{"id":"W3212440815","doi":"10.32920/ryerson.14649462.v1","title":"Residential energy management systems with renewables and battery energy storage","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"Mitacs","keywords":"Renewable energy; Energy management; Computer science; Demand response; Variety (cybernetics); Environmental economics; Controller (irrigation); Model predictive control; Energy storage; Transactive memory; Energy consumption; Scale (ratio); Control (management); Risk analysis (engineering); Electricity; Energy (signal processing); Engineering; Business; Economics; Knowledge management","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002113085,0.0002877182,0.0004058192,0.0001610687,0.0003841273,0.0008215435,0.0006788194,0.000386822,0.003339811],"category_scores_gemma":[0.0004647838,0.0002293381,0.0004964231,0.0004585356,0.0002959977,0.0009753569,0.0005815507,0.0003567383,0.0006261644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000545212,"about_ca_system_score_gemma":0.0005318006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004825987,"about_ca_topic_score_gemma":0.00569207,"domain_scores_codex":[0.9997256,0.00009631352,0.00001462707,0.00004999597,0.00008253389,0.00003075648],"domain_scores_gemma":[0.9998369,0.00004960622,0.00002095122,0.00003785677,0.00004659998,0.000008028609],"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":[0.0002380359,0.0002296643,0.002753572,0.0001317279,0.0000701666,0.0001991996,0.0001109117,0.9241374,0.006306241,0.01329802,0.001086442,0.05143865],"study_design_scores_gemma":[0.0000310606,0.0001553278,0.0008955902,0.00001046315,0.00002535144,0.00005699609,0.00005404218,0.9882826,0.003133273,0.003765637,0.003578796,0.00001085051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6304179,0.0007785693,0.304502,0.0005738352,0.0001002117,0.0001940596,0.0003424088,0.001535192,0.06155585],"genre_scores_gemma":[0.9838928,0.0001755819,0.01007492,0.0000190573,0.00001023504,0.00004074356,0.00007083253,0.0000143902,0.005701433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004825987,"threshold_uncertainty_score":0.01117271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005733752006449119,"score_gpt":0.1649487382668934,"score_spread":0.1592149862604443,"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."}}