Risk-Aware Stochastic Optimization for Battery Energy Arbitrage Dispatch Planning

Abstract

This paper presents a risk-aware stochastic optimization framework for dispatch planning of Battery Energy Storage Systems (BESS) in volatile market conditions. By integrating quantile-based price forecasting with a stochastic optimization approach, the proposed model effectively captures market uncertainties and incorporates user-defined risk preferences. Simulation results demonstrate the framework’s ability to optimize dispatch schedules under varying risk scenarios, balancing profitability and risk mitigation. The findings provide actionable insights for flexibility service providers, enabling efficient and profitable energy arbitrage while managing exposure to adverse market conditions.

Authors 6

1. Sreejith P. Sajeev Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Institute for Automation of Complex Power Systems,Aachen,Germany

2. L. E. Roth Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Institute for Automation of Complex Power Systems,Aachen,Germany

3. Tripti Gangwar

   Siemens Energy

   Affiliation as printed

   Siemens Energy India Ltd.,BESS Digital Solutions, STO,Gurugram,India

4. James Amankwah Adu
   Affiliation as printed

   SEN Siemens Energy,GT, STO, E&D,Erlangen,Germany

5. Ilia Alexander Sakowski
   Affiliation as printed

   SEN Siemens Energy,GT, STO, E&D,Erlangen,Germany

6. Antonello Monti Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Institute for Automation of Complex Power Systems,Aachen,Germany