Exploring the Winds of Change: A Multiple Correspondence Analysis of Offshore Wind Market Attractiveness with a specific focus on Brazil

Abstract

Wind energy, mainly the onshore kind, has been a key technology in the energy transition. However, as more onshore wind is being deployed, the remaining sites become less attractive in terms of wind conditions and capacity factor compared to its offshore equivalent. Offshore wind (OFW) represents a great opportunity as it possesses a wider range of potential installation areas, with better winds, larger turbines, higher energy generation volumes, and a lower impact on local stakeholders. Nevertheless, by the end of 2023, only a total of 75.2 GW of global OFW capacity across 18 countries was in operation, mainly due to regulatory bottlenecks and high costs.
As a result, this thesis intends, while supplementing the academic literature around the industry, to better understand the underpinnings of OFW market profiles by analyzing their performance in relation to a diverse set of features. This intention is fueled not only by the relevance and interdisciplinarity of the topic, but also by the lack of holistic approaches in the existing literature, which instead mainly focuses on singular case studies or single-discipline approaches. Thus, the aim of this thesis is to investigate the attractiveness of OFW markets with a focus on the current situation of the potential Brazilian market. Brazil has been incorporated as a way of exemplifying the analysis, given its great untapped potential and its current regulatory developments. We intend to do this by, firstly, mapping out the attractiveness status of 61 relevant countries, through a Multiple Correspondence Analysis (MCA) with 20 variables related to market characteristics. Secondly, we answer the research question by dividing it into 5, more specific, sub-questions building on the MCA results and with a thorough discussion of the case of Brazil.
An ad hoc dataset with 33 variables was generated in order to obtain, through an MCA, a space constructed by eight thoroughly decided active variables. Within this space, Dimension 1 opposes high versus low attractiveness, while Dimension 2 medium attractiveness in the lower bound: together, they explain 78.8% of the inertia in the data. From the interpretation of the space constructed, we found that the UK, China, Denmark, Brazil, and Mexico are to be considered very attractive; Germany and Chile medium to highly attractive; Belgium, The Netherlands, and Argentina hold medium attractiveness; and Colombia medium to low attractiveness. Furthermore, our results show that the regulation variable did not appear to give a major contribution, while port is the main variable used to construct the geometric space.