{"id":"W2793796704","doi":"10.1109/tpwrs.2018.2819942","title":"Effective Dynamic Scheduling of Reconfigurable Microgrids","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Microgrid; Islanding; Dispatchable generation; Control reconfiguration; Scheduling (production processes); Schedule; Computer science; Grid; Distributed generation; Reliability engineering; Reliability (semiconductor); Mathematical optimization; Engineering; Control engineering; Distributed computing; Power (physics); Renewable energy; Embedded system; Control (management)","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":[0.0003842554,0.0007626317,0.000737026,0.0003257313,0.0003993747,0.0008675622,0.001010677,0.0005644479,0.002751973],"category_scores_gemma":[0.0009869491,0.0004629768,0.0006024118,0.0003688684,0.0006002883,0.0009644773,0.0006889806,0.0008874126,0.0003005923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009863512,"about_ca_system_score_gemma":0.001010363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006493768,"about_ca_topic_score_gemma":0.005215619,"domain_scores_codex":[0.9996816,0.00009184315,0.00001038051,0.00006276667,0.0000850361,0.00006840758],"domain_scores_gemma":[0.9997784,0.00008841314,0.00004370241,0.00003480494,0.00003021807,0.00002436803],"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":[0.000008213276,0.00000515946,0.00004314577,0.000007806058,0.000002997016,0.00001684435,0.00000699537,0.9912383,0.0002590085,0.006226934,0.0001511912,0.002033391],"study_design_scores_gemma":[0.000002914204,0.00000523679,0.00001730178,0.000001092559,0.000001204355,0.000003719355,0.000003307114,0.9975165,0.00008384531,0.002067333,0.0002962059,0.000001301768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03274122,0.0002087102,0.952857,0.0002067857,0.00006332617,0.00006060956,0.0001379046,0.0003223365,0.0134022],"genre_scores_gemma":[0.9296828,0.000361422,0.0627109,0.00006143069,0.00004624203,0.0001552611,0.0001623402,0.0001215892,0.006698073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006493768,"threshold_uncertainty_score":0.01291198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003657887603884045,"score_gpt":0.1960747199626182,"score_spread":0.1924168323587341,"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."}}