{"id":"W2902597158","doi":"10.1016/j.ijepes.2018.11.033","title":"Source-load-storage consistency collaborative optimization control of flexible DC distribution network considering multi-energy complementarity","year":2018,"lang":"en","type":"article","venue":"International Journal of Electrical Power & Energy Systems","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Complementarity (molecular biology); Consistency (knowledge bases); Energy storage; Computer science; Mathematical optimization; Mathematics","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":[0.001204147,0.001023502,0.001256639,0.0003274784,0.0007482572,0.001686719,0.001113778,0.0008736008,0.001880405],"category_scores_gemma":[0.00176039,0.0005253965,0.0004861236,0.0007126243,0.0008014571,0.001003205,0.001442212,0.0009308995,0.0001509555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009675476,"about_ca_system_score_gemma":0.001150715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009505612,"about_ca_topic_score_gemma":0.007641544,"domain_scores_codex":[0.9995752,0.0001126897,0.00001918428,0.0001130026,0.00009906732,0.0000808456],"domain_scores_gemma":[0.9992515,0.0003309374,0.0001370475,0.00005069042,0.0001793057,0.00005048568],"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":[0.00009609517,0.0000246145,0.0001612198,0.00003921479,0.00002972016,0.00004789887,0.00003352933,0.9895694,0.0007878183,0.004222713,0.0003768986,0.004610859],"study_design_scores_gemma":[0.000007619115,0.00001511193,0.00005557578,0.00000147632,0.000004050207,0.000003624013,0.000004511714,0.998979,0.0001188305,0.0007427976,0.00006497225,0.000002440786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1126462,0.000449127,0.8677356,0.0006019941,0.0001565571,0.0001209329,0.0001337425,0.0001981721,0.01795768],"genre_scores_gemma":[0.9924859,0.0000547018,0.005924928,0.00002575693,0.0000154348,0.0000384335,0.00002258032,0.00001450748,0.001417778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009505612,"threshold_uncertainty_score":0.01890051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006932077646996359,"score_gpt":0.217679057836184,"score_spread":0.2107469801891877,"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."}}