{"id":"W2629831979","doi":"10.1109/ccece.2017.7946600","title":"Linearized power flow for stochastic optimization","year":2017,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematical optimization; Economic dispatch; Computer science; Electric power system; Computation; Linear programming; Piecewise linear function; Power (physics); Iterative method; Piecewise; Power flow; Stochastic programming; AC power; Control theory (sociology); Algorithm; Mathematics","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":[0.0005446092,0.0006954925,0.0004417453,0.0005041749,0.0002252898,0.0007141853,0.0003258053,0.0003828004,0.005544967],"category_scores_gemma":[0.002398944,0.0002539057,0.0004291933,0.0006339382,0.0004796302,0.0008279056,0.0006128334,0.001101997,0.000905302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006075499,"about_ca_system_score_gemma":0.000607049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002953415,"about_ca_topic_score_gemma":0.001690576,"domain_scores_codex":[0.9997323,0.0001508358,0.000007079065,0.00002242337,0.00007195659,0.0000153798],"domain_scores_gemma":[0.9993291,0.0004764413,0.00006079849,0.0000356731,0.00008419463,0.0000137928],"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":[0.0000141718,0.00001280667,0.0001411744,0.00008530532,0.00001526782,0.0000260203,0.00003504267,0.7719053,0.001011655,0.2046661,0.002530205,0.0195569],"study_design_scores_gemma":[0.000001925698,0.000006057787,0.00002974284,0.000006402333,0.00000184201,0.000007647054,0.000004073189,0.9647577,0.0001687125,0.03387214,0.001140906,0.000002756341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001997455,0.0003133893,0.9921665,0.0001903293,0.00003019462,0.00001551096,0.00006035392,0.0001553966,0.00507092],"genre_scores_gemma":[0.6063534,0.002564207,0.366453,0.0003730979,0.0003183907,0.0004382212,0.000571769,0.0005164923,0.02241146],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005544967,"threshold_uncertainty_score":0.01854974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009241897045171326,"score_gpt":0.224317492052904,"score_spread":0.2150755950077327,"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."}}