{"id":"W2542023874","doi":"10.1109/tdc-la.2010.5762873","title":"The impact of wind power variability and curtailment on ramping requirements","year":2010,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Wind power; Residual; Reliability engineering; Base load power plant; Grid; Computer science; Load management; Electric power system; Power grid; Service (business); Power demand; Automotive engineering; Peak demand; Demand response; Power (physics); Engineering; Electricity; Electrical engineering; Power consumption; Business","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":[0.0004390603,0.00007524359,0.0000798327,0.00002545784,0.00003909661,0.00002322823,0.00006767917,0.00004160387,0.00005990568],"category_scores_gemma":[0.00007943479,0.00004676788,0.00002647718,0.00008548258,0.00001724653,0.00006421695,0.00001275174,0.00009572144,0.000003445399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004861758,"about_ca_system_score_gemma":0.00001233785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002190416,"about_ca_topic_score_gemma":0.000003999767,"domain_scores_codex":[0.9995025,0.00002124388,0.0001625675,0.00008319151,0.00009978285,0.0001306794],"domain_scores_gemma":[0.9995738,0.000105178,0.00002700112,0.0002298586,0.00002905571,0.00003505855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002574866,0.0005134736,0.2096104,0.0002621174,0.001308796,0.0000037092,0.003084375,0.2990167,0.4119651,0.03394156,0.01052397,0.02951237],"study_design_scores_gemma":[0.002246192,0.001241935,0.2920644,0.0001188735,0.00004961947,0.00001783193,0.00009972889,0.6590429,0.04048771,0.00187317,0.001887582,0.0008700783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603164,0.00001839104,0.00645159,0.00002160996,0.0003010489,0.0002227861,0.000001379957,0.00006618565,0.03260062],"genre_scores_gemma":[0.9995998,0.000008041735,0.0003101335,0.000003429438,0.0000113693,0.000002724228,7.958018e-7,0.000009472449,0.00005421022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3714774,"threshold_uncertainty_score":0.1907139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006302993472803593,"score_gpt":0.2457508884602599,"score_spread":0.2394478949874563,"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."}}