{"id":"W4312532452","doi":"10.1109/tsg.2022.3228636","title":"Physics-Shielded Multi-Agent Deep Reinforcement Learning for Safe Active Voltage Control With Photovoltaic/Battery Energy Storage Systems","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; McGill University; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Reinforcement learning; Scalability; AC power; Computer science; Photovoltaic system; Energy storage; Electric power system; Battery (electricity); Engineering; Control engineering; Voltage; Power (physics); Artificial intelligence; Electrical engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001471267,0.0003366547,0.0003411622,0.0001324516,0.0005831589,0.00005895654,0.000162395,0.00007367354,0.0001350522],"category_scores_gemma":[0.000002760074,0.0003613786,0.000179429,0.0002557222,0.0000346983,0.0002311057,0.000002631697,0.0005159264,0.00001959639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007817341,"about_ca_system_score_gemma":0.00003974267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001827221,"about_ca_topic_score_gemma":0.00004920837,"domain_scores_codex":[0.9983915,0.00007038502,0.0003360049,0.0003541142,0.0003766791,0.0004713197],"domain_scores_gemma":[0.9992751,0.0001262633,0.00009336336,0.0002945938,0.00008460263,0.0001260823],"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":[0.0004346673,0.0001465862,0.000008720547,0.00006389867,0.0003195052,0.000009884033,0.0002587543,0.9786242,0.01850722,0.00001640293,0.0004482326,0.001161939],"study_design_scores_gemma":[0.002899126,0.0007309779,0.00003429353,0.00002801746,0.0001401099,0.00001168253,0.0005492613,0.9481931,0.03242705,0.000001240512,0.01455665,0.000428466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01069852,0.00004655391,0.9849414,0.00001524978,0.0025598,0.0008518919,0.0003698008,0.0003820933,0.0001347339],"genre_scores_gemma":[0.9966643,0.00001409672,0.0001895826,0.0000788925,0.0001572755,0.002010157,0.0001953287,0.00009013331,0.0006001691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9859658,"threshold_uncertainty_score":0.9998838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057924438012842,"score_gpt":0.2011182880561035,"score_spread":0.190539043675975,"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."}}