Frances McGinley, A&I Summer Intern at ORE Catapult

Behind the scenes of ORE Catapult’s Analysis and Insights team

Published 25 August 2023

This blog was written by Frances McGinley, who joined ORE Catapult for the summer as the Analysis and Insights intern. Here, she explains how the Analysis and Insights department works at ORE Catapult and the experience she gained as part of the team:

For the past six weeks, I have been working in the Analysis and Insights team at the Offshore Renewable Energy (ORE) Catapult. The team contributes to the organisation’s mission by producing industry-leading insight pieces and thought leadership, as well as working with companies to show them the commercial opportunities for their technology. The thought leadership pieces produced by the team can inform key industry players and aid emerging offshore renewable energy technologies. To construct these innovative analysis pieces, the Analysis and Insights (A&I) team relies heavily on an up-to-date Offshore Wind Cost Model and accurate market data, something that I learnt first-hand as part of my internship.


Offshore Wind Cost Model

I started my internship by learning about one of the two pillars of the A&I team’s work – their Offshore Wind Cost Model. This model takes a bottom-up approach to modelling the costs of an offshore wind installation throughout its lifetime. Not only is this model used to carry out techno-economic analysis on client innovations, but it is also used to support a lot of the team’s insight pieces on more general industry points. The cost model’s main output is the Levelised Cost of Energy (LCoE), a metric used to compare the costs of electricity production across different projects. The LCoE can be thought of as the average total cost of building and operating a wind farm per unit of total electricity generated over an assumed lifetime. To calculate the LCoE, the lifetime costs of the project are divided by the sum of the electricity produced over the project’s lifetime:

Levelised Cost of Energy equation

During my time with the A&I team, my learning was focused on the lifetime costs of offshore wind projects, and I was shown how these costs were estimated for real projects. The lifetime costs are then divided into development (DEVEX), capital (CAPEX), operational (OPEX) and decommissioning (DECEX) expenditures. Once these are calculated, they can be inputted into a cash flow forecasting model and discounted to give LcoE.

Development Expenditure (DEVEX)

The first phase of any offshore wind project is development. During this phase, wind farm developers must carry out several activities to secure planning consent. These activities include a wide range of environmental, geological and hydrographical surveys. I had the opportunity to focus on one type of geological survey that developers are required to carry out: the geophysical survey.

As part of my degree in Physics, I had experience modelling various physical phenomena, but this type of cost modelling was different to my previous experiences. The main difference was the level of uncertainty. The nature of client work in an industry filled with proprietary intellectual property meant that I was faced with many ill-defined variables. The dynamic and fast-growing nature of the modern offshore wind sector means that the A&I team do a lot of work keeping their market data up to date. Costs that were needed to model the geophysical survey often had to be updated as we went and were taken as market averages due to a lack of precise cost estimates. This affected the accuracy and validity of the obtained results.

During my time within the A&I team, I was able to assist in the techno-economic analysis of a client’s innovation, where we identified whether there was potentially significant savings on both time and surveying costs by making it possible to automate part of the survey. This involved modelling the current costs of a geophysical survey, as well as the less well-defined costs of the survey under the implementation of the client’s technology. From the client’s perspective, we remained relatively pessimistic in many of our assumptions and were still able to confirm the innovation’s cost-saving ability. Thanks to the team’s work to keep the model costs updated, the estimated DEVEX expenditure attributable to the geophysical survey was still valid, despite a large margin of error, and our analysis proved to be very valuable to the client.

Capital Expenditure (CAPEX)

An offshore wind project’s capital expenditure covers everything from the substation, anchors, and mooring lines to the turbine tower, nacelle and blade costs. These expenditure costs vary, not only depending on turbine capacity, site conditions and design, but also on different manufacturers and resource availability. In the team’s cost model, these costs are often estimated using approximated data from previous projects with similar characteristics. I spent a couple of days updating this CAPEX data by comparing information taken from various wind farm databases. I was tasked with combing through sheets of CAPEX data from the databases and pulling out values that were suitable for comparison. This often involved discovering hidden patterns in the data. My internship exposed me to the big discussions on the quality of cost data within the industry, and just how difficult it is to get accurate cost data from developers and manufacturers.

Operational Expenditure (OPEX)

All costs associated with the operations and maintenance of a wind farm fall under operational expenditure. In my learning about OPEX, I also experienced part of the research that the team carries out to conceive thought leadership pieces. These insight pieces are used to inform policymakers, manufacturers and other industry players. I worked on building a forecast model for the vessels involved in offshore wind farm operations and maintenance. As I was further along in my internship, I was able to contribute more to this model and draw similarities between the construction of this model and the much larger cost model. We once again relied on the data from the ORE Catapult’s databases, but this time looking at wind farm distances from shore and the current fleet of maintenance vessels in action. Assuming a vessel’s lifetime, we were able to forecast future vessel demand and the number of new builds that would be required to meet this demand. In future, this model can be adapted to work for different technology scenarios; for example, if automated maintenance technologies become more widespread, this model can be used to calculate the reduced vessel demand. Projections like this are very important to stakeholders, such as the UK Shipbuilders Association, as they can help companies understand the market value and project pipeline.

Market Data

The second pillar of the A&I team’s work is sourcing up-to-date market data, as the team uses this to inform industry, update the cost model, and to carry out client work. Although I was only scraping the surface of the team’s market analysis data, I spent some time interacting with it when I was tasked with updating global offshore wind energy targets. For clean growth strategies, many countries around the world have set targets for offshore wind energy generation for the coming decades. The UK, for example, aims to be generating 50GW of offshore wind energy by 2030. The ORE Catapult analysts take in-depths look into the ongoing and planned projects and make predictions about whether these targets will be reached. In contrast to the granular cost comparison work I had done when looking at the cost model inputs, my time looking into global targets gave me a more holistic understanding of the industry.


Schematic outline of how A&I team functions

Figure 1: A schematic outline of how ORE Catapult’s Analysis and Insights team functions.

Figure 1 shows the overhead structure of the team and summarises how the various components of my internship linked together. As you can see, the Offshore Wind Cost Model and the market data work in parallel to facilitate the A&I team at ORE Catapult. The cost model and market data provide key information that feeds into the client work and the thought leadership pieces generated. As part of my time with the team, I was able to study the cost model inputs in detail. Working with clients allowed me to see the impact of the work by the team at ORE Catapult, and I conducted research that will aid in the production of future insight pieces for industry players.

I chose to do an industry placement to help inform my future career decisions and explore opportunities outside of academia. I was looking for an experience where my work was more application-focused, rather than theoretical. Moreover, as someone deeply concerned about the climate, the chance to make my mark in the renewables sector was perfect. My time at ORE Catapult did all that and has left me feeling more informed. I feel more prepared to decide on a future career direction. Although I enjoyed my internship immensely and would be interested in working in the offshore wind sector, I will ultimately seek a more technical and possibly physics-related role.

“I’d like to thank everyone at ORE Catapult, particularly the A&I team, for making my internship such an enjoyable experience. Everyone went out of their way to make me feel welcome and made sure I felt comfortable asking for help; a lot of time was spent explaining acronyms. The team’s accommodating attitude and insightful discussions taught me a lot, and I’m incredibly grateful to have had this experience.”

Frances McGinley joined ORE Catapult for the summer of 2023 as the Analysis and Insights intern. She completed her internship in July and with the application-focused experience she has gained, she plans to seek a technical and physics-related role within the renewables sector.