{"id":"W2751099879","doi":"10.2139/ssrn.3027705","title":"Optimal Procurement of Distributed Energy Resources","year":2017,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Electric Power System Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Canada First Research Excellence Fund; Government of Canada","keywords":"Procurement; Order (exchange); Electricity; Environmental economics; Distributed generation; Business; Distribution (mathematics); Industrial organization; Risk analysis (engineering); Microeconomics; Computer science; Operations research; Economics; Finance; Engineering; Renewable energy; Marketing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001589466,0.0009159868,0.001717854,0.0007559147,0.0004758668,0.002625638,0.001059193,0.001725231,0.008086257],"category_scores_gemma":[0.006935074,0.001008204,0.0005607073,0.001884986,0.001064421,0.002192937,0.001325412,0.00146701,0.0005923157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001914971,"about_ca_system_score_gemma":0.002207495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002982656,"about_ca_topic_score_gemma":0.003326169,"domain_scores_codex":[0.9990982,0.000478976,0.00003389082,0.0001044618,0.0001316899,0.0001527366],"domain_scores_gemma":[0.9982029,0.001221554,0.0001029278,0.0001499693,0.0001925797,0.0001300286],"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":[0.0002533639,0.0001019092,0.0004537115,0.0002265234,0.00004904605,0.000124263,0.00003824897,0.9063439,0.001054932,0.06746556,0.003187923,0.02070057],"study_design_scores_gemma":[0.00006126157,0.0000583556,0.0003045292,0.00003195949,0.00002244038,0.00003552164,0.00007358192,0.900791,0.0005644436,0.09657548,0.00146848,0.00001298804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1769942,0.002012127,0.7393803,0.003423674,0.0003359223,0.0002857084,0.0009495853,0.0003392118,0.07627932],"genre_scores_gemma":[0.9514896,0.0006506592,0.03769221,0.00009806823,0.00005852952,0.0001340444,0.0001873398,0.0000972659,0.009592347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008086257,"threshold_uncertainty_score":0.02705127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006458869113208802,"score_gpt":0.210041397819429,"score_spread":0.2035825287062202,"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."}}