{"id":"W4414592678","doi":"10.3390/electronics14193846","title":"Climate-Adaptive Residential Demand Response Integration with Power Quality-Aware Distributed Generation Systems: A Comprehensive Multi-Objective Optimization Framework for Smart Home Energy Management","year":2025,"lang":"en","type":"article","venue":"Electronics","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Demand response; Flexibility (engineering); Renewable energy; Adaptability; Distributed generation; Home automation; Artificial neural network; Electric power system; Sensitivity (control systems)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003658131,0.0003319328,0.0003289132,0.0003022904,0.0002394994,0.0001630093,0.0001652155,0.000176665,0.00000461957],"category_scores_gemma":[0.00003924163,0.0003339265,0.00007665881,0.0005717869,0.00003345407,0.0002170863,0.00006247416,0.0001963685,0.000002306341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001047891,"about_ca_system_score_gemma":0.00005623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000228922,"about_ca_topic_score_gemma":0.0002593716,"domain_scores_codex":[0.9980737,0.0002592297,0.0004501887,0.000443845,0.0002632004,0.0005098101],"domain_scores_gemma":[0.9989105,0.0002178953,0.000121106,0.0003957423,0.0003035743,0.0000512101],"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":[0.001260409,0.0000517317,0.0000223834,0.00009457787,0.0004707122,0.000004586321,0.0001232583,0.9232168,0.000297427,0.07346869,0.0007731996,0.0002162225],"study_design_scores_gemma":[0.001603301,0.0003372058,0.001358024,0.000240979,0.0001855775,0.000002018675,0.0008008979,0.9877594,0.003352586,0.0003076556,0.003609863,0.0004425524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01177074,0.001540727,0.9844565,0.00008132949,0.0007588517,0.0008870439,0.00007721199,0.0003569547,0.00007064056],"genre_scores_gemma":[0.9666174,0.0008249943,0.03012691,0.00009787441,0.0001029743,0.001000966,0.0009460325,0.00008060333,0.0002022176],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9548467,"threshold_uncertainty_score":0.9999112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262825424312762,"score_gpt":0.2512719327620055,"score_spread":0.2386436785188779,"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."}}