{"id":"W2787302219","doi":"10.1109/pesgm.2017.8274674","title":"Assessing energy storage potential to facilitate the increased penetration of photovoltaic generators and electric vehicles in distribution networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Photovoltaic system; Transformer; Energy storage; Monte Carlo method; Computer science; Reliability engineering; Automotive engineering; Electrical engineering; Voltage; Engineering; Power (physics)","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":[0.0001503109,0.00007679025,0.00009319263,0.00004049536,0.0001265664,0.0001618888,0.00007814509,0.00004751966,0.00000491601],"category_scores_gemma":[0.00002112884,0.00006096288,0.00001795366,0.00008497151,0.00001158096,0.0002311405,0.00001715979,0.00005327925,2.470274e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003284739,"about_ca_system_score_gemma":0.00001006962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009833685,"about_ca_topic_score_gemma":0.0004465019,"domain_scores_codex":[0.9995407,0.00003138542,0.0001475492,0.00009313211,0.0000633011,0.000123952],"domain_scores_gemma":[0.9997475,0.00001767315,0.00003780109,0.0001380907,0.00002767981,0.00003126447],"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":[0.00001249231,0.000007431356,0.00134465,0.00000644167,0.000009633815,0.000001120418,0.00002949095,0.7029455,0.2712423,0.00006537895,0.0001068556,0.02422877],"study_design_scores_gemma":[0.0002295504,0.00001262797,0.07197742,0.000006674159,0.000007829135,8.614937e-7,0.00001437904,0.9151893,0.01240016,0.00002228303,0.00007104286,0.00006784462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7131692,0.0004002498,0.2862168,0.00001486869,0.00004677822,0.00006762262,0.00000310322,0.00002139251,0.00005991838],"genre_scores_gemma":[0.9994858,0.000181394,0.0002194077,0.00001618773,0.0000439137,0.00001076374,0.00002906988,0.000006671538,0.000006823213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2863165,"threshold_uncertainty_score":0.2485994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009522028099019638,"score_gpt":0.1970594807256048,"score_spread":0.1875374526265851,"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."}}