{"id":"W2913620256","doi":"10.1109/tii.2019.2897741","title":"Distributed Cooperative Economic Optimization Strategy of a Regional Energy Network Based on Energy Cell–Tissue Architecture","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Distributed computing; Computer science; Robustness (evolution); Scalability; Scheduling (production processes); Distributed generation; Telecommunications network; Power control; Renewable energy; Power (physics); Mathematical optimization; Engineering; Computer network","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":[0.0003940678,0.0006310122,0.0006562459,0.0003485511,0.0006952331,0.001081103,0.001449931,0.0006299167,0.002744527],"category_scores_gemma":[0.000427256,0.0002441132,0.0005197483,0.0005275345,0.000532563,0.0009216808,0.001302931,0.0004784103,0.0002909789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009878643,"about_ca_system_score_gemma":0.0008583639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005913277,"about_ca_topic_score_gemma":0.00526436,"domain_scores_codex":[0.999782,0.00004631799,0.00000852398,0.0000667972,0.0000458387,0.00005039521],"domain_scores_gemma":[0.9998657,0.00002642405,0.00002444905,0.00001074237,0.00004604627,0.00002677641],"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":[0.00007007625,0.00003192079,0.0006718033,0.00004814952,0.00003559239,0.0003204657,0.0001134895,0.944439,0.006021119,0.02842895,0.001259659,0.01855979],"study_design_scores_gemma":[0.000007344669,0.00002448942,0.00007896904,0.00000188079,0.000009710833,0.00002197622,0.00001945818,0.9958301,0.0003964514,0.003040166,0.0005642939,0.000005098612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09433268,0.000424151,0.8856398,0.0004041892,0.00006951008,0.00008941432,0.00005747687,0.0002398142,0.01874302],"genre_scores_gemma":[0.9607061,0.0002164935,0.03134938,0.00005608421,0.00002140473,0.0001287839,0.00004353682,0.00001746276,0.00746077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005913277,"threshold_uncertainty_score":0.01175773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01002894481275841,"score_gpt":0.1848485204917387,"score_spread":0.1748195756789803,"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."}}