{"id":"W4405602314","doi":"10.1109/synergymed62435.2024.10799262","title":"Towards dynamic pricing algorithm for residential buildings: A Model Predictive Control framework for load aggregation","year":2024,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Collège Shawinigan; University of Waterloo; Université de Sherbrooke; Concordia University","funders":"Hydro-Québec","keywords":"Model predictive control; Computer science; Control (management); Mathematical optimization; Algorithm; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009054577,0.0006094783,0.0008339515,0.000377282,0.0004278322,0.001068221,0.001164566,0.0007446563,0.001582761],"category_scores_gemma":[0.001595867,0.0003827623,0.0004893067,0.0005597087,0.00051457,0.0008030579,0.0007017499,0.001197038,0.0003068437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008425657,"about_ca_system_score_gemma":0.001295498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.014096,"about_ca_topic_score_gemma":0.01003955,"domain_scores_codex":[0.999684,0.00009212997,0.00001411072,0.00006131645,0.0001064875,0.00004201805],"domain_scores_gemma":[0.999671,0.0001420013,0.00003802843,0.00002407066,0.0001070236,0.00001787327],"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":[0.000009307993,0.00001551145,0.0001147579,0.000009371698,0.000007105975,0.0000125144,0.00001829549,0.9822005,0.0003430983,0.005104974,0.0002714853,0.01189316],"study_design_scores_gemma":[0.000001057913,0.000002374343,0.00000889381,6.431684e-7,5.831939e-7,9.152555e-7,0.000001167216,0.9991552,0.00003268945,0.0007310953,0.00006472641,7.016878e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005432596,0.00005212117,0.9926829,0.0001045044,0.00001381431,0.00001966253,0.00001654144,0.0001929881,0.001484837],"genre_scores_gemma":[0.7803934,0.0002000146,0.2163075,0.0001263554,0.00005985183,0.0001936619,0.0001219675,0.00008961923,0.00250768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.014096,"threshold_uncertainty_score":0.02802789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006608502889492049,"score_gpt":0.241367918935186,"score_spread":0.2347594160456939,"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."}}