The transition to a low carbon energy system is focusing attention on the synergies between large scale offshore wind and green hydrogen production. These synergies can have system-wide benefits for the integration of wind farms to the power system, whilst improving their economic performance. Offshore wind investments face multiple uncertainties: commodity prices fluctuate and impact turbine cost, vessel rates required to install the turbines are dynamic and the electricity price fluctuates daily. Additionally, to realize wind-hydrogen synergies (hybrid powerplants) the electrolyzer is an additional source of cost uncertainty. On the contrary, the revenue uncertainty of the wind farm is expected to be mitigated through the use of Hydrogen Purchase Agreements. To take informed investment decisions regarding wind-hydrogen synergies, Vattenfall, a leading European utility, is interested in analyzing the trade-off between increased cost uncertainty and reduced revenue uncertainty.

This thesis investigates how integrating a 400 MW onshore electrolyzer with a 2 GW bottom-fixed wind farm affects the project’s economic uncertainty. To answer the question, a three-step methodology is applied. Firstly, the economics of the offshore wind farm and hybrid powerplant are modelled without the presence of uncertainty, using Vattenfall’s techno-economic model. This model considers investment and operation costs, along with the revenues of the wind farm from electricity sales on the power market. For the revenues of the hybrid powerplant, an optimization algorithm deciding when it is optimal to produce hydrogen or electricity is employed. Secondly, the uncertainties in key commodities (steel, aluminum, copper and shipping fuel oil), vessel day-rates, electricity prices and electrolyzer costs, are defined. Thirdly, the uncertainties are sampled through a Monte Carlo simulation to create 10,000 different realizations of the project, covering the entire range of possible outcomes. By combining the techno-economic model, the dispatch algorithm and the Monte Carlo approach, the uncertainties of the offshore farm and hybrid powerplant can be quantified, and their impact on the project economics can be evaluated.

The methodology allows to compare the effect of hydrogen integration in the business case uncertainty of an offshore wind farm. On a deterministic comparison, the two projects perform similarly. For the considered wind farm, the inclusion of the electrolyzer adds an additional e94 M
in cost uncertainty, while it reduces revenue uncertainty by e18 M. These results hold true for the considered offshore farm, given projected conditions and modelling assumptions. For this case, the offshore wind farm is marginally more certain in terms of economic returns. Given the two projects produce similar investment returns, accepting the increased uncertainty of the hybrid powerplant is non-economical.

The results of the thesis do not favor an investment in hybrid project in terms of uncertainties. However, this result is true for the project investigated and as conditions change and hydrogen technology matures, the analysis can shift in favor of hydrogen. Specifically, hydrogen is a large
scale infrastructure with the first full scale projects currently under development. With more project-experience gained, the uncertainty in costs can be reduced, favoring the hybrid projects. With increased support for large scale hydrogen production, the proposed framework for continuous analysis can be leveraged to keep pace with the external macroeconomic changes. The methodology can be extended and applied to other hybrid solutions, such as hybrid projects with batteries.