A Standardised Comparison Model for Offshore Wind to Hydrogen Concepts
Through Industry Validation and Promotion of Widespread Adoption Towards Improved Stakeholder Cooperation in the Energy Transition
W.J.F. van den Haak (TU Delft - Civil Engineering & Geosciences)
M. Van Koningsveld – Mentor (TU Delft - Rivers, Ports, Waterways and Dredging Engineering)
P Taneja – Graduation committee member (TU Delft - Rivers, Ports, Waterways and Dredging Engineering)
George Lavidas – Graduation committee member (TU Delft - Offshore Engineering)
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Abstract
To facilitate the energy transition, effective collaboration among all stakeholders is necessary. However, there is currently a lack of understanding regarding the impact of different components in the value chain on the energy system's overall structure and the final energy price. This knowledge gap poses a significant obstacle to cooperation and progress in the energy transition. It creates the risk that effort goes into developing certain partial solutions when they may not be feasible from a larger system perspective. By focusing on their own component, stakeholders do not fully take into account the needs and interests of others involved. As the development of green hydrogen projects is in its early stages, it is important to think in terms of systems. Stakeholders should establish an ecosystem where players operating in different parts of the value chain are collaborating together. This helps to de-risk projects, share lessons and promote the development of innovative, first-mover initiatives.
This study aims to develop a standardised method to evaluate offshore wind to hydrogen concepts through a techno-economic analysis. This analysis method combines technical analysis with economic evaluation of projects and concepts to determine the potential economic outcomes and impacts of implementing a particular technology or project.
Through stakeholder interviews, the study found that stakeholders in the offshore wind and hydrogen market have distinct objectives and concerns. Key factors influencing their willingness to contribute include confidentiality, competition, and reputation.
To increase the transparency of the model, it was developed in Python. A standard notation system was developed, which was presented alongside the model's results. This should aid in the understanding of the underlying assumptions.