{"id":"W2587544603","doi":"10.1109/tpwrs.2017.2665695","title":"A Fast Solution Method for Stochastic Transmission Expansion Planning","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Electric Power System Optimization","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Linearization; Reduction (mathematics); Stochastic programming; Computer science; Nonlinear system; Model order reduction; Benders' decomposition; Mathematics; Algorithm","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":[0.0009652044,0.001045331,0.0008590958,0.0008005217,0.0006017493,0.0006361269,0.0007748323,0.0008406838,0.006528419],"category_scores_gemma":[0.001899839,0.0005194913,0.001112098,0.001098466,0.0004523279,0.0008057549,0.0008764667,0.001742932,0.001040673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006132103,"about_ca_system_score_gemma":0.002000394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006017989,"about_ca_topic_score_gemma":0.00559521,"domain_scores_codex":[0.9996287,0.0001210984,0.0000200226,0.00005666336,0.0001408565,0.0000326293],"domain_scores_gemma":[0.9994143,0.0003302582,0.00004194755,0.00002926027,0.0001619299,0.00002229016],"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":[0.00003317033,0.00002220436,0.000213002,0.0001469569,0.00003153529,0.00006764991,0.00004277872,0.8591235,0.002115329,0.03624612,0.003947414,0.09801032],"study_design_scores_gemma":[0.000008487914,0.000009455173,0.00003029247,0.000008155029,0.000003475784,0.00001525722,0.000004639807,0.9923394,0.0002613815,0.004963274,0.002351915,0.000004282694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008760336,0.0001274677,0.9974744,0.00007368196,0.0000477608,0.00002440388,0.00004236275,0.0001487403,0.001185119],"genre_scores_gemma":[0.09804053,0.0007484279,0.8943806,0.0001252828,0.0001183698,0.0004714261,0.0003956581,0.0002244117,0.005495251],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006528419,"threshold_uncertainty_score":0.02183968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999731207967152,"score_gpt":0.2772400854513618,"score_spread":0.2572427733716903,"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."}}