{"id":"W4417259818","doi":"10.1016/j.segan.2025.102102","title":"A novel time-varying control method of renewable energy sources for smart grid efficiency enhancement","year":2025,"lang":"en","type":"article","venue":"Sustainable Energy Grids and Networks","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"Science and Technology Project of State Grid; State Grid Hubei Electric Power Co","keywords":"Smart grid; Renewable energy; Voltage droop; Linearization; Photovoltaic system; Convergence (economics); Demand response; Optimization problem; Optimal control; Electric power system","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":[0.0001800021,0.0003816603,0.0003641074,0.0001986326,0.0002789526,0.0004798686,0.0005857414,0.0003610873,0.002353713],"category_scores_gemma":[0.0003571642,0.0001149447,0.0002930508,0.0002894544,0.0001992988,0.0003809867,0.0002405323,0.0003629234,0.0002324289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002062146,"about_ca_system_score_gemma":0.0002189526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001230108,"about_ca_topic_score_gemma":0.002183076,"domain_scores_codex":[0.9998683,0.0000252058,0.00000871651,0.00003959527,0.00004731608,0.00001091556],"domain_scores_gemma":[0.9999034,0.00002770288,0.00001578496,0.00001028182,0.00003672851,0.00000613871],"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":[0.0004936226,0.00029561,0.0004310903,0.0004542811,0.0001048871,0.0002209004,0.0001760814,0.235714,0.1622333,0.03000759,0.004446294,0.5654222],"study_design_scores_gemma":[0.00002226788,0.0001335789,0.0002033157,0.000006905351,0.00001788415,0.0000554407,0.000007524164,0.9908763,0.005298859,0.000864661,0.002502619,0.00001065431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02146305,0.0005653224,0.9693108,0.000123707,0.0002851292,0.00004791201,0.0000219694,0.000288409,0.007893693],"genre_scores_gemma":[0.8786585,0.0004084607,0.1134527,0.0001432912,0.0001465402,0.00007731198,0.00004347352,0.00004678684,0.007023002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002353713,"threshold_uncertainty_score":0.007874012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002376540494764484,"score_gpt":0.1915862183366508,"score_spread":0.1892096778418864,"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."}}