{"id":"W4414305174","doi":"10.1016/j.epsr.2026.113109","title":"Chance Constrained Models for the Operation of Electric Storage in Energy and Reserve Markets with Uncertainty in Wind Power","year":2025,"lang":"en","type":"preprint","venue":"Electric Power Systems Research","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wind power; Context (archaeology); Energy storage; Range (aeronautics); Wind speed; Mode (computer interface); Pumped-storage hydroelectricity; Power (physics); Electric power system","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":[0.003638432,0.001688824,0.003314452,0.0009798394,0.0008483074,0.00402846,0.002900525,0.004118025,0.01056993],"category_scores_gemma":[0.01353403,0.001981543,0.001741727,0.001650281,0.002539573,0.00468692,0.001690497,0.003726422,0.0007653466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002687782,"about_ca_system_score_gemma":0.002025862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02243729,"about_ca_topic_score_gemma":0.01591452,"domain_scores_codex":[0.9987718,0.0005819378,0.0000606174,0.0001805182,0.0001429875,0.0002621236],"domain_scores_gemma":[0.9902837,0.007894799,0.0007530536,0.0001642196,0.0004727294,0.000431534],"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":[0.00006779494,0.00001788971,0.0002106654,0.00003620188,0.00003010328,0.00006820433,0.00003839429,0.9408485,0.0001187244,0.05665729,0.001035185,0.0008710038],"study_design_scores_gemma":[0.00001374594,0.00000773055,0.00009008675,0.000005608589,0.000007051309,0.000007280584,0.00001230543,0.9791704,0.00002256893,0.02051294,0.0001402466,0.00001001165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2125786,0.005215598,0.717836,0.009751233,0.0005314511,0.0001928448,0.002842007,0.0005128356,0.05053945],"genre_scores_gemma":[0.9589024,0.00131564,0.01001489,0.0003049405,0.0002021766,0.0001696423,0.000551798,0.0001636874,0.02837472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02243729,"threshold_uncertainty_score":0.04461342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02579951561859388,"score_gpt":0.2764415579910888,"score_spread":0.2506420423724949,"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."}}