{"id":"W7127531193","doi":"10.1109/ccece64018.2025.11364429","title":"Optimal Day-Ahead BESS Schedules in Microgrids: A Comparison Between Reinforcement Learning and Meta-Heuristic Algorithms","year":2025,"lang":"","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Microgrid; Reinforcement learning; Scheduling (production processes); Grid; Electric power system; Genetic algorithm; Job shop scheduling; Optimization algorithm","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":[0.002322673,0.0006999015,0.001051284,0.000673453,0.000323637,0.0008403771,0.001086321,0.0009651286,0.0008025664],"category_scores_gemma":[0.004679628,0.0003724315,0.0003917186,0.0005143326,0.000611382,0.0009237679,0.0005249897,0.0009151581,0.0001043007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001344682,"about_ca_system_score_gemma":0.001531972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01256779,"about_ca_topic_score_gemma":0.008245935,"domain_scores_codex":[0.9995109,0.0002650369,0.00002183362,0.00005906174,0.00008669154,0.00005643719],"domain_scores_gemma":[0.9967881,0.002541242,0.0002120478,0.0000891484,0.0002739608,0.00009540942],"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":[0.00005346482,0.00004847513,0.0003802195,0.00001688603,0.00002163978,0.000007438668,0.00001170233,0.9883631,0.0000603718,0.0009797992,0.0001148876,0.009942162],"study_design_scores_gemma":[0.0000108489,0.00002498762,0.00006263049,0.00000331435,0.000003848782,0.000001781264,0.000005005584,0.9993857,0.00003593323,0.0004200716,0.00004449879,0.000001322512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3900142,0.003098205,0.5914137,0.001342028,0.0001507656,0.0002132235,0.0001177021,0.0005819151,0.01306828],"genre_scores_gemma":[0.9624481,0.000370734,0.03630249,0.0001062901,0.00002770061,0.00004826521,0.00004271529,0.00003125737,0.0006225039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01256779,"threshold_uncertainty_score":0.02498925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01629613471176659,"score_gpt":0.2669400487055482,"score_spread":0.2506439139937816,"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."}}