{"id":"W2029579463","doi":"10.1049/iet-gtd.2009.0739","title":"Heuristic curve-fitted technique for distributed generation optimisation in radial distribution feeder systems","year":2011,"lang":"en","type":"article","venue":"IET Generation Transmission & Distribution","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Distributed generation; Reliability (semiconductor); Heuristic; Mathematical optimization; Sensitivity (control systems); Computer science; Voltage; Electric power system; Power (physics); Reliability engineering; Control theory (sociology); Mathematics; Engineering; Electronic engineering; Electrical engineering; Renewable energy","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":[0.001265891,0.0008798665,0.0008621793,0.001206651,0.0003892964,0.0005827856,0.0008512167,0.001032944,0.003116595],"category_scores_gemma":[0.00365759,0.0005461341,0.0008489249,0.001705908,0.0005536859,0.000673931,0.000565124,0.001123167,0.0004615341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008248849,"about_ca_system_score_gemma":0.001017984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005898362,"about_ca_topic_score_gemma":0.004881682,"domain_scores_codex":[0.9995441,0.0002459521,0.00001394334,0.00003652602,0.0001228596,0.00003658748],"domain_scores_gemma":[0.9987862,0.0008597532,0.00009005483,0.00005512817,0.0001821342,0.00002684481],"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":[0.00003268773,0.00002558994,0.0001623413,0.00004156062,0.00001816358,0.00002330928,0.00003042372,0.9697396,0.0008043459,0.001788031,0.0003359642,0.0269981],"study_design_scores_gemma":[0.000007201871,0.00001679001,0.00004643251,0.000004613485,0.000002413174,0.000006679222,0.0000053289,0.9986913,0.0002359758,0.0006503154,0.0003290911,0.000003808611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01243303,0.0002505685,0.9844855,0.00005374641,0.00002215644,0.00005894608,0.00003479799,0.0003323207,0.002328922],"genre_scores_gemma":[0.4327837,0.0003889712,0.5622832,0.00009234197,0.00003977477,0.0003677893,0.0002063766,0.0002634718,0.00357445],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005898362,"threshold_uncertainty_score":0.01172805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0352244040144332,"score_gpt":0.2367831918336961,"score_spread":0.2015587878192629,"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."}}