{"id":"W4406939239","doi":"10.2139/ssrn.5117154","title":"Comparison of Machine Learning and Mpc Methods for Control of Home Battery Storage Systems in Distribution Grids","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Battery (electricity); Control (management); Model predictive control; Computer science; Battery storage; Control theory (sociology); Artificial intelligence; Power (physics); Physics; Thermodynamics","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":[0.001722001,0.0005695036,0.001100268,0.0005751128,0.0003684375,0.0008142464,0.0005040999,0.000611019,0.001508394],"category_scores_gemma":[0.003863323,0.0002040494,0.0003580599,0.0005439431,0.0003182058,0.0007242285,0.0004233459,0.000765032,0.0001672115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007051277,"about_ca_system_score_gemma":0.0006751665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0089412,"about_ca_topic_score_gemma":0.005054628,"domain_scores_codex":[0.9993696,0.0002681996,0.00004493968,0.00006019682,0.0002094861,0.00004772909],"domain_scores_gemma":[0.9973825,0.001903654,0.000114727,0.0001247225,0.0004413501,0.0000330845],"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":[0.0004264791,0.00009213307,0.0006746452,0.0002626455,0.00008194172,0.00002025853,0.00003822371,0.8868181,0.001010192,0.001846708,0.0004510852,0.1082776],"study_design_scores_gemma":[0.0000145631,0.00005521983,0.0005333845,0.000007725572,0.00001191213,0.00000445543,0.00000765699,0.9981158,0.0005734536,0.0004938755,0.0001780578,0.000003946388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3364923,0.007665489,0.6377473,0.0007886786,0.0003646972,0.000148107,0.0001501852,0.001228925,0.01541441],"genre_scores_gemma":[0.9808713,0.0004990371,0.01700062,0.00003539129,0.00003943217,0.00003353402,0.00005627728,0.00003327686,0.00143121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0089412,"threshold_uncertainty_score":0.01777834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008028270401419,"score_gpt":0.299103038048097,"score_spread":0.2890227553440828,"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."}}