{"id":"W4309213926","doi":"10.3390/en15228525","title":"Microgrid Energy Management and Methods for Managing Forecast Uncertainties","year":2022,"lang":"en","type":"article","venue":"Energies","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Renewable energy; Microgrid; Environmental economics; Electricity generation; Energy management; Fossil fuel; Intermittent energy source; Energy storage; Electricity; Energy engineering; Distributed generation; Environmental science; Engineering; Energy (signal processing); Economics; Power (physics); Waste management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000740095,0.001054589,0.000783802,0.0008023041,0.0004750347,0.001384279,0.001012752,0.0005542369,0.002213196],"category_scores_gemma":[0.001323648,0.0003169777,0.0005731775,0.0009941999,0.0003638623,0.001234115,0.0009650132,0.0007859569,0.0003552499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005403725,"about_ca_system_score_gemma":0.0006746809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00303767,"about_ca_topic_score_gemma":0.003365819,"domain_scores_codex":[0.9996684,0.00008450812,0.00003299235,0.00006051302,0.0001285714,0.00002499664],"domain_scores_gemma":[0.999621,0.0001587739,0.0000660506,0.00004144473,0.0001022472,0.00001045128],"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":[0.0000605266,0.00004436878,0.0007636565,0.0005771142,0.0001184765,0.0001196615,0.0001637775,0.6338944,0.003168791,0.0349994,0.00306962,0.3230202],"study_design_scores_gemma":[0.00001086657,0.00004761496,0.0004198757,0.00008629975,0.00003127985,0.00007896844,0.00007385722,0.9694898,0.001780677,0.01806895,0.009889647,0.00002224565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004686614,0.003915629,0.9821299,0.0002633574,0.0001031458,0.00008658408,0.00009210983,0.0003293092,0.00839331],"genre_scores_gemma":[0.6902362,0.01088563,0.2882245,0.0001631029,0.0004462234,0.0003743388,0.0003214489,0.0001300346,0.00921851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00303767,"threshold_uncertainty_score":0.00740391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005546610083607112,"score_gpt":0.2226927517524799,"score_spread":0.2171461416688727,"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."}}