{"id":"W4308073549","doi":"10.1080/15325008.2022.2138638","title":"ANFIS Based Energy Management System for V2G Integrated Micro-Grids","year":2022,"lang":"en","type":"article","venue":"Electric Power Components and Systems","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adaptive neuro fuzzy inference system; Energy management system; Photovoltaic system; Grid; State of charge; Energy management; Controller (irrigation); Computer science; Automotive engineering; Engineering; Fuzzy logic; Simulation; Power (physics); Battery (electricity); Fuzzy control system; Energy (signal processing); Electrical engineering; Artificial intelligence","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":[0.0002698957,0.0005282835,0.0003892865,0.0002463752,0.0003619527,0.0007277875,0.0004503697,0.0005705201,0.003353613],"category_scores_gemma":[0.0003780179,0.0001449485,0.0002322088,0.0001863547,0.0001889433,0.0004421437,0.0002396032,0.0004375992,0.0003853431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005502077,"about_ca_system_score_gemma":0.0004031966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006162085,"about_ca_topic_score_gemma":0.006914495,"domain_scores_codex":[0.9998573,0.00003485392,0.00001322679,0.00002233179,0.00006073058,0.00001146129],"domain_scores_gemma":[0.9998932,0.00003664549,0.00001695287,0.000006016656,0.00004258259,0.000004647321],"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":[0.0001777676,0.0000836835,0.0008254038,0.0001978639,0.00005367239,0.0002594307,0.00009469778,0.8939434,0.01019449,0.004898961,0.002078993,0.0871916],"study_design_scores_gemma":[0.00001693736,0.0000750796,0.0003293264,0.00001568979,0.00001177269,0.00003102559,0.00001950367,0.9944972,0.002188863,0.0007600455,0.00204899,0.00000553735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09814814,0.001254092,0.8616548,0.0006353316,0.0002729731,0.000435974,0.0004436677,0.00354287,0.03361224],"genre_scores_gemma":[0.9490309,0.0002918479,0.0435873,0.00007023882,0.00002402012,0.0002175595,0.0001703146,0.00002720585,0.006580741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006162085,"threshold_uncertainty_score":0.01225239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0055218870399779,"score_gpt":0.1709227455320011,"score_spread":0.1654008584920232,"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."}}