{"id":"W4384518995","doi":"10.1109/access.2023.3296152","title":"Transmission Network Planning in Super Smart Grids: A Survey","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Load balancing (electrical power); Smart grid; Transmission (telecommunications); Electric power transmission; Reliability (semiconductor); Renewable energy; Grid; Reliability engineering; Distributed computing; Power (physics); Telecommunications; Engineering; Electrical engineering; 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":[0.001298186,0.0009286095,0.0007739275,0.002656678,0.0004129398,0.002102336,0.001297161,0.001107612,0.007581652],"category_scores_gemma":[0.00255543,0.0007017747,0.000688506,0.009403426,0.0004588005,0.003122934,0.0008251282,0.0009563863,0.001515054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001124101,"about_ca_system_score_gemma":0.001613993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007482291,"about_ca_topic_score_gemma":0.007883846,"domain_scores_codex":[0.9993846,0.0001910137,0.00005606177,0.0001133314,0.0002099525,0.00004498976],"domain_scores_gemma":[0.99866,0.0008214316,0.0001060188,0.0000781587,0.0002721305,0.00006220685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005634009,0.000143193,0.00266373,0.003995004,0.00006863428,0.0002217529,0.0001919803,0.07817603,0.0002917295,0.04570307,0.03114072,0.8373478],"study_design_scores_gemma":[0.00003957581,0.0002486508,0.004977506,0.003748032,0.0001086766,0.00105175,0.0008786049,0.1183313,0.0008347458,0.07680891,0.7928918,0.0000805722],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01040433,0.7861278,0.1247382,0.004294712,0.0006981613,0.0001838089,0.0009930987,0.0003461272,0.07221373],"genre_scores_gemma":[0.05695168,0.8911884,0.04031926,0.0004186141,0.0009966639,0.0001241188,0.001307575,0.0000821648,0.008611431],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007581652,"threshold_uncertainty_score":0.02536315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0317994545129276,"score_gpt":0.2719921885452735,"score_spread":0.2401927340323459,"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."}}