{"id":"W3093502878","doi":"10.1016/j.ijepes.2020.106561","title":"Optimal planning and investment benefit analysis of shared energy storage for electricity retailers","year":2020,"lang":"en","type":"article","venue":"International Journal of Electrical Power & Energy Systems","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canada School of Energy and Environment","keywords":"Energy storage; Investment (military); Electricity; Environmental economics; Investment analysis; Business; Electricity market; Energy (signal processing); Electricity retailing; Computer science; Operations research; Industrial organization; Economics; Electrical engineering; Finance; Engineering; Power (physics); Financial risk; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001285776,0.0008043828,0.001682838,0.0007009315,0.000514044,0.002126929,0.001067464,0.001362827,0.007268384],"category_scores_gemma":[0.003459805,0.001403001,0.0008139597,0.001000758,0.0009673606,0.001978332,0.0009704993,0.001337961,0.000241073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003247252,"about_ca_system_score_gemma":0.003146196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0265517,"about_ca_topic_score_gemma":0.02904631,"domain_scores_codex":[0.999448,0.0002564755,0.00001633624,0.00006980066,0.00008046688,0.0001289728],"domain_scores_gemma":[0.9981876,0.00137976,0.00009416147,0.00005706189,0.000172797,0.0001086071],"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":[0.00009812387,0.00002486249,0.0002227186,0.00002316062,0.00001362031,0.00004098291,0.00001216001,0.9939157,0.0001450658,0.003536175,0.0003017342,0.00166567],"study_design_scores_gemma":[0.00001458409,0.00003010221,0.0001775627,0.000004467745,0.00001242891,0.000005392528,0.00003542787,0.9964689,0.0001187321,0.002997268,0.0001306789,0.000004491969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6789169,0.001714334,0.2556823,0.002803896,0.0001690074,0.0004962343,0.001802729,0.0003935755,0.05802111],"genre_scores_gemma":[0.991747,0.0001236731,0.004827183,0.00002760484,0.00001102467,0.00003730983,0.000100217,0.00002413657,0.003101909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0265517,"threshold_uncertainty_score":0.05279428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415395892548893,"score_gpt":0.2263133826057527,"score_spread":0.2121594236802637,"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."}}