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We introduce a new approach for decoupling trends (drift) and changepoints (shifts) in time series. Our locally adaptive model-based approach for robustly decoupling combines Bayesian trend filtering and machine learning based regularization. An over

Externí odkaz: http://arxiv.org/abs/2201.06606

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Role of Variable Renewable Energy Penetration on Electricity Price and its Volatility Across Independent System Operators in the United States

Autor: Owolabi, Olukunle O., Schafer, Toryn L. J., Smits, Georgia E., Sengupta, Sanhita, Ryan, Sean E., Wang, Lan, Matteson, David S., Sherman, Mila Getmansky, Sunter, Deborah A.

The U.S. electrical grid has undergone substantial transformation with increased penetration of wind and solar -- forms of variable renewable energy (VRE). Despite the benefits of VRE for decarbonization, it has garnered some controversy for inducing

Externí odkaz: http://arxiv.org/abs/2112.11338

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