{"id":"W7133496684","doi":"10.1109/etfg61999.2025.11402516","title":"A Holistic Iterative Optimization Approach for Optimal Renewable Energy Resources-Based DG Placement and Sizing in Distribution Networks","year":2025,"lang":"","type":"article","venue":"","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Sizing; Renewable energy; Iterative method; Energy (signal processing); Key (lock); Convergence (economics); Distribution (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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006037003,0.0005786893,0.0005808618,0.0002942968,0.0003069113,0.0004312216,0.0001863288,0.0004489285,0.00004085404],"category_scores_gemma":[0.000199894,0.0006769525,0.0001252463,0.001100224,0.0001090089,0.0003572759,0.000119486,0.000282878,2.962462e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206979,"about_ca_system_score_gemma":0.000113079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003568242,"about_ca_topic_score_gemma":0.00006581056,"domain_scores_codex":[0.9970079,0.0001473463,0.0009076169,0.0008479555,0.0002242456,0.0008649219],"domain_scores_gemma":[0.9988269,0.0003257851,0.0001451656,0.0003437767,0.0002025896,0.0001557386],"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":[0.0006627587,0.0002277361,0.0001573704,0.0003576867,0.00009345415,0.000002186013,0.0001158486,0.9944758,0.00006453287,0.001809148,0.001249447,0.0007840073],"study_design_scores_gemma":[0.003332455,0.0002796433,0.0001052694,0.0003737966,0.0001590437,0.000001381961,0.0004375202,0.9929242,0.0006994384,0.00002313363,0.001096507,0.0005675923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001738247,0.001948741,0.9919422,0.00009826198,0.0003456945,0.001132788,0.0004213328,0.0001593084,0.002213452],"genre_scores_gemma":[0.8988466,0.0001402123,0.0940972,0.00008876877,0.0001159832,0.0004763497,0.00568499,0.00005169398,0.0004982185],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.897845,"threshold_uncertainty_score":0.9995682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01061144500159258,"score_gpt":0.2334183541833369,"score_spread":0.2228069091817443,"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."}}