{"id":"W3020549889","doi":"10.1109/tpwrs.2020.2987982","title":"Transmission Expansion Planning Including TCSCs and SFCLs: A MINLP Approach","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Linearization; Sizing; Mathematical optimization; Transmission line; Electric power transmission; Transmission (telecommunications); Nonlinear programming; Benders' decomposition; Thyristor; Computer science; Nonlinear system; Engineering; Voltage; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001288555,0.001443434,0.001381403,0.0007688701,0.0004391337,0.001507302,0.001203657,0.001202971,0.005102873],"category_scores_gemma":[0.00194538,0.0008354902,0.000780157,0.001388534,0.0005747355,0.001200728,0.0006903477,0.001350247,0.0004822357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001452184,"about_ca_system_score_gemma":0.001769302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007277459,"about_ca_topic_score_gemma":0.00702973,"domain_scores_codex":[0.9994237,0.0003299584,0.00001590246,0.00007335028,0.0000988645,0.00005825451],"domain_scores_gemma":[0.9992729,0.0004993684,0.00006906719,0.00001863757,0.00009976178,0.00004029879],"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":[0.00001474224,0.00002241787,0.00007431355,0.00005273601,0.00001622715,0.00005228512,0.0000158291,0.9808866,0.0001807169,0.01092897,0.0007863152,0.006968813],"study_design_scores_gemma":[0.000005493295,0.00002391046,0.00002723329,0.000008322892,0.000005754904,0.00001000543,0.000011841,0.991,0.000116983,0.008085814,0.0007006276,0.000003990569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01066356,0.0005872839,0.9763818,0.0006814972,0.00004489932,0.00009374363,0.0003371785,0.0001678074,0.0110422],"genre_scores_gemma":[0.5440083,0.002505315,0.4311907,0.0004459461,0.000276601,0.001030013,0.0007747434,0.0002508344,0.01951768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007277459,"threshold_uncertainty_score":0.01707083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03771004114794754,"score_gpt":0.2367823013889106,"score_spread":0.1990722602409631,"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."}}