{"id":"W4392164686","doi":"10.1002/9781394167319.ch2","title":"Renewable Power Generation Price Prediction and Forecasting Using Machine Learning","year":2024,"lang":"en","type":"other","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity price forecasting; Renewable energy; Computer science; Predictive power; Machine learning; Econometrics; Economics; Artificial intelligence; Electricity price; Engineering; Electricity; Electrical engineering","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":[0.0005732269,0.0005921504,0.0007414811,0.001108388,0.000247706,0.0008036791,0.0005897959,0.0007020403,0.0009916155],"category_scores_gemma":[0.002866497,0.0003032017,0.0005134059,0.001611174,0.0001809746,0.0009828031,0.000289768,0.001094445,0.0006723295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005330614,"about_ca_system_score_gemma":0.0003553375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008706168,"about_ca_topic_score_gemma":0.005840426,"domain_scores_codex":[0.999705,0.00005422016,0.00002762421,0.00007471722,0.0001061286,0.00003217509],"domain_scores_gemma":[0.9993225,0.0003764811,0.00008339861,0.00006091352,0.0001386382,0.00001807096],"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":[0.00005430562,0.00008391877,0.004019554,0.0000531661,0.0000473793,0.00007137311,0.00001611196,0.805814,0.0008650511,0.001920716,0.001958072,0.1850964],"study_design_scores_gemma":[0.000001298205,0.000002963414,0.0003736211,0.000003165435,0.000001713399,0.000003979891,0.000001563356,0.9985261,0.0001514797,0.000770842,0.0001605945,0.000002663297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1410667,0.003528405,0.8415416,0.0008008611,0.0003545388,0.00009536287,0.0007903255,0.002875353,0.008946854],"genre_scores_gemma":[0.9216083,0.001473472,0.07323911,0.00009028591,0.0002180121,0.00006891147,0.0008249051,0.00005766913,0.002419273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008706168,"threshold_uncertainty_score":0.01731104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02324009514701816,"score_gpt":0.2079371687042764,"score_spread":0.1846970735572583,"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."}}