{"id":"W2799132062","doi":"10.1109/smartgridcomm.2017.8340719","title":"Application of energy storage systems for frequency regulation service","year":2017,"lang":"en","type":"article","venue":"","topic":"Frequency Control in Power Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Energy storage; Computer science; Frequency deviation; Automatic frequency control; Electric power system; Schedule; CVAR; Frequency regulation; Reliability engineering; Power (physics); Expected shortfall; Engineering; Risk management; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000311545,0.0004383973,0.0003627728,0.0002009873,0.0002424512,0.0005635147,0.0004805874,0.0003675802,0.002527009],"category_scores_gemma":[0.0006725867,0.0001135295,0.0002839112,0.0003915706,0.0002888272,0.000443453,0.0004414431,0.0004656987,0.0002764123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003195537,"about_ca_system_score_gemma":0.0004679546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001211123,"about_ca_topic_score_gemma":0.001316053,"domain_scores_codex":[0.9997376,0.00008021556,0.00001432557,0.0000461303,0.0000915128,0.0000302852],"domain_scores_gemma":[0.9997005,0.0001370636,0.00005457637,0.00003525843,0.0000589284,0.00001371658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003653536,0.0001358982,0.003266243,0.0003761674,0.0001057863,0.0006498758,0.0001169613,0.6386621,0.05362864,0.03891954,0.003349402,0.260424],"study_design_scores_gemma":[0.00003264163,0.0002003276,0.001225613,0.00003053042,0.00004693595,0.0003088887,0.00004087647,0.9564513,0.02177793,0.01075145,0.00911733,0.00001624204],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09440891,0.001642966,0.8882514,0.0006326895,0.0001365787,0.00008537847,0.0001175173,0.0006907459,0.01403384],"genre_scores_gemma":[0.9841471,0.0004499743,0.01399459,0.00002988842,0.00002828669,0.00001476466,0.00002951256,0.0000137488,0.001292105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002527009,"threshold_uncertainty_score":0.008453667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01094099224222189,"score_gpt":0.2183418913170811,"score_spread":0.2074008990748592,"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."}}