{"id":"W2787636654","doi":"10.1109/pesgm.2017.8274023","title":"Investigation of Ontario's electricity market behaviour and energy storage scheduling in the market based on model predictive control","year":2017,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Electricity market; Energy storage; Arbitrage; Model predictive control; Electricity; Renewable energy; Profit (economics); Computer science; Scheduling (production processes); Software deployment; Operations research; Microeconomics; Business; Economics; Control (management); Engineering; Operations management; Finance; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005890784,0.0001307899,0.0001728218,0.0001336097,0.00008505665,0.00005515781,0.0001869259,0.0000944596,0.0000217393],"category_scores_gemma":[0.00009799841,0.000108128,0.00002542054,0.00008622957,0.0000275443,0.0001924942,0.000009158894,0.0001595823,1.211571e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002550146,"about_ca_system_score_gemma":0.0001118336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004255599,"about_ca_topic_score_gemma":0.007052389,"domain_scores_codex":[0.9991671,0.00009280065,0.0002200894,0.0001543047,0.0002006156,0.000165086],"domain_scores_gemma":[0.9993538,0.0001386475,0.0001004651,0.0003231181,0.00004590233,0.00003804528],"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":[0.00009113822,0.00001717317,0.06288463,0.00002094054,0.00001718781,0.000002328303,0.0003102668,0.9355018,0.0003401033,0.000220252,0.0004536751,0.0001404891],"study_design_scores_gemma":[0.0007197335,0.00006106435,0.1053074,0.00003598326,0.0000198554,0.000001037507,0.000008487281,0.8928472,0.0008098895,0.00009666673,0.000002681483,0.00008994968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3484081,0.00003402353,0.6177723,0.00007504676,0.00006680417,0.0002628281,0.00001040122,0.00006455175,0.03330589],"genre_scores_gemma":[0.9974033,0.000006098508,0.002156855,0.00007296044,0.000011846,0.0000436333,0.000003894111,0.0000159884,0.0002854115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6489952,"threshold_uncertainty_score":0.6433221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008131479506227236,"score_gpt":0.1872153250033361,"score_spread":0.1790838454971089,"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."}}