{"id":"W2889617750","doi":"10.3390/en11092381","title":"Optimal Scheduling of Microgrid with Distributed Power Based on Water Cycle Algorithm","year":2018,"lang":"en","type":"article","venue":"Energies","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Jiangxi Provincial Department of Science and Technology; Natural Science Foundation of Jiangxi Province; National Natural Science Foundation of China","keywords":"Microgrid; Mathematical optimization; Computer science; Operating cost; Distributed generation; Renewable energy; Convergence (economics); Scheduling (production processes); Algorithm; Engineering; Mathematics","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":[0.0004879918,0.0007462402,0.001031434,0.0006094281,0.0006033746,0.0008074229,0.0007583509,0.0005267085,0.001867265],"category_scores_gemma":[0.001017685,0.0003899526,0.0004442925,0.0008039905,0.0004626852,0.0006951847,0.0005363842,0.0004615031,0.0001457604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000928522,"about_ca_system_score_gemma":0.001770851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01442009,"about_ca_topic_score_gemma":0.01003475,"domain_scores_codex":[0.9997768,0.00006274493,0.00001170767,0.00005026598,0.0000505715,0.00004800019],"domain_scores_gemma":[0.9997225,0.0001256205,0.00003813077,0.00001524657,0.00007116066,0.00002733003],"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":[0.0000380701,0.00002082984,0.0002727415,0.00002681071,0.00001301637,0.00002032242,0.00002293532,0.981292,0.0005635635,0.002643075,0.0003740925,0.0147126],"study_design_scores_gemma":[0.000008465813,0.0000125536,0.0000356987,0.000001108529,0.000002225644,0.000002275019,0.000004289951,0.9989367,0.0001176568,0.0007454582,0.0001321624,0.000001448004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09326669,0.0004454401,0.8987204,0.0002137474,0.00007213477,0.0001244622,0.00008360282,0.000410067,0.006663507],"genre_scores_gemma":[0.9002696,0.0002212344,0.09667289,0.00004272372,0.0000206808,0.0001604048,0.000120972,0.00005109534,0.002440315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01442009,"threshold_uncertainty_score":0.02867234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002187710904616886,"score_gpt":0.1670814573272079,"score_spread":0.164893746422591,"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."}}