{"id":"W2886075502","doi":"10.3390/en11082048","title":"Optimal Component Sizing for Peak Shaving in Battery Energy Storage System for Industrial Applications","year":2018,"lang":"en","type":"article","venue":"Energies","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Peaking power plant; Sizing; Payback period; Battery (electricity); Energy storage; Automotive engineering; Load profile; Computer science; Peak demand; Reliability engineering; Power (physics); Electricity; Engineering; Electrical engineering; Distributed generation; Production (economics); Renewable energy; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001413811,0.0001562186,0.0002092278,0.0002448066,0.0001216238,0.00004562163,0.000330772,0.0001462822,0.000005320495],"category_scores_gemma":[0.00004687146,0.0001669906,0.00005247662,0.0002121542,0.0000831877,0.0001471578,0.0001143428,0.0001297864,0.000003796859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003044839,"about_ca_system_score_gemma":0.00001828071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002224286,"about_ca_topic_score_gemma":0.00003330418,"domain_scores_codex":[0.9989441,0.00001319534,0.0002575218,0.0002425889,0.0001163693,0.0004262347],"domain_scores_gemma":[0.999296,0.0002722081,0.00003505464,0.0003041425,0.00005678409,0.00003580726],"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":[0.00006713376,0.0000323394,0.0001263907,0.0002432236,0.00005030116,0.000003506365,0.0001540001,0.8729214,0.07917824,0.007016461,0.002292065,0.03791494],"study_design_scores_gemma":[0.002480897,0.0002723461,0.0001969121,0.0002987725,0.00002287021,0.0000120046,0.003025317,0.4870647,0.3205286,0.0004872337,0.1847537,0.000856632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3978312,0.0003260976,0.5991168,0.00009909818,0.0004512094,0.0006594671,0.00007467525,0.001058066,0.0003833519],"genre_scores_gemma":[0.982118,0.00001411525,0.01494666,0.00001036156,0.0005388448,0.002178009,0.00003989093,0.0000562503,0.00009792363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5842867,"threshold_uncertainty_score":0.6809677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03373809120928455,"score_gpt":0.2723683548824535,"score_spread":0.238630263673169,"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."}}