{"id":"W2540882355","doi":"10.1109/sae.2009.5534871","title":"Effects of wind power on day-ahead reserve schedule","year":2009,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Wind power; Power system simulation; Schedule; Electric power system; Penetration (warfare); Reserve requirement; Computer science; Wind speed; Benchmark (surveying); Environmental science; Simulation; Power (physics); Meteorology; Operations research; Economics; Engineering; Electrical engineering; Monetary economics; Geography; Central bank; Physics","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":[0.001003443,0.0005618822,0.0006055722,0.0003080084,0.0003695785,0.0009979536,0.0004373803,0.0008539464,0.002318576],"category_scores_gemma":[0.005691733,0.0003330447,0.0004073164,0.0003366913,0.0005273857,0.0007690822,0.0003471598,0.0008740345,0.0002376584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006502278,"about_ca_system_score_gemma":0.000478024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005669357,"about_ca_topic_score_gemma":0.006056101,"domain_scores_codex":[0.9996524,0.000158254,0.00001674603,0.00004053113,0.00004985576,0.0000821832],"domain_scores_gemma":[0.9962161,0.002909159,0.0003107481,0.0001478393,0.0002276511,0.0001884518],"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":[0.0002442859,0.00005455504,0.003041398,0.00003122956,0.0000399062,0.000227945,0.00003102038,0.990501,0.00235528,0.0008548946,0.0002901449,0.002328224],"study_design_scores_gemma":[0.00008937551,0.0005966983,0.01018788,0.0000147121,0.00006056279,0.00009344685,0.0001463796,0.9836992,0.003102984,0.001393328,0.0005755729,0.00003977097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902467,0.0001317782,0.004679554,0.0001698902,0.0000404815,0.00002784331,0.0003288743,0.00009492151,0.004279985],"genre_scores_gemma":[0.9991393,0.00003861529,0.0004402478,0.00001927772,0.00000243192,0.000005383763,0.00006774299,0.00001824871,0.0002688032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005669357,"threshold_uncertainty_score":0.01127273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003477806844238603,"score_gpt":0.1963689408313104,"score_spread":0.1928911339870718,"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."}}