{"id":"W3199935164","doi":"10.1109/icjece.2021.3093520","title":"EV Fleet as Virtual Battery Resource for Community Microgrid Energy Storage Planning","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microgrid; Queueing theory; Battery (electricity); Energy storage; Sizing; Computer science; Grid; Queue; Electric vehicle; Photovoltaic system; Markov chain; Automotive engineering; Vehicle-to-grid; Operations research; Renewable energy; Electrical engineering; Engineering; Computer network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.000115013,0.0001626865,0.0002566666,0.0002140872,0.0001290758,0.000102043,0.0001711612,0.0001031078,0.000009434536],"category_scores_gemma":[0.0000321058,0.0001675079,0.00008797125,0.000260742,0.00001276773,0.00009426699,0.00001154533,0.0005871672,3.159811e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001162504,"about_ca_system_score_gemma":0.0001595143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009184546,"about_ca_topic_score_gemma":0.00006137002,"domain_scores_codex":[0.9991465,0.00002946342,0.0002638157,0.00008717793,0.00007944112,0.0003935633],"domain_scores_gemma":[0.9991505,0.000194919,0.00003585146,0.0001041445,0.0000668681,0.0004477187],"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":[0.00002212435,0.00002033693,0.0006568108,0.0001186941,0.0003870641,0.0008579022,0.0007361772,0.7919691,0.01097857,0.003162011,0.02854604,0.1625452],"study_design_scores_gemma":[0.001032556,0.0008785476,0.003346862,0.0002233686,0.00006331115,0.003653681,0.0000516897,0.7104013,0.011946,0.0004491834,0.2673291,0.0006244341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6444374,0.008856786,0.3459182,0.0001348194,0.0004594524,0.00004071842,0.00001012395,0.00004544966,0.00009707178],"genre_scores_gemma":[0.9964666,0.00004142688,0.002463627,0.0003305119,0.0006257443,0.000001609391,0.000008929379,0.00003489184,0.00002661016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3520293,"threshold_uncertainty_score":0.6830773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005209654433394603,"score_gpt":0.1697974659858333,"score_spread":0.1645878115524387,"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."}}