{"id":"W2201691106","doi":"10.1080/15325008.2014.990069","title":"Enhancing Storage Capabilities for Active Distribution Systems Using Flywheel Technology","year":2015,"lang":"en","type":"article","venue":"Electric Power Components and Systems","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of Waterloo","funders":"","keywords":"Flywheel; Energy storage; Photovoltaic system; Flywheel energy storage; Distributed generation; Engineering; Electricity generation; Distributed data store; Automotive engineering; Electrical engineering; Computer science; Power (physics); Renewable energy; Distributed computing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008197692,0.0003875258,0.0002603045,0.0003298542,0.0003244804,0.0005444597,0.0004478419,0.0002408958,0.003751553],"category_scores_gemma":[0.0001791381,0.0001341662,0.0002445513,0.0002888804,0.000174213,0.001265616,0.0003106232,0.0002289784,0.0003895299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002405458,"about_ca_system_score_gemma":0.0002501961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001195594,"about_ca_topic_score_gemma":0.002716746,"domain_scores_codex":[0.9999609,0.000004687756,0.000003753618,0.000007237394,0.00001641652,0.000006968994],"domain_scores_gemma":[0.9999305,0.00002398853,0.00001056028,0.00001179183,0.00001965925,0.000003439508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004292937,0.0002252317,0.001683011,0.0009839721,0.000111439,0.000475964,0.0002253824,0.1105964,0.6371086,0.01895104,0.0013571,0.2278526],"study_design_scores_gemma":[0.0002036328,0.001458136,0.002936729,0.0001472098,0.0002012577,0.001109157,0.0002149229,0.4873269,0.4387019,0.01399663,0.05362424,0.00007937881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.479175,0.003558627,0.4898977,0.0004326299,0.0001810313,0.0001292004,0.0003153823,0.001937553,0.02437288],"genre_scores_gemma":[0.9837324,0.0006327892,0.012209,0.00001850214,0.00001130561,0.00001867708,0.0000688269,0.00002017076,0.003288385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003751553,"threshold_uncertainty_score":0.01255018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410382413183809,"score_gpt":0.2081547090945085,"score_spread":0.1940508849626704,"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."}}