{"id":"W4313568642","doi":"10.1016/j.enconman.2023.116656","title":"Sizing-design method for compressed air energy storage (CAES) systems: A case study based on power grid in Ontario","year":2023,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sizing; Compressed air energy storage; Gas compressor; Energy (signal processing); Energy storage; Power (physics); Process engineering; Engineering; Compressed air; Environmental science; Automotive engineering; Mechanical engineering; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003410792,0.00041369,0.0003482322,0.0003790014,0.001250571,0.0009009337,0.0005815027,0.000439802,0.002421548],"category_scores_gemma":[0.0005240174,0.0002469101,0.0003167158,0.00049504,0.0004749369,0.0002582183,0.0002192503,0.000225261,0.0001401312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005008416,"about_ca_system_score_gemma":0.005940948,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4641254,"about_ca_topic_score_gemma":0.6547027,"domain_scores_codex":[0.9997844,0.000044989,0.00000969889,0.00002752909,0.00007884386,0.00005455712],"domain_scores_gemma":[0.9997469,0.00009412472,0.00002215396,0.0000147964,0.0001040505,0.00001799847],"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":[0.0003916385,0.0002205519,0.01333425,0.0003230788,0.00005332517,0.0007284365,0.0007226416,0.8777016,0.02315771,0.005976287,0.00230876,0.07508166],"study_design_scores_gemma":[0.00008321195,0.0003050829,0.009965565,0.00001535074,0.00005841608,0.00009164836,0.0009391157,0.973433,0.008902865,0.0009693612,0.005210684,0.0000258158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9072009,0.0002276252,0.06170339,0.0002038791,0.00001503414,0.0005902592,0.000395066,0.0003304078,0.02933357],"genre_scores_gemma":[0.9855306,0.00005146757,0.01057958,0.00000676663,0.000001229086,0.00004370638,0.00007102078,0.00001350996,0.003702165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5358746,"threshold_uncertainty_score":0.9228477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479435753709347,"score_gpt":0.2302279515560956,"score_spread":0.2154335940190021,"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."}}