{"id":"W4414308733","doi":"10.1115/es2025-156635","title":"The Economic Dispatch of Power-to-Gas Systems With Deep Reinforcement Learning: Tackling the Challenge of Delayed Rewards With Long-Term Energy Storage","year":2025,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Siemens (Canada); McGill University","funders":"","keywords":"Economic dispatch; Electricity; Energy storage; Renewable energy; Reinforcement learning; Electric power system; Wind power; Energy (signal processing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001494642,0.0006380834,0.0007015136,0.0002729362,0.0003435169,0.00102446,0.0007572875,0.000917404,0.001636847],"category_scores_gemma":[0.00497795,0.0003475778,0.000348035,0.0002311758,0.0007102655,0.001257674,0.0008224012,0.001773534,0.0001352922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166591,"about_ca_system_score_gemma":0.001315683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01246474,"about_ca_topic_score_gemma":0.008594228,"domain_scores_codex":[0.9996669,0.0001562128,0.00001445426,0.00004640254,0.00004845177,0.00006757637],"domain_scores_gemma":[0.9970843,0.002185522,0.0002531973,0.00008121016,0.0002232056,0.0001725311],"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":[0.00004392526,0.00002397872,0.0006632102,0.00001330542,0.00000867293,0.00003142324,0.00000839221,0.9947136,0.0001566555,0.001647981,0.0001537308,0.00253505],"study_design_scores_gemma":[0.000003119093,0.00000714813,0.0000680482,0.000001192718,9.552871e-7,0.000001259667,0.000002924302,0.9992125,0.00004760622,0.0006232312,0.00003077513,0.000001154974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6456324,0.0005875654,0.3423726,0.002096291,0.0001506856,0.0001040151,0.0001692125,0.0003431909,0.008544107],"genre_scores_gemma":[0.9935068,0.00004834328,0.005926584,0.00004542336,0.00001050858,0.00001364632,0.00002327436,0.000009301563,0.0004162133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01246474,"threshold_uncertainty_score":0.02478439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004022554718895172,"score_gpt":0.1901014028071644,"score_spread":0.1860788480882693,"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."}}