{"id":"W3188345843","doi":"10.11575/prism/36122","title":"Minimizing Demand Transmission Service Charges in Optimal Sizing and Scheduling Of Campus Microgrids","year":2019,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sizing; Scheduling (production processes); Service (business); Transmission (telecommunications); Operations research; Computer science; Engineering; Business; Operations management; Telecommunications; Marketing; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003831559,0.0004387769,0.0004263734,0.0002586192,0.0002824223,0.001004965,0.0003104012,0.000304735,0.00186125],"category_scores_gemma":[0.0008203353,0.0003036333,0.0002963564,0.0005146192,0.0002213001,0.0004575824,0.000398923,0.0004593895,0.0002039449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009181891,"about_ca_system_score_gemma":0.001720082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006299378,"about_ca_topic_score_gemma":0.008842653,"domain_scores_codex":[0.9998403,0.00006488746,0.000006278282,0.00002336846,0.00003354031,0.00003169799],"domain_scores_gemma":[0.9998919,0.00004927277,0.00001979832,0.00000787763,0.00001945355,0.00001174709],"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":[0.00003418057,0.00003111918,0.000345068,0.00004468526,0.00001005963,0.00002609993,0.00004345873,0.9650021,0.001819654,0.00719056,0.0003581055,0.02509481],"study_design_scores_gemma":[0.000008124412,0.00006295138,0.0003137667,0.000008450391,0.000008989561,0.00000983234,0.00009336702,0.9937761,0.001613484,0.002933437,0.001167411,0.000004107306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3818303,0.0006399485,0.5816888,0.0005432066,0.00005502141,0.0002295843,0.0001679314,0.0002582842,0.03458697],"genre_scores_gemma":[0.9310632,0.0004480061,0.06430306,0.00002064188,0.00001277794,0.00007190006,0.00005890066,0.00003942546,0.003982096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006299378,"threshold_uncertainty_score":0.01252544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349979192895065,"score_gpt":0.2530761061089705,"score_spread":0.2395763141800199,"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."}}