{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006186414,0.001127926,0.0006104486,0.0004889721,0.0002582843,0.0005870834,0.0004261721,0.0004195317,0.002708241],"category_scores_gemma":[0.0008810418,0.0003468475,0.0006494382,0.0004414115,0.0003271021,0.0003787293,0.0007197672,0.0006152423,0.0002868585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004956682,"about_ca_system_score_gemma":0.0009148913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002186036,"about_ca_topic_score_gemma":0.002437507,"domain_scores_codex":[0.9997547,0.0001166634,0.000009025412,0.00003536315,0.00005710713,0.00002714422],"domain_scores_gemma":[0.9997627,0.0001225738,0.00003334966,0.000013909,0.00005255441,0.00001486536],"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":[0.000020284,0.00001503148,0.0001662197,0.00006560612,0.00002071278,0.00002885333,0.00002042311,0.9826205,0.001511344,0.004345482,0.0004550655,0.01073032],"study_design_scores_gemma":[0.00000847547,0.00004452945,0.00009515647,0.000007293781,0.000007822004,0.000008818678,0.00001613142,0.9952117,0.0004137159,0.00284398,0.001339257,0.000003312048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03332497,0.0004631009,0.9540511,0.00016161,0.00005063497,0.000112028,0.0001272823,0.0002320338,0.01147726],"genre_scores_gemma":[0.743515,0.0006827012,0.2461135,0.0001133378,0.00003134354,0.0005052016,0.0003004162,0.000138865,0.008599488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002708241,"threshold_uncertainty_score":0.009059906,"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."}}