Colloquia

Summary

The transition to renewable energy has increased the integration of photovoltaic (PV) systems into the power grid, necessitating Battery Energy Storage Systems (BESS) to enhance stability and maximize revenue. This thesis explores the optimal sizing of a co-located BESS for merchant operation in the German electricity market, leveraging multiple revenue streams.

An optimization model, formulated as a Mixed-Integer Linear Programming (MILP) problem, determines the most profitable BESS configuration while considering battery degradation, investment costs, and market uncertainties. The study evaluates participation in the Day-Ahead (DA), Intraday (ID), and automatic Frequency Restoration Reserve (aFRR) markets, with a Monte Carlo Simulation (MCS) assessing market variability.

Results indicate that multi-market operation significantly improves revenue compared to standalone arbitrage. The Intraday market is the most profitable due to price volatility, while aFRR enhances economic resilience through diversified income. Optimal sizing strategies highlight trade-offs between energy and power capacity, depending on market priorities.