{"id":"W4321465645","doi":"10.1016/j.enconman.2023.116809","title":"Integrated model for optimal energy management and demand response of microgrids considering hybrid hydrogen-battery storage systems","year":2023,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":161,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Microgrid; Demand response; Renewable energy; Energy storage; Energy management; Mathematical optimization; Computer science; Schedule; Distributed generation; Automotive engineering; Electricity; Reliability engineering; Engineering; Power (physics); Energy (signal processing); Electrical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0002430741,0.0001915211,0.0002289624,0.000333394,0.00008183048,0.00004517745,0.00008111077,0.00004569177,0.000005539197],"category_scores_gemma":[0.000002413236,0.0001948063,0.00004814615,0.0001440419,0.00003938662,0.00008494726,0.0001256871,0.00003156373,0.000001221612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004054952,"about_ca_system_score_gemma":0.000005074976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001570134,"about_ca_topic_score_gemma":0.000001784402,"domain_scores_codex":[0.9990923,0.0000371027,0.0002609287,0.0002590482,0.0001098543,0.0002407707],"domain_scores_gemma":[0.9996324,0.00004677958,0.00004832936,0.0001632939,0.00003024809,0.00007891689],"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":[0.0002483009,0.00001417031,0.000009888483,0.0004952888,0.0002769685,0.00004150203,0.00008172158,0.9818839,0.002486687,0.001697155,0.008344562,0.004419869],"study_design_scores_gemma":[0.001301821,0.00003629438,0.00003015364,0.0000833571,0.00008447748,0.000005429655,0.0002609839,0.9543374,0.002842878,0.00002345045,0.04080286,0.0001909435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2033274,0.003434436,0.791717,0.00008974494,0.0004366767,0.0003769673,0.00003739675,0.0003532172,0.0002271902],"genre_scores_gemma":[0.9845287,0.01001336,0.002149221,0.00010522,0.0000194658,0.00011296,0.00008674864,0.00003939289,0.00294499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7895678,"threshold_uncertainty_score":0.7943969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007499137086043928,"score_gpt":0.1771834309632967,"score_spread":0.1696842938772528,"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."}}