Supercharging congestion management with battery Energy Storage

Abstract

The energy transition is gaining momentum in the Netherlands, but not without consequences. Due to energy grid congestion, developments are on hold as they cannot be connected to the energy grid due to limited capacity. The ACM has revised electricity grid regulations to optimize grid efficiency, which increased the risk of congestion during peak load. This can be mitigated by using congestion management and battery energy storage (BES) can be the solution by storing surplus energy during peak periods and releasing it during periods of sufficient grid capacity, presenting an opportunity for Statkraft.

This study analyses the effect of using battery energy storage systems for congestion management on the overall business case. The interactions between the battery and the energy markets is simulated using model predictive control. The business model of the battery consist of energy arbitrage and value stacking i.e. trading on multiple markets in order to generate revenue. This model uses real market data of four identified markets, aFRR, FCR, intraday and day ahead. The results of the BES simulation are used to build a business case for BES. The business case is comprised of a economic assessment, risk assessment and a sensitivity analysis. The business case for battery energy storage is positive and through research and modelling it can be concluded that the congestion management market is beneficial to the business case of the BES.

Keywords: battery energy storage (BES), congestion management, simulation, model predictive control (MPC), business case.