{"id":"W3108888750","doi":"10.1109/tste.2020.3039758","title":"Stochastic Energy Management of Electric Bus Charging Stations With Renewable Energy Integration and B2G Capabilities","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic programming; Mathematical optimization; Computer science; Photovoltaic system; Markov decision process; Regret; Dynamic programming; Renewable energy; Heuristic; Energy management; Wind power; Energy storage; Markov process; Robust optimization; Grid; Automotive engineering; Engineering; Energy (signal processing); Power (physics); Electrical engineering; Mathematics","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":[0.001147966,0.0008124606,0.0008512712,0.0003850014,0.0004640825,0.001345478,0.00111833,0.0008542845,0.001682041],"category_scores_gemma":[0.002855532,0.0005996816,0.0006478853,0.0008658841,0.0005604225,0.001360661,0.001028044,0.0009260472,0.0001526843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001155801,"about_ca_system_score_gemma":0.001130246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006033508,"about_ca_topic_score_gemma":0.006138552,"domain_scores_codex":[0.9991705,0.0002796025,0.00003488709,0.0001619671,0.0001838515,0.0001691603],"domain_scores_gemma":[0.9990908,0.0004500088,0.0002161236,0.00005132485,0.0001216688,0.0000699851],"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":[0.00002665558,0.00001269333,0.0003301051,0.00001697746,0.00001382114,0.00005150993,0.000009103696,0.9871464,0.0004597756,0.006835102,0.0001901974,0.004907712],"study_design_scores_gemma":[0.000003597926,0.00001428002,0.0001386559,0.00000168131,0.000004469759,0.00001235461,0.000006373046,0.9971178,0.0001482967,0.00240867,0.0001402936,0.000003560919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0777202,0.0002881736,0.9155962,0.0003978048,0.00005548088,0.00006115767,0.0001240284,0.0001457603,0.005611239],"genre_scores_gemma":[0.9870947,0.0001426043,0.01144017,0.00003948323,0.00002029012,0.00002465433,0.00005474698,0.00001751334,0.001165927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006033508,"threshold_uncertainty_score":0.01199681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003841288515131854,"score_gpt":0.1699156145650683,"score_spread":0.1660743260499364,"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."}}