{"id":"W4408348672","doi":"10.1109/access.2025.3548044","title":"Dynamic Characteristics-Based Capacity Optimization Strategy for Hybrid AA-CAES and Battery Storage Systems in Source-Grid-Load-Storage Integrated Base","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Computer data storage; Grid; Energy storage; Battery (electricity); Base (topology); Battery storage; Smart grid; Electrical engineering; Engineering; Computer hardware; Power (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004753636,0.0003764744,0.0006161114,0.0004132789,0.0001694994,0.0004094873,0.0004029844,0.0002143142,0.00003230742],"category_scores_gemma":[0.00011822,0.0003419024,0.00008758192,0.0004294458,0.00008559999,0.0004454465,0.0000493944,0.0002040296,0.000002422779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004574596,"about_ca_system_score_gemma":0.000312083,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01880075,"about_ca_topic_score_gemma":0.003471262,"domain_scores_codex":[0.9977828,0.0002304327,0.0007130976,0.0005919651,0.0002216445,0.000460031],"domain_scores_gemma":[0.998665,0.0002231482,0.0002905649,0.0004444823,0.0002549537,0.0001218948],"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":[0.0001257441,0.000105903,0.0007973493,0.0005315825,0.00005919769,0.00003085017,0.00004343026,0.9940274,0.001946571,0.0001633717,0.0008944412,0.001274128],"study_design_scores_gemma":[0.001514634,0.00006258085,0.001784822,0.0005489819,0.00004687038,0.000007610067,0.0001096722,0.98578,0.001748936,0.0000360801,0.007934853,0.0004249651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5728359,0.0003815022,0.4223252,0.00006345794,0.003067872,0.0004655866,0.0002457569,0.0001370503,0.0004777206],"genre_scores_gemma":[0.9972305,0.00003938312,0.0001591727,0.0001810969,0.0001608417,0.0002592813,0.0002667474,0.00005673677,0.001646292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4243946,"threshold_uncertainty_score":0.9999033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02008460262389112,"score_gpt":0.2611129266930037,"score_spread":0.2410283240691126,"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."}}