{"id":"W2016995256","doi":"10.1109/acc.2014.6859231","title":"Optimal control of microgrids - algorithms and field implementation","year":2014,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scalability; Computer science; Microgrid; Mathematical optimization; Field (mathematics); Dynamic programming; Economic dispatch; Knapsack problem; Linear programming; Optimal control; Algorithm; Control (management); Electric power system; Mathematics; Power (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000645154,0.0000535386,0.00008617782,0.00002890557,0.00001303362,0.00001152997,0.00002770333,0.00002786368,0.0001330237],"category_scores_gemma":[0.000003944617,0.00004907652,0.00001727914,0.00003009492,0.000007444544,0.00005374199,0.0000052599,0.0000263054,0.000002151561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003739242,"about_ca_system_score_gemma":0.000001882828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002469195,"about_ca_topic_score_gemma":0.00000807116,"domain_scores_codex":[0.9996977,0.000007540092,0.0001213427,0.00005592971,0.00003565925,0.00008185563],"domain_scores_gemma":[0.9998574,0.00003290103,0.00001423121,0.00005297194,0.00001948645,0.00002303099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002194059,0.00001696745,0.003001521,0.00006692562,0.00009144197,3.749738e-7,0.0002274948,0.06907715,0.06490405,0.001017358,0.002235093,0.8593397],"study_design_scores_gemma":[0.001505549,0.0001063952,0.001170576,0.00000410034,0.00002452465,0.000002677073,0.00006663191,0.9419655,0.05028735,0.00003278512,0.004727978,0.0001058869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08116858,0.000482172,0.916914,0.0001130221,0.00009717439,0.0001204851,0.000006379135,0.00008738926,0.001010833],"genre_scores_gemma":[0.9865662,0.00009938803,0.0131553,0.00009440236,0.000049549,0.000005670602,0.000007212921,0.000006984861,0.00001532676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9053976,"threshold_uncertainty_score":0.2001282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002807145830758003,"score_gpt":0.2044848580788284,"score_spread":0.2016777122480704,"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."}}