{"id":"W2884870305","doi":"10.1109/tia.2018.2858189","title":"Unified Probabilistic Modeling of Wind Reserves for Demand Response and Frequency Regulation in Islanded Microgrids","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Research and Development Corporation of Newfoundland and Labrador","keywords":"Microgrid; Probabilistic logic; Wind power; Demand response; Automatic frequency control; Computer science; Grid; Electric power system; Distributed generation; Wind speed; Automatic Generation Control; Electricity generation; Engineering; Control engineering; Reliability engineering; Renewable energy; Power (physics); Electricity; Telecommunications","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":[0.0012277,0.0007309818,0.000859723,0.0005444789,0.000312733,0.0009854345,0.001226169,0.0007382871,0.001078489],"category_scores_gemma":[0.003529554,0.0005812612,0.0008936836,0.0006233889,0.0005598347,0.001581246,0.0008133616,0.0007463326,0.000167754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008213577,"about_ca_system_score_gemma":0.0009378966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01172254,"about_ca_topic_score_gemma":0.006483424,"domain_scores_codex":[0.9994467,0.0001871999,0.00003314017,0.0001057369,0.0001579436,0.00006927163],"domain_scores_gemma":[0.9990442,0.0004420349,0.0001981213,0.00008020703,0.0002017709,0.00003362909],"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":[0.000007887805,0.000004618818,0.000227987,0.000004718629,0.000005866227,0.00001158226,0.000007377078,0.9962649,0.0001790462,0.001853694,0.00004062535,0.001391651],"study_design_scores_gemma":[6.024183e-7,0.000002385043,0.00005948936,4.376784e-7,0.000001441443,0.000002204076,0.000001324753,0.9994428,0.00003813461,0.0004261778,0.00002385922,0.000001100238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05626429,0.0001026198,0.9409346,0.00009523836,0.00001072815,0.0000358905,0.000120895,0.0003134525,0.002122332],"genre_scores_gemma":[0.9713039,0.0001552263,0.02668484,0.00001958972,0.0000154182,0.00007685184,0.0001363283,0.0000533146,0.001554551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01172254,"threshold_uncertainty_score":0.02330858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663818735092086,"score_gpt":0.238393863288125,"score_spread":0.2217556759372042,"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."}}