The Dutch electricity system is undergoing a rapid transformation driven by the increasing share of variable renewable energy sources like wind and solar power. This transition, coupled with the electrification of various sectors, is leading to growing imbalances between electricity supply and demand, challenging the stability of the grid. To maintain balance, the Transmission System Operator (TSO), TenneT, relies on balancing services such as the automatic Frequency Restoration Reserve (aFRR). Traditionally provided by conventional power plants, there is a growing need for new flexible resources like Battery Energy Storage Systems (BESS) to participate in these markets.

Currently, the business model for home battery aggregators like Zonneplan is based on "passive balancing," where batteries strategically take out-of-balance positions to profit from imbalance price fluctuations. However, the sudden widespread and simultaneous application of this strategy has led to unintended consequences, including system oscillations and a high frequency of "Regulation State 2" (RS2) quarters, where the system swings between shortage and surplus. This development not only complicates grid management for TenneT but also reduces the profitability of passive balancing for market participants.

In response, TenneT is working to make active participation in the aFRR market more attractive for fast-responding assets like batteries. This research addresses the critical question of whether a shift from passive balancing to active aFRR participation is financially viable for aggregators of home batteries, using Zonneplan as a case study.

This thesis compares the performance of Zonneplan's passive balancing strategy with three simulated aFRR bidding strategies. The research is guided by the following main research question: How does the performance of aFRR bidding strategies compare to Zonneplan’s currently used passive balancing strategy?

To answer this, the study is structured around three sub-questions:

1. How does the currently used passive balancing strategy of Zonneplan work and how does it perform under the growing frequency of Regulation State 2 ISPs?

2. What are the current trends in the aFRR bidding ladder, prices, and volumes?

3. What are possible bidding strategies for Zonneplan to participate in the Dutch aFRR market and how do they perform?

To answer these research questions, the study applies a mixed-methods approach combining qualitative case analysis, quantitative data analysis, and simulation modeling. Zonneplan's passive balancing strategy was examined through internal documentation and discussions with employees. A backcast of the period January 2024–March 2025 was used to analyze the passive balancing strategy performance using Python, while considering Ex-Post trading and both internal and external portfolio advantages. The aFRR market analysis drew on publicly available TenneT datasets to identify trends in prices, volumes, and bidding ladder. Finally, three aFRR bidding strategies were simulated using a custom-built Python model that replicates bidding, activation, and financial settlement processes at one-minute resolution, enabling a robust comparison with Zonneplan’s passive balancing strategy. The model incorporates real-world constraints such as bid timing and state-of-charge limitations.

The analysis of Zonneplan's passive balancing backcast data from January 2024 to March 2025 reveals that while the strategy initially showed growing revenue, its revenue has been declining since August 2024. This is mainly due to increasing charging costs and partly due to the increased frequency of RS2, which, despite price risk mitigation through Ex-Post trading and Portfolio advantages, limits revenue opportunities.

The aFRR market analysis identifies key trends, including the impact of the European PICASSO platform, which has led to higher activation volumes. While extreme price peaks for upward regulation have become less frequent, average prices remain attractive. A clear daily pattern in aFRR prices, often correlated with Day-Ahead market prices, presents opportunities for dynamic bidding.

Three aFRR bidding strategies were simulated: a constant bid strategy, a Day-Ahead price-based strategy, and an intraday price-based strategy. The Day-Ahead price-based strategy (Bid Strategy 2) yielded the highest net revenue, consistently outperforming the others.

The final comparison shows that the simulated aFRR bid strategy (Bid Strategy 2) consistently generates higher net revenue than the passive balancing strategy throughout the entire analysis period. The aFRR strategy achieves higher activation volumes and benefits from being able to capture revenue during RS2 periods, where passive balancing is ineffective. Furthermore, aFRR participation aligns directly with the TSO's need for system stability, offering a more robust and system-supportive business model.

The discussion highlights key limitations of this research, including limited data availability on passive balancing, simplifications in the bidding simulations, and the rapidly evolving nature of the aFRR market. It also outlines the main implications for the broader context and key stakeholders. For home battery aggregators, the findings demonstrate a clear financial incentive to transition from passive balancing to active aFRR participation, offering not only more stable and higher revenues but also enabling batteries to contribute more effectively to grid stability. For TenneT, it is encouraging that there is a clear financial incentive for aggregators to shift from passive balancing to active aFRR participation. This shift is expected to reduce the frequency oscillations that are currently amplified by uncoordinated passive responses, while enabling batteries to actively support grid stability by following TenneT's aFRR setpoints, effectively using their fast response capabilities to prevent oscillations rather than cause them. Finally, for home battery owners, the study suggests that while passive balancing revenues are declining, participating in aFRR through aggregators can maintain a reasonable payback period.

The research concludes with several suggestions for future work. Future studies should examine how an aFRR-focused strategy can be integrated into broader multi-market value stacking approaches, including intraday arbitrage and selective passive balancing, to reduce revenue volatility and improve overall profitability. More detailed econometric and scenario-based analyses are also needed to better understand aFRR market dynamics, especially in light of regulatory changes and increasing cross-border integration via PICASSO. As battery participation grows, future research should explore potential market saturation effects and their impact on price levels, activation frequency, and aggregator returns. Lastly, the gradual phase-out of gas-fired power plants from balancing markets introduces new uncertainties, warranting investigation into how this shift could affect price volatility, scarcity pricing, and the strategic positioning of new flexible assets like batteries.