{"id":"W3116851389","doi":"10.3390/s21010130","title":"Demand Management for Optimized Energy Usage and Consumer Comfort Using Sequential Optimization","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Thermal comfort; HVAC; Computer science; Demand response; Energy consumption; Scheduling (production processes); Linear programming; Efficient energy use; Air conditioning; Energy management; Mathematical optimization; Reliability engineering; Engineering; Energy (signal processing); Electricity; Operations management; Algorithm","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":[0.0005055671,0.0007571003,0.0006297211,0.0002716962,0.0003440969,0.0007759139,0.0005819583,0.0004401447,0.002384052],"category_scores_gemma":[0.0007588548,0.0004076788,0.0006161653,0.0004790465,0.0003063946,0.000655518,0.000562479,0.0005153165,0.0001912352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008115519,"about_ca_system_score_gemma":0.00114728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007357989,"about_ca_topic_score_gemma":0.007428675,"domain_scores_codex":[0.9996487,0.0001020911,0.00001351765,0.0000787457,0.00008669506,0.000070239],"domain_scores_gemma":[0.9997825,0.0000893119,0.00003967638,0.00001583364,0.00005237233,0.00002033747],"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":[0.00003828266,0.00003580038,0.0003167571,0.0000226862,0.00001570004,0.0000203046,0.00001931238,0.9885323,0.001949699,0.002184323,0.000288244,0.006576618],"study_design_scores_gemma":[0.000003564605,0.00001788016,0.00006692842,9.247455e-7,0.000003195053,0.000002666534,0.000006373452,0.9985745,0.0002577134,0.0009105008,0.0001542751,0.000001451755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08482944,0.0001165978,0.9075413,0.0001923259,0.0000337523,0.00007731697,0.0001057473,0.0002548526,0.0068487],"genre_scores_gemma":[0.9263306,0.00009335565,0.0697659,0.00006492857,0.00001700996,0.0001168709,0.000115857,0.00006906919,0.003426482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007357989,"threshold_uncertainty_score":0.01463032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112853134088911,"score_gpt":0.2179576694929108,"score_spread":0.1968291381520217,"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."}}