{"id":"W4380029382","doi":"10.1109/icit58465.2023.10143039","title":"Intelligent Control of An Islanded Hybrid Microgrid","year":2023,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Opal-Rt Technologies (Canada)","funders":"","keywords":"Microgrid; Converters; Computer science; Controller (irrigation); Battery (electricity); Supercapacitor; Control engineering; Intelligent control; Artificial neural network; MATLAB; Electric power system; Energy storage; Power (physics); Automotive engineering; Engineering; Control (management); Electrical engineering; Artificial intelligence","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":[0.0001477803,0.0003216131,0.0002402896,0.0001280596,0.0002062411,0.0005144351,0.0003364811,0.0001894958,0.001081003],"category_scores_gemma":[0.0002181345,0.0001119093,0.0002039438,0.0001050322,0.0002847826,0.0002523539,0.0003475694,0.0002701825,0.0001483801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001813052,"about_ca_system_score_gemma":0.0002054002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001828846,"about_ca_topic_score_gemma":0.001799575,"domain_scores_codex":[0.999935,0.00001300123,0.000004342272,0.00001632184,0.0000214867,0.000009863507],"domain_scores_gemma":[0.9999151,0.00002428255,0.0000195271,0.00001302091,0.00002090745,0.000007149052],"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":[0.0001342082,0.00006346725,0.0007193199,0.00008909796,0.00006774926,0.000243335,0.0001076887,0.9118383,0.03101532,0.006745779,0.0007973881,0.04817845],"study_design_scores_gemma":[0.00001129581,0.00008464546,0.0003224552,0.000003832082,0.00001246203,0.00002245285,0.00001155488,0.9954347,0.00216776,0.001130975,0.000793499,0.000004340327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2502788,0.0002594422,0.7218425,0.0001846373,0.0001048787,0.00008108334,0.00008893813,0.001595368,0.02556431],"genre_scores_gemma":[0.9930223,0.00003991829,0.005515843,0.00001395543,0.000006830589,0.00002064251,0.00001569052,0.000009305268,0.001355532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001828846,"threshold_uncertainty_score":0.00363642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005864496532805113,"score_gpt":0.1948819328200067,"score_spread":0.1890174362872016,"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."}}