596928,0.0008036164,0.9360743,0.00006833798,0.001006385,0.0007958382,0.00008968693,0.0007805963,0.000688493],"genre_scores_gemma":[0.9949876,0.00001245214,0.003966096,0.0002312757,0.0001791979,0.0003125408,0.00005773553,0.00003353852,0.0002195325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9352948,"threshold_uncertainty_score":0.4500046,"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."}}