{"id":"W2144133756","doi":"10.1109/pes.2011.6039089","title":"Stochastic analysis of wind penetration impact on electricity market prices","year":2011,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Wind power; Electricity generation; Monte Carlo method; Electricity market; Wind speed; Wake; Electric power system; Computer science; Electricity; Stochastic process; Meteorology; Power (physics); Engineering; Electrical engineering; Aerospace engineering; Mathematics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001676097,0.0001105943,0.0002162543,0.0005591028,0.00001511952,0.000009580203,0.0000881093,0.00005695889,0.0007912431],"category_scores_gemma":[0.00002854789,0.00009123983,0.00009385853,0.001601554,0.000005366335,0.0001115968,0.000003766744,0.00005584236,0.000007767729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009042026,"about_ca_system_score_gemma":0.00001454316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001043564,"about_ca_topic_score_gemma":0.00003510217,"domain_scores_codex":[0.9993358,0.00002322835,0.0002227981,0.0001111118,0.0001543884,0.0001526777],"domain_scores_gemma":[0.9996082,0.00006791782,0.00006000045,0.0001745025,0.00004910042,0.00004033988],"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":[0.00004854604,0.00006661248,0.004660236,0.00002226576,0.001368988,6.986336e-7,0.0003371252,0.9902176,0.001544909,0.0003883227,0.0006261069,0.000718587],"study_design_scores_gemma":[0.00008349667,0.0001266657,0.1534306,0.000004760186,0.0002768172,6.150095e-7,0.000005494127,0.8426343,0.00332216,0.00001418286,0.00000140163,0.00009950269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3677007,0.00006629446,0.5464038,0.000001109796,0.00005500569,0.0001670074,0.000004619912,0.0001494722,0.08545202],"genre_scores_gemma":[0.9990485,0.000006881201,0.0007735058,0.000003900665,0.000009428806,0.000003147131,0.000009988374,0.00001248995,0.0001321608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6313478,"threshold_uncertainty_score":0.8663557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032812732095264,"score_gpt":0.2139676856123262,"score_spread":0.2036395582913735,"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."}}