{"id":"W4385759838","doi":"10.3390/electronics12163408","title":"Enhancing the Performance of a Renewable Energy System Using a Novel Predictive Control Method","year":2023,"lang":"en","type":"article","venue":"Electronics","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Nazarbayev University","keywords":"Model predictive control; Control theory (sociology); Computer science; Wind power; Renewable energy; Controller (irrigation); Permanent magnet synchronous generator; Maximum power point tracking; Control engineering; Maximum power principle; Photovoltaic system; Engineering; Control (management); Voltage; 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":[0.0002394034,0.0004529583,0.0002886692,0.0002208791,0.0001716216,0.0004827775,0.0004382509,0.00027264,0.0007809682],"category_scores_gemma":[0.0004807594,0.0001240354,0.0001884854,0.0001988795,0.0001882264,0.000319367,0.0002402939,0.0002971049,0.0001489833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001880219,"about_ca_system_score_gemma":0.0003300325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009478841,"about_ca_topic_score_gemma":0.000947253,"domain_scores_codex":[0.9998711,0.00002052587,0.000007166499,0.0000260247,0.00006500218,0.00001017724],"domain_scores_gemma":[0.9998642,0.00004473379,0.00002937171,0.00001984749,0.00003689107,0.000004963401],"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":[0.0001289933,0.000125808,0.0005658179,0.0003130898,0.00005646043,0.000210139,0.00009945658,0.6758106,0.07959521,0.00765499,0.00097809,0.2344613],"study_design_scores_gemma":[0.000007407962,0.0001052211,0.0001785791,0.000007466369,0.00001289384,0.00004167819,0.000004566974,0.9900966,0.008314412,0.0004475549,0.0007781853,0.000005370915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03785274,0.000483783,0.9544086,0.00007107959,0.00006189298,0.00005092232,0.00001722924,0.0007717255,0.006282068],"genre_scores_gemma":[0.9495376,0.0002786389,0.04866472,0.00002532156,0.00002954544,0.00005603142,0.00002266678,0.00002056733,0.001364938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009478841,"threshold_uncertainty_score":0.002612591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004905469693556331,"score_gpt":0.1959202724289986,"score_spread":0.1910148027354423,"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."}}