{"id":"W2735093141","doi":"10.1109/tsg.2017.2724919","title":"Long-Term Scheduling of Battery Storage Systems in Energy and Regulation Markets Considering Battery’s Lifespan","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Battery (electricity); Limiting; Scheduling (production processes); Frequency regulation; Battery storage; Energy storage; Computer science; Term (time); Mathematical optimization; Engineering; Control theory (sociology); Reliability engineering; Electric power system; Control (management); Power (physics); Operations management; Mathematics","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":[0.0001466274,0.0001603761,0.0002412318,0.0002115958,0.0001488217,0.0001001618,0.00009632856,0.0001026524,0.00002893345],"category_scores_gemma":[0.000004867325,0.0001790047,0.00004763754,0.00005399244,0.00004654847,0.0003227604,0.000001901,0.0001223578,0.000002490742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004594235,"about_ca_system_score_gemma":0.00001398826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009769767,"about_ca_topic_score_gemma":0.0002225397,"domain_scores_codex":[0.9991656,0.00003866406,0.0003141373,0.0001881535,0.0001109712,0.0001824659],"domain_scores_gemma":[0.9994237,0.000064309,0.00008549684,0.0003312464,0.00003642118,0.00005885702],"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":[0.00004155602,0.00002589656,0.00358966,0.0001523037,0.00005068955,0.000008688994,0.00007089641,0.9813851,0.006301397,0.000005040293,0.00003741364,0.0083314],"study_design_scores_gemma":[0.001264543,0.00003381646,0.08478195,0.0004816932,0.00005062061,0.00002788383,0.00002182592,0.9004316,0.01228988,0.000005554877,0.0002888335,0.0003218328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4763585,0.0006273896,0.52079,0.00005261123,0.001820049,0.0001329888,0.00002100072,0.00008006552,0.0001174098],"genre_scores_gemma":[0.9986554,0.0008191175,0.0002814683,0.00001640937,0.0001112863,0.00002949676,0.000005325155,0.00003104613,0.00005045558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5222968,"threshold_uncertainty_score":0.7299598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107087610160793,"score_gpt":0.204598415490034,"score_spread":0.1935275393884261,"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."}}