The ongoing electrification of the Dutch energy system, driven by ambitious 2050 climate targets, is causing increasing congestion in medium- and low-voltage electricity networks. A key challenge lies in the mismatch between rapidly increasing renewable electricity generation and the limited capacity of the grid infrastructure. This imbalance not only delays the energy transition but also obstructs economic growth, as businesses and consumers struggle to connect new renewable projects to the grid. Residential Battery Energy Storage Systems (R-BESS) are considered a key flexibility solution to mitigate this problem. However, if operated purely for market profit, especially through arbitrage and participation in the imbalance market, R-BESS can unintentionally exacerbate grid congestion. This thesis investigates how congestion-neutral operation of R-BESS can be implemented to ensure their contribution to a stable and resilient grid. This thesis investigates how the concept of congestion-neutral operation, a relatively new design approach that aims to prevent residential batteries from contributing to peak grid load, can be applied to the integration of R-BESS. While R-BESS are often deployed to maximize economic returns through market participation, this research focuses on the impact of this implementation and investigates operational strategies that explicitly avoid increasing grid congestion. The central research question addressed is: How can congestion-neutral R-BESS be integrated into Dutch electricity networks to mitigate net congestion while balancing techno-economic trade-offs? A mixed-method approach was applied. The qualitative phase involved literature review and interviews with involved actors (distribution system operators, aggregators, and policy advisors) to identify key technical and institutional design elements for congestion-neutral R-BESS. The quantitative phase implemented a Mixed-Integer Linear Programming model in PyPSA to simulate R-BESS behavior at aggregator level under various market scenarios. The model was applied to a real Dutch medium-voltage substation (MSR), with scenario analyses for 2024 and 2030, supported by sensitivity and robustness testing on weather variability and system parameters. Results show that uncoordinated R-BESS operation substantially increases congestion, particularly in the imbalance market. The outcomes are summarized in Table 1. Congestion-neutral strategies, in particular time constraints, significantly reduced negative grid impacts. For example, applying time constraints reduced new congestion events by half for day-ahead and imbalance 2024 scenarios. However, mitigation periods also decreased with more than 25% for both scenarios. In addition, time-constraint operation preserved economic viability in the day-ahead market: total system costs increased by only 0.9% (2024) and 1.3% (2030), when combining battery trading with self-consumption (”value stacking”). However, for the imbalance market, total system costs increased by 3.47% and 5.09% under time-constraint operation. The study highlights key trade-offs between grid impact and business model profitability. It also identifies limitations, including single-node focus and perfect foresight assumptions.
Practical recommendations include enabling congestion-neutral R-BESS through flexible constraints, distinguishing day-ahead and imbalance market, and clear coordination between DSOs and aggregators. Future research should extend to multinode grids, explore dynamic real-time signals, and further integrate market design for congestion-neutral flexibility services. All results of this thesis are open source. The complete model developed for this research is publicly available at: https://github.com/Tanneheemsbergen/pypsa-NL2025