{"id":"W3000230823","doi":"10.1109/oajpe.2019.2952811","title":"Optimal Scheduling of Merchant-Owned Energy Storage Systems With Multiple Ancillary Services","year":2020,"lang":"en","type":"article","venue":"IEEE Open Access Journal of Power and Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Energy storage; Profit (economics); Grid; Scheduling (production processes); Electric power system; Computer science; Reliability engineering; Linear programming; Automotive engineering; Operations research; Engineering; Operations management; Power (physics); Economics","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":[0.0007870519,0.0007788764,0.0009665853,0.0003254054,0.0004163232,0.001037822,0.0008053427,0.0006957677,0.003086769],"category_scores_gemma":[0.001056795,0.0006008487,0.000500441,0.0004769255,0.0004792422,0.0007793037,0.0005221686,0.0007033428,0.0001945262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456643,"about_ca_system_score_gemma":0.00170268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01210342,"about_ca_topic_score_gemma":0.01510006,"domain_scores_codex":[0.9996898,0.0001218964,0.00001164696,0.0000504072,0.00004503858,0.00008114833],"domain_scores_gemma":[0.9995611,0.0002162153,0.00007517802,0.00001809585,0.00006327057,0.00006612998],"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":[0.00005731249,0.00002016468,0.0001841252,0.00002173019,0.000009434289,0.00004441044,0.00001348845,0.9942324,0.0004254842,0.001825882,0.00022513,0.002940537],"study_design_scores_gemma":[0.000009776714,0.00003546774,0.0001142156,0.00000235787,0.000004639988,0.000005570493,0.0000158793,0.998486,0.0002136882,0.0009179352,0.0001915606,0.000002881238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3544122,0.0007682352,0.6172209,0.0007071644,0.000149029,0.0004142502,0.0005716708,0.0002823118,0.02547422],"genre_scores_gemma":[0.9801928,0.0001507656,0.01612675,0.00002167374,0.00001539028,0.00006150625,0.00007821121,0.0000283242,0.003324462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01210342,"threshold_uncertainty_score":0.02406591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01537146525233533,"score_gpt":0.2380095088033461,"score_spread":0.2226380435510107,"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."}}