{"id":"W3189223837","doi":"10.1109/tsg.2021.3103783","title":"An Energy Management System With Short-Term Fluctuation Reserves and Battery Degradation for Isolated Microgrids","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microgrid; Renewable energy; Context (archaeology); Reliability engineering; Battery (electricity); Term (time); Benchmark (surveying); Computer science; Electric power system; Engineering; Automotive engineering; Power (physics); Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006845083,0.0001651072,0.0001499651,0.00013168,0.0001537445,0.0001027934,0.00005733549,0.00007286407,0.00001291543],"category_scores_gemma":[3.207975e-7,0.0001617969,0.00004409504,0.0001826612,0.00001525211,0.0002722664,6.270112e-7,0.00006931529,0.000001834487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006929177,"about_ca_system_score_gemma":0.00001069165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001304126,"about_ca_topic_score_gemma":0.0002196243,"domain_scores_codex":[0.9992171,0.00003282799,0.0002100789,0.0002560303,0.0001055983,0.0001783582],"domain_scores_gemma":[0.9995666,0.00002565453,0.00001988864,0.0002246019,0.0000972282,0.00006610043],"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":[0.0002872812,0.0001579442,0.0001653176,0.0005043122,0.0004402788,0.00002330931,0.000169811,0.7977763,0.06193332,0.00008094187,0.0003086973,0.1381525],"study_design_scores_gemma":[0.001331107,0.000253157,0.00139478,0.0001719691,0.0002509865,0.00006593828,0.0002123341,0.8985552,0.09560751,0.000004110833,0.001754356,0.0003986117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07121152,0.0002093603,0.9273452,0.000043305,0.0005927811,0.0002213348,0.00006003322,0.0002649808,0.00005146549],"genre_scores_gemma":[0.9908003,0.0004271131,0.008062064,0.00002606127,0.00009878154,0.0001970428,0.0002227005,0.00004642694,0.0001194844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9195888,"threshold_uncertainty_score":0.6597888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007653989139004964,"score_gpt":0.1949237111964682,"score_spread":0.1872697220574633,"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."}}