{"id":"W2898893905","doi":"10.23919/ipec.2018.8507562","title":"A Dynamic Battery Charging Approach for Energy Trading in the Smart Grid","year":2018,"lang":"en","type":"article","venue":"2018 International Power Electronics Conference (IPEC-Niigata 2018 -ECCE Asia)","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Smart grid; Battery (electricity); Profitability index; Computer science; Profit (economics); Grid; Dynamic pricing; Trading strategy; Energy market; Energy storage; Business; Renewable energy; Electrical engineering; Microeconomics; Engineering; Economics; Finance; Power (physics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004821183,0.0004018174,0.0005981862,0.0001998524,0.0003895199,0.001044644,0.0009605802,0.0006732203,0.00253603],"category_scores_gemma":[0.000757713,0.0001902435,0.0005145734,0.0003763434,0.00060724,0.001538525,0.0007620945,0.0008184509,0.0002186399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000566323,"about_ca_system_score_gemma":0.0007530075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001418641,"about_ca_topic_score_gemma":0.00155284,"domain_scores_codex":[0.9996616,0.0001305051,0.00001244512,0.00005344004,0.00009614483,0.00004597633],"domain_scores_gemma":[0.9998276,0.00007600543,0.00001736095,0.00002722777,0.00003455508,0.0000171247],"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":[0.00008802838,0.00007892725,0.0005537009,0.00009635314,0.00004646708,0.0002448495,0.00009587595,0.7686927,0.006647314,0.1764595,0.001065472,0.0459308],"study_design_scores_gemma":[0.0000105991,0.00004449895,0.00008399927,0.000003923475,0.000007759898,0.0000714843,0.00001923783,0.9690791,0.0007156717,0.02825562,0.001699192,0.000008921152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03580248,0.0005573217,0.9472307,0.0003996529,0.00008689227,0.00006864604,0.00003679776,0.0001323994,0.01568508],"genre_scores_gemma":[0.962821,0.0002620683,0.03339897,0.00006015309,0.00003652108,0.0000395122,0.00001552029,0.0000191521,0.003347162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00253603,"threshold_uncertainty_score":0.008483887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0155809634945354,"score_gpt":0.2340598394200598,"score_spread":0.2184788759255243,"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."}}