{"id":"W4312786875","doi":"10.1109/pesgm48719.2022.9916812","title":"Duck-curve Mitigation in Power Grids with High Penetration of PV Generation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Power &amp; Energy Society General Meeting (PESGM)","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Penetration (warfare); Electricity generation; Environmental science; Power grid; Electrical engineering; Power (physics); Nuclear engineering; Materials science; Engineering; Physics; Operations research","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":[0.0002241843,0.0002968427,0.0003946499,0.0001558651,0.0002886915,0.0004105001,0.0003526221,0.0002460106,0.0006909858],"category_scores_gemma":[0.0004673069,0.0001415584,0.00019418,0.0002900718,0.0003024666,0.0004969572,0.0003136374,0.0003778434,0.00008136105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005434119,"about_ca_system_score_gemma":0.0003470375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007595575,"about_ca_topic_score_gemma":0.01218195,"domain_scores_codex":[0.9998786,0.00004620872,0.000003024045,0.00001717279,0.00002556133,0.00002951461],"domain_scores_gemma":[0.9997937,0.00008673774,0.00003205299,0.00003351668,0.000038224,0.00001579363],"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":[0.000176893,0.0000822112,0.007983887,0.00006050582,0.0000239543,0.0003614165,0.0001182063,0.9604455,0.0117789,0.00163194,0.000620853,0.01671568],"study_design_scores_gemma":[0.00001968101,0.0002213953,0.005582719,0.00000598203,0.00001114033,0.00006834903,0.0001560775,0.9837852,0.008082156,0.00112144,0.0009369972,0.00000893791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9336404,0.00009219634,0.06013998,0.0001219445,0.00001503653,0.00004816485,0.00008523475,0.0003714556,0.005485535],"genre_scores_gemma":[0.9978382,0.00002251752,0.00178671,0.000007139423,0.000001671831,0.000004814636,0.00001472453,0.000009040332,0.000315188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007595575,"threshold_uncertainty_score":0.01510274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00803790246504773,"score_gpt":0.2110092058839434,"score_spread":0.2029713034188957,"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."}}