{"id":"W2599344532","doi":"10.20508/ijrer.v7i1.5172.g6974","title":"Frequency Control of Micro Grid with wind Perturbations Using Levy walks with Spider Monkey Optimization Algorithm","year":2017,"lang":"en","type":"article","venue":"International Journal of Renewable Energy Research","topic":"Frequency Control in Power Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spider; Grid; Algorithm; Optimization algorithm; Computer science; Control (management); Mathematical optimization; Control theory (sociology); Mathematics; Biology; Artificial intelligence; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002339426,0.0004242229,0.0006189534,0.0002699842,0.0002659368,0.0004891896,0.0004435496,0.0005306266,0.001061119],"category_scores_gemma":[0.0005173067,0.0001777621,0.0003396549,0.0002546607,0.0003319274,0.000246957,0.0003723948,0.0002946378,0.0001181193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002970211,"about_ca_system_score_gemma":0.0005021581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004709181,"about_ca_topic_score_gemma":0.00309367,"domain_scores_codex":[0.9999156,0.0000251486,0.000003683628,0.00001503272,0.0000249487,0.0000156061],"domain_scores_gemma":[0.9998152,0.000090473,0.00003095599,0.000008829139,0.00004033397,0.00001434259],"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":[0.00003404636,0.0000188484,0.0006028994,0.00002629283,0.00002501311,0.00005856944,0.00002868096,0.9826533,0.001332166,0.002332793,0.0003038159,0.01258365],"study_design_scores_gemma":[0.000005162661,0.00001850951,0.00006880982,0.000001424832,0.000002402832,0.000006291601,0.000003770059,0.9993104,0.00008472264,0.0003909697,0.0001062181,0.00000133417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.164751,0.0005834855,0.8231806,0.0002738795,0.00006060207,0.00006526018,0.00003682509,0.0003746312,0.01067375],"genre_scores_gemma":[0.9679857,0.0001218549,0.02937834,0.00004705237,0.00001361801,0.00007976934,0.00002663654,0.00001888765,0.00232808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004709181,"threshold_uncertainty_score":0.009363532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02850459398752323,"score_gpt":0.2943528233434766,"score_spread":0.2658482293559534,"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."}}