{"id":"W3132337940","doi":"10.1016/j.ijepes.2020.106731","title":"Demand response integrated day-ahead energy management strategy for remote off-grid hybrid renewable energy systems","year":2021,"lang":"en","type":"article","venue":"International Journal of Electrical Power & Energy Systems","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Renewable energy; Demand response; Energy management; Intermittent energy source; Environmental economics; Computer science; Electric power system; Energy management system; Smart grid; Peak demand; Grid; Energy storage; Incentive; Reliability engineering; Distributed generation; Engineering; Energy (signal processing); Power (physics); Electricity; Electrical engineering; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001178948,0.0005636491,0.0008542936,0.0009984259,0.00010362,0.0004858006,0.001063587,0.0002076055,0.00004493005],"category_scores_gemma":[0.0001760524,0.0005377557,0.0004375285,0.0006874876,0.00004434248,0.0003936646,0.0001358516,0.0002742503,0.000005213137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00127722,"about_ca_system_score_gemma":0.0002313837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001008524,"about_ca_topic_score_gemma":0.0001105122,"domain_scores_codex":[0.9949081,0.0005509651,0.001837709,0.0005339247,0.00139661,0.0007727028],"domain_scores_gemma":[0.9966446,0.0005175699,0.0005446598,0.0005155343,0.00141862,0.0003590881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007305361,0.0001444928,0.00001170762,0.00003491267,0.002297421,0.001711424,0.00001503161,0.8624418,0.002750679,0.01629768,0.1090555,0.004508769],"study_design_scores_gemma":[0.001395221,0.0002891558,0.00004080523,0.0003130621,0.0001055651,0.0009005623,0.00007815716,0.3442874,0.006258133,0.0003576598,0.6455376,0.0004367389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0032113,0.01859849,0.9486388,0.0002767694,0.01882031,0.0001491276,0.0000922629,0.0002308144,0.009982136],"genre_scores_gemma":[0.9812765,0.002682983,0.0005037917,0.0002306003,0.002141849,0.00005705563,0.0001547179,0.0001561373,0.01279635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9780652,"threshold_uncertainty_score":0.9997074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009909350893998614,"score_gpt":0.2283882867581326,"score_spread":0.218478935864134,"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."}}