{"id":"W4404103012","doi":"10.1109/sege62220.2024.10739547","title":"Improvement of Microgrids Operation Considering Demand Response Using Imperialist Competitive Algorithm","year":2024,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Demand response; Imperialist competitive algorithm; Algorithm; Algorithm design; Mathematical optimization; Engineering; Mathematics; Electrical engineering; Electricity; Metaheuristic","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":[0.000839924,0.0009830592,0.001355138,0.0006313024,0.000680294,0.001360342,0.00111344,0.00100848,0.002285106],"category_scores_gemma":[0.001843847,0.0003303867,0.0006464429,0.0006188523,0.0004397308,0.0008210107,0.0007722891,0.0006020708,0.0002745701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008699027,"about_ca_system_score_gemma":0.001437344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01242542,"about_ca_topic_score_gemma":0.007087219,"domain_scores_codex":[0.9995345,0.000149123,0.00002451165,0.00007712452,0.0001285099,0.00008619557],"domain_scores_gemma":[0.999519,0.0002183874,0.00005835871,0.00002372775,0.0001451635,0.00003539898],"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":[0.0000610061,0.00005895915,0.0004581798,0.00007996847,0.00003362805,0.00008240833,0.00007170488,0.9686196,0.001046941,0.002544823,0.0007742761,0.02616853],"study_design_scores_gemma":[0.000006589408,0.00002458951,0.00006125663,0.00000261819,0.000005283082,0.00001209171,0.00001231975,0.9991012,0.0001627241,0.0003706438,0.0002380717,0.000002636521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1569924,0.001174304,0.8134193,0.0004995288,0.0001312326,0.0002306285,0.0001019058,0.0009620396,0.02648863],"genre_scores_gemma":[0.9444467,0.0002599474,0.05251171,0.0000571452,0.00002790392,0.0001035234,0.00008240516,0.00004794152,0.002462612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01242542,"threshold_uncertainty_score":0.02470618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009762401596526915,"score_gpt":0.2298567722174817,"score_spread":0.2200943706209547,"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."}}