{"id":"W4411037420","doi":"10.18280/jesa.580416","title":"Optimization of a Hybrid PV-Wind Power System for Enhancing Efficiency and Power Quality Using MATLAB/SIMULINK Simulations","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"MATLAB; Power quality; Computer science; Power (physics); Wind power; Quality (philosophy); Photovoltaic system; Automotive engineering; Environmental science; Control theory (sociology); Electrical engineering; Engineering; Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002360431,0.0006396009,0.0005254128,0.0003052843,0.0003022942,0.0006718651,0.000494529,0.0006187335,0.003134655],"category_scores_gemma":[0.0004798885,0.0002613909,0.0004692318,0.0002699827,0.0002281579,0.0003676062,0.0002866761,0.0004254954,0.0003244934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004278398,"about_ca_system_score_gemma":0.0006260719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008392389,"about_ca_topic_score_gemma":0.006810392,"domain_scores_codex":[0.9998971,0.00003209885,0.00000662767,0.00001408733,0.00003306492,0.00001698774],"domain_scores_gemma":[0.9997992,0.0001029777,0.00003127696,0.00001069433,0.00004802169,0.000007949513],"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":[0.00002851277,0.00001586077,0.0003264592,0.00005220339,0.000009923724,0.00005327313,0.00001624452,0.9955486,0.001570188,0.0004273949,0.0001089329,0.001842438],"study_design_scores_gemma":[0.00001263518,0.00003733298,0.0002019486,0.000006365952,0.000006293119,0.000006789037,0.00001124305,0.998313,0.000996921,0.0001567257,0.0002478107,0.00000291578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6107366,0.0004433509,0.3392516,0.0002641473,0.00006180334,0.000402618,0.00130449,0.001581365,0.04595403],"genre_scores_gemma":[0.9803333,0.0001133871,0.0163623,0.00001435201,0.000002817827,0.0002028241,0.0001597225,0.00003664526,0.002774752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008392389,"threshold_uncertainty_score":0.0166871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682381104569446,"score_gpt":0.2669890355903184,"score_spread":0.250165224544624,"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."}}