{"id":"W4310388963","doi":"10.3390/en15239032","title":"Deep Reinforcement Learning-Based Operation of Transmission Battery Storage with Dynamic Thermal Line Rating","year":2022,"lang":"en","type":"article","venue":"Energies","topic":"Thermal Analysis in Power Transmission","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Electric System Operator","keywords":"Reinforcement learning; Ampacity; Battery (electricity); Computer science; Transmission line; Electric power system; Grid; Line (geometry); Power (physics); Artificial intelligence; Engineering; Electrical engineering; Telecommunications; Electrical conductor","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000149989,0.0001417292,0.0001660493,0.0001086194,0.0001747514,0.00001485515,0.0001320299,0.00002726635,0.0008639637],"category_scores_gemma":[0.000002646204,0.0001181455,0.00005998231,0.0001641394,0.00002241283,0.00009863449,0.00001807447,0.000217037,0.000001519149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007252581,"about_ca_system_score_gemma":0.00002048035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001387361,"about_ca_topic_score_gemma":0.000004971049,"domain_scores_codex":[0.9990988,0.00007585368,0.0002436683,0.0001321956,0.0002998608,0.0001495957],"domain_scores_gemma":[0.9997158,0.00003534944,0.00004888092,0.0001454533,0.00002041202,0.00003408706],"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":[0.00004883493,0.00001502758,0.00003571086,0.00004567425,0.00003219152,0.000004395774,0.0006905477,0.7839214,0.2121587,0.000008224592,0.000005179632,0.003034036],"study_design_scores_gemma":[0.0003988785,0.0001863393,0.0001909212,0.00003263747,0.00003131897,0.000001344132,0.0002789503,0.9163603,0.08163685,0.000001411242,0.000739008,0.0001420176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5381135,0.0003483093,0.4609155,0.00005602315,0.00005821165,0.00006841475,8.242653e-7,0.0001502185,0.0002890198],"genre_scores_gemma":[0.9982551,0.00001767038,0.001287308,0.00002574206,0.00001499013,0.00003297859,0.00007800918,0.00003678361,0.0002514457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4601416,"threshold_uncertainty_score":0.9459797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003842670778274631,"score_gpt":0.1891328062953236,"score_spread":0.1852901355170489,"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."}}