Research Papers
Research Papers

Research Papers

«Scientific articles in collaboration with research institutes and universities»
Cover Photo: Flaticon
 
🏡 Home | ✉️ Contact
 

 

SSRN - (Mar 2024)

Abstract

In this study, we introduce a conservative model designed to accurately predict renewable energy generation while addressing fluctuations and imbalances in power supply. We employ a time-inhomogeneous Vasicek model driven by both a skew Brownian motion and a compound Poisson process, providing proofs of solution existence, uniqueness, and mean reversion. Our focus is on minimizing deficits caused by underestimating actual generation levels. By prioritizing a positively skewed distribution of errors and aiming for errors to cluster around zero, we achieve significant reductions in forecasting errors compared to established benchmarks. Using hourly data from Terna in 2023, our model demonstrates the impact of energy imbalances, resulting in losses, but also showcases improved revenues and substantial CO2 savings.
Keywords: Skew Brownian motion, Electricity, Forecasting, Solar, Wind, Renewable Energy
JEL Classification: C53, Q41, Q54, Q5
Suggested Citation: dx.doi.org/10.2139/ssrn.4770859
 

Built with Potion.so