{"id":"W3117044811","doi":"10.1109/pesgm41954.2020.9281577","title":"Optimal Configuration of Energy Storage System Considering Uncertainty of Load and Wind Generation","year":2020,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Wind power; Computer science; Particle swarm optimization; Mathematical optimization; Electric power system; Energy storage; Simulated annealing; Power (physics); Engineering; Algorithm","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":[0.00005929807,0.00008184779,0.0001496502,0.00003053986,0.00001306735,0.000009908974,0.00003570481,0.00003339997,0.00002878184],"category_scores_gemma":[0.0000107466,0.00008356124,0.00001884855,0.00007253529,0.00002477786,0.00007597642,0.0000204214,0.00002457938,9.084246e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004689841,"about_ca_system_score_gemma":0.00001187199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007616739,"about_ca_topic_score_gemma":0.00002143619,"domain_scores_codex":[0.9994621,0.00001464868,0.0002249368,0.0001009952,0.0001240785,0.00007318388],"domain_scores_gemma":[0.9997725,0.00001606035,0.00003867526,0.00008578184,0.00004696285,0.00004002143],"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":[0.000004506835,0.000002203183,0.00003529437,0.0001549997,0.00003911031,0.000001756789,0.0001520394,0.9105943,0.0782266,0.01004041,0.0004877408,0.0002610154],"study_design_scores_gemma":[0.0002155764,0.00003106377,0.0001056191,0.0000155022,0.00001489838,0.000001170145,0.00023792,0.852379,0.1459379,9.979245e-7,0.0009878338,0.00007258051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.661966,0.0001836347,0.3305188,0.00005862113,0.000175136,0.00007205927,0.000003890167,0.0001314187,0.006890458],"genre_scores_gemma":[0.9985245,0.00001776011,0.001300479,0.00002442297,0.00008535024,0.000003125579,0.000009407073,0.00001138159,0.00002361534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3365585,"threshold_uncertainty_score":0.3407529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665053913672874,"score_gpt":0.1877563254694582,"score_spread":0.1711057863327294,"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."}}