{"id":"W2113369277","doi":"10.1109/tpwrs.2010.2045663","title":"Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Electric Power System Optimization","field":"Engineering","cited_by":466,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Wind power; Sizing; Installation; Energy storage; Distributed generation; Reliability engineering; Electricity; Computer science; Environmental economics; Renewable energy; Environmental science; Engineering; Electrical engineering; Power (physics); Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002771719,0.0002172593,0.0003793951,0.0003196856,0.00003767961,0.00003386389,0.0001458476,0.000228136,0.000009857367],"category_scores_gemma":[0.000003885882,0.0002122505,0.00005020659,0.0007225751,0.00003953914,0.0002835596,5.122767e-7,0.0002258892,0.000003035911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001489224,"about_ca_system_score_gemma":0.00006466488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0011274,"about_ca_topic_score_gemma":0.0002582259,"domain_scores_codex":[0.9983683,0.00008541675,0.0007154312,0.0002285494,0.0003763655,0.0002259421],"domain_scores_gemma":[0.9990755,0.00007087838,0.0002004391,0.0003754904,0.0002159236,0.00006176972],"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":[0.00005136585,0.0001142673,0.00007721996,0.0002023699,0.00006275593,0.000001614624,0.0001910923,0.9703149,0.02770232,0.001190054,0.00003200688,0.00006006411],"study_design_scores_gemma":[0.0016963,0.0006122477,0.00120486,0.000646664,0.00008773122,0.00008998542,0.0003418793,0.8419707,0.1525266,0.000003146141,0.0002876801,0.0005321313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2443034,0.00007790975,0.7530265,0.00000512005,0.001761477,0.0003668217,0.0000742331,0.00009157395,0.0002929484],"genre_scores_gemma":[0.9995123,0.0000189707,0.0001775537,9.294419e-7,0.00001549701,0.00009831436,0.00004981226,0.0000431508,0.00008343215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.755209,"threshold_uncertainty_score":0.8655323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003358343786777668,"score_gpt":0.1751567484709851,"score_spread":0.1717984046842075,"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."}}