{"id":"W2558465750","doi":"10.1109/tsg.2016.2633873","title":"Optimization of Aggregate Capacity of PEVs for Frequency Regulation Service in Day-Ahead Market","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"News aggregator; Operations research; Automatic Generation Control; Stochastic programming; Computer science; Economics; Business; Mathematical optimization; Engineering; Electric power system; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001918093,0.001484814,0.001791062,0.0006818758,0.0006672989,0.002941158,0.001736995,0.002205672,0.005998322],"category_scores_gemma":[0.003961775,0.001250894,0.0009249221,0.001014728,0.0009548463,0.002246059,0.001484627,0.001917256,0.0005251286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002245161,"about_ca_system_score_gemma":0.002131855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008975485,"about_ca_topic_score_gemma":0.005465745,"domain_scores_codex":[0.9990258,0.0003284278,0.00003469734,0.0001938837,0.0001350183,0.0002821327],"domain_scores_gemma":[0.9980358,0.001067379,0.0002470393,0.00006910066,0.0003000898,0.0002806344],"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":[0.0000591419,0.00002829442,0.0002471959,0.00003866326,0.00001848819,0.00008929871,0.00001808489,0.991606,0.0005595981,0.004677667,0.0006055755,0.002051966],"study_design_scores_gemma":[0.00001159554,0.00003506762,0.0001853595,0.000006809016,0.000009107231,0.00001630743,0.0000292442,0.9963767,0.0001649439,0.002882813,0.0002739517,0.000008208231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2847834,0.001819042,0.6726341,0.00186616,0.0002363023,0.0003748023,0.001003017,0.0004226815,0.03686037],"genre_scores_gemma":[0.9769797,0.0002963798,0.01701896,0.0001020245,0.00002687696,0.0001028803,0.0001617835,0.00007061248,0.005240868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008975485,"threshold_uncertainty_score":0.02006638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009957055437251528,"score_gpt":0.1973105909104431,"score_spread":0.1873535354731916,"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."}}