Energy Storage Systems in Electrical Distribution Grids : Analysis and implementations of use cases for service stacking

Abstract: This Ph.D. thesis investigates the possibility of using energy storage systems for multiple services by implementing service stacking, with special emphasis on congestion management in distribution grids. The shift towards increased shares of RES in combination with the ongoing electrification of society will create challenges in all parts of the power system. To ensure enough flexibility throughout the power system, energy storage should be part of the discussion as a crucial tool to support balancing and stability, but also to assist in or solve local and regional challenges. One important step in the development of energy storage integration is the forming of more complex business models where multiple services are provided using the same storage unit and is known as service stacking. This increases the availability of the storage capacity towards the power system where value could be generated on both local, regional and system levels. Although, one of the main barriers of energy storage investments have been the high investment and operational costs. By implementing service stacking, the chance of creating a lucrative business case increases and should be considered in all contexts of energy storage implementations.The targeted research questions focus on mapping the current state of service stacking implementations globally, comparing different methods for implementing scheduling optimization tools, and evaluation of the technical and economic performance for different service portfolios. According to the trends in the results of the appended papers, energy storage systems have the potential to stack services both as large-scale centralized units as well as small-scale distributed units and can be applied to all storage technologies. The higher degree of utilization of the storage units will result in increased degradation due to cycle aging, but the magnitude of this increase strongly depends on the service portfolio composition and allowed cycle intensity. Future work could focus on multi-objective optimization, extended service portfolios, and scheduling over several time scales to include seasonal storage and intraday trading.