{"id":"W1999395055","doi":"10.1109/epec.2014.11","title":"Accommodating High Levels of Renewable Generation in Remote Microgrids under Uncertainty","year":2014,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Renewable energy; Flexibility (engineering); Intermittency; Computer science; Grid; Probabilistic logic; Reliability engineering; Wind power; Energy storage; Electricity generation; Electric power system; Renewable resource; Distributed generation; Power (physics); Engineering; Electrical engineering","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":[0.0009055249,0.0006349213,0.0006641878,0.0002330914,0.0004161593,0.0009263478,0.0006026424,0.0005794532,0.0007534529],"category_scores_gemma":[0.002135673,0.0003901488,0.0005555215,0.0003847848,0.0005879335,0.001246269,0.0008762693,0.0005894935,0.00009760905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005860072,"about_ca_system_score_gemma":0.0004192359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003942268,"about_ca_topic_score_gemma":0.0033045,"domain_scores_codex":[0.9995229,0.0002079147,0.00002106754,0.00007292315,0.00009620965,0.00007897335],"domain_scores_gemma":[0.998863,0.0007493136,0.000203858,0.00007814552,0.00006469249,0.00004107065],"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":[0.00001932098,0.000006294184,0.000390033,0.00001222082,0.00001058659,0.0001544346,0.00001261006,0.9962808,0.0005267286,0.001241793,0.00004079723,0.001304289],"study_design_scores_gemma":[0.000004017626,0.00002903358,0.0003923036,0.000003028744,0.000007949946,0.00003656926,0.0000239527,0.9969211,0.0003323808,0.002166666,0.00007765997,0.000005403739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.65644,0.0002708033,0.3350706,0.0002706702,0.00002842885,0.00005575156,0.0001393617,0.000253234,0.007471269],"genre_scores_gemma":[0.9980291,0.00003738581,0.001648461,0.000005265116,0.000004633293,0.00000816622,0.00001342556,0.000006862771,0.0002467609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003942268,"threshold_uncertainty_score":0.007838666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02186947298334901,"score_gpt":0.2206646702351261,"score_spread":0.1987951972517771,"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."}}