Battery Sizing for PV-based Hybrid Parks in the Netherlands

A Multi-Stage Stochastic Optimisation Approach

Master Thesis (2025)
Author(s)

E.M. van der Pouw (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Simon Tindemans – Mentor (TU Delft - Intelligent Electrical Power Grids)

K. Bruninx – Graduation committee member (TU Delft - Energy and Industry)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
27-06-2025
Awarding Institution
Delft University of Technology
Programme
['Electrical Engineering | Sustainable Energy Technology']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

As grid congestion continues to limit the expansion of renewable energy in the Netherlands, co-locating battery storage systems with existing PV farms is gaining attention as a practical and cost-effective solution. These hybrid parks make better use of existing grid connections and enhance system flexibility. However, the capital intensity of batteries, combined with grid constraints and associated fees, makes it challenging to determine the optimal battery size within a hybrid park.

The aim of this thesis is to determine the optimal battery size for a co-located PV and storage system behind a shared grid connection, referred to as a hybrid park, in a computationally efficient manner. A multi-stage stochastic optimisation model is developed to maximise the Net Present Value of the hybrid park. The model includes participation on the Day-Ahead, Frequency Containment Reserve and Intraday markets. To manage complexity, representative days are carefully selected using k-medoids clustering and uncertainty in solar generation and Intraday prices is introduced through scenario sampling.

Results show that the hybrid park improves financial performance compared to stand-alone configurations. This advantage is primarily driven by cost savings from shared infrastructure and reduced grid fees. Battery sizing is strongly influenced by the choice of market participation, the presence of grid fees and the level of uncertainty included in the model. FCR participation is the main driver for the required power capacity, while energy capacity is primarily shaped by participation in the Intraday market. Including uncertainty in solar generation and Intraday prices typically leads to larger energy capacity, enabling the battery to respond more effectively to variability. Grid fees, modelled as peak offtake charges, have a notable impact by discouraging high grid offtake and reducing the need for large offtake grid connections. Allowing combinations of multiple C-rates adds design flexibility but also increases model complexity, which can affect convergence and runtime.

In conclusion, this study shows that optimal sizing depends on the strategy of the hybrid park, including market participation and regulatory context. The developed model provides a practical tool for optimising battery size within a reasonable computation time. Future research could focus on improving the representation of uncertainty and market dynamics to better reflect real-world operation and enable more robust sizing decisions.

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