{"id":"W3086236066","doi":"10.1007/s12652-020-02511-z","title":"Optimal reconfiguration and DG integration in distribution networks considering switching actions costs using tabu search algorithm","year":2020,"lang":"en","type":"article","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematical optimization; Control reconfiguration; Tabu search; Computer science; Distributed generation; Solver; AC power; Integer programming; Computational intelligence; Particle swarm optimization; Voltage; Nonlinear programming; Sizing; Power (physics); Algorithm; Nonlinear system; Mathematics; Engineering","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":[0.0007629716,0.000944436,0.001594786,0.0009990452,0.000667931,0.001397974,0.0008824146,0.001229431,0.004539453],"category_scores_gemma":[0.00168063,0.0007007879,0.0008114541,0.001300646,0.0005122516,0.001005917,0.0004654606,0.0007556317,0.0002721922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083571,"about_ca_system_score_gemma":0.001304514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01239952,"about_ca_topic_score_gemma":0.01105651,"domain_scores_codex":[0.999732,0.0001170128,0.000008416429,0.00004279281,0.00004565187,0.00005411066],"domain_scores_gemma":[0.9994636,0.0003581312,0.00004527347,0.00002021429,0.0000863984,0.00002636667],"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":[0.00003908439,0.00003023961,0.0001534218,0.00003047088,0.00002180702,0.00002165018,0.00001196246,0.9875891,0.0002127195,0.001284176,0.0003994105,0.01020599],"study_design_scores_gemma":[0.000007785857,0.00001303674,0.0000690365,0.000004319812,0.000009357457,0.000004338722,0.000007467968,0.9990375,0.00006525619,0.0007063124,0.00007383515,0.000001775744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1409896,0.001498152,0.838193,0.0004430696,0.0001408622,0.0001493108,0.0001789511,0.0005056604,0.01790131],"genre_scores_gemma":[0.8945525,0.0003365538,0.1013032,0.00007820646,0.00004891558,0.0001260963,0.0001182213,0.0000863242,0.003349931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01239952,"threshold_uncertainty_score":0.02465469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05062004400830709,"score_gpt":0.2835493449109475,"score_spread":0.2329293009026404,"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."}}