{"id":"W4289656864","doi":"10.1109/tsg.2022.3195989","title":"Microgrids Multiobjective Design Optimization for Critical Loads","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Microgrid; Reliability engineering; Renewable energy; Computer science; Sizing; Reliability (semiconductor); Electricity generation; Power (physics); Control engineering; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001740525,0.0001835388,0.0001720193,0.0001849275,0.0004944396,0.00004536727,0.0001201349,0.0000655569,0.000528386],"category_scores_gemma":[0.000008636436,0.0002151596,0.0001390107,0.0002124845,0.00003378975,0.0001534141,0.000001160261,0.0002532896,0.00001617843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000196736,"about_ca_system_score_gemma":0.00003243464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008941387,"about_ca_topic_score_gemma":0.000004833168,"domain_scores_codex":[0.9989945,0.00007295248,0.0002385411,0.0002455116,0.0001588266,0.00028969],"domain_scores_gemma":[0.9994033,0.0002337602,0.00002012412,0.0001750208,0.0000924632,0.0000753272],"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":[0.0001403461,0.0001287714,9.683431e-7,0.000019583,0.00005288537,0.000001581901,0.0001681985,0.9850256,0.002062701,0.000009600384,0.001640338,0.01074943],"study_design_scores_gemma":[0.0009276971,0.0002463341,0.000004337151,0.000006032749,0.00007193768,0.00001510732,0.00008204236,0.9757863,0.01788302,0.00002877464,0.004705819,0.0002426094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002302841,0.0002000772,0.9947087,0.0001425246,0.003287234,0.0006216983,0.0003010522,0.0004229412,0.00008550088],"genre_scores_gemma":[0.8107126,0.000228543,0.1851018,0.000397941,0.0004034902,0.002670268,0.00009789605,0.000162577,0.0002248561],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8104824,"threshold_uncertainty_score":0.8773953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01353758422555447,"score_gpt":0.2237543575548912,"score_spread":0.2102167733293367,"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."}}