{"id":"W3036163467","doi":"10.1049/iet-rpg.2019.1127","title":"Robust optimisation framework for SCED problem in mixed AC‐HVDC power systems with wind uncertainty","year":2020,"lang":"en","type":"article","venue":"IET Renewable Power Generation","topic":"Electric Power System Optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Electric power system; Wind power; Computer science; Mathematical optimization; Power system simulation; Power (physics); Operations research; Control theory (sociology); Reliability engineering; Electrical engineering; Engineering; Mathematics; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001335085,0.001444858,0.001284383,0.0006246796,0.000315045,0.001531174,0.001022106,0.001314971,0.003013174],"category_scores_gemma":[0.001869099,0.0005720791,0.00113733,0.00070722,0.0008506115,0.0007709372,0.001359852,0.001504475,0.000295855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009299376,"about_ca_system_score_gemma":0.001524706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008268938,"about_ca_topic_score_gemma":0.004437692,"domain_scores_codex":[0.9994071,0.0002571321,0.00002265769,0.00009847075,0.0001353751,0.00007940415],"domain_scores_gemma":[0.999369,0.0003874608,0.0000898431,0.00002286224,0.00009964395,0.00003131002],"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":[0.00001008735,0.000006558335,0.00006254962,0.00003612941,0.00001679156,0.00003138187,0.000009277605,0.9912048,0.0001812979,0.006260545,0.0002141161,0.001966513],"study_design_scores_gemma":[0.000004211315,0.00001005842,0.00003130892,0.000004509923,0.000003025591,0.000004059289,0.000004169514,0.9979094,0.00003958748,0.001759467,0.000228031,0.000002126754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008895901,0.0007113725,0.980325,0.0003252199,0.00005545204,0.00005784645,0.000112619,0.00009242717,0.009424065],"genre_scores_gemma":[0.8808595,0.001286715,0.1074656,0.0002067509,0.0001367798,0.0004242132,0.0003335351,0.0001323881,0.009154518],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008268938,"threshold_uncertainty_score":0.01644164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02597383567058324,"score_gpt":0.2093777984993233,"score_spread":0.1834039628287401,"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."}}