{"id":"W2561870604","doi":"10.3390/en9121070","title":"A Decentralized Control Method for Distributed Generations in an Islanded DC Microgrid Considering Voltage Drop Compensation and Durable State of Charge","year":2016,"lang":"en","type":"article","venue":"Energies","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microgrid; Voltage droop; Voltage drop; Voltage; State of charge; Engineering; Distributed generation; Control theory (sociology); Voltage compensation; Grid; Electrical impedance; Electronic engineering; Compensation (psychology); Node (physics); Computer science; Voltage source; Power (physics); Electrical engineering; Control (management); Battery (electricity); Renewable energy","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":[0.0001479409,0.0001117236,0.0002258604,0.00007736961,0.00004154075,0.00003249058,0.00004305844,0.00003800046,0.00001806344],"category_scores_gemma":[0.00003808553,0.00009029893,0.00002931005,0.00007101606,0.00002330291,0.0001948132,0.000007000961,0.00002740229,5.160722e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002909665,"about_ca_system_score_gemma":0.00001367615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003509816,"about_ca_topic_score_gemma":0.0003385324,"domain_scores_codex":[0.9993324,0.00003914957,0.0002640004,0.0001298194,0.00004768953,0.0001868868],"domain_scores_gemma":[0.9996113,0.0001386035,0.00005107657,0.00009948922,0.00006166193,0.00003792267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005452421,0.00001436518,0.000927774,0.00002766398,0.00003285604,6.793431e-7,0.0001936639,0.1746798,0.8144419,0.0003441059,0.00007849398,0.009204231],"study_design_scores_gemma":[0.004935054,0.00004007691,0.001843451,0.00003858266,0.00002829288,0.000002663075,0.00003219249,0.696808,0.2939689,0.0003584539,0.001761963,0.0001823723],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4737345,0.0008087303,0.5247148,0.00007672219,0.00006946131,0.000233738,0.0002850141,0.00007242434,0.000004657851],"genre_scores_gemma":[0.9857987,0.0007200986,0.01322098,0.00001945406,0.00002459006,0.00007007689,0.0001079785,0.00001909639,0.00001902479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5221282,"threshold_uncertainty_score":0.3682283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00839248090907615,"score_gpt":0.2260699654926899,"score_spread":0.2176774845836137,"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."}}