Global push to scale offshore wind as innovation and policies drive renewables
In an exclusive interview with Energy Connects, Ben Backwell, CEO of the Global Wind Energy Council, highlights the rapid development of offshore wind energy and its critical role in the global transition to renewable energy.
At COP 28, organisations and governments pledged to triple renewable energy capacity by 2030. How are innovation and policies contributing to the scaling up of offshore wind energy?
Offshore wind energy is one of the fastest-growing renewable technologies today. This growth is driven by its large-scale potential and competitive costs compared to fossil fuels and other renewable sources. Offshore projects can be developed at a vast scale without the need for valuable land, making them particularly attractive in regions with high population density. Over the last 20 years, offshore wind has transitioned from a niche technology to a mainstream player in the energy sector. More governments worldwide are adopting offshore wind and setting ambitious targets, positioning it as a central driver of the global energy transition.
"Offshore wind energy is one of the fastest-growing renewable technologies today. This growth is driven by its large-scale potential and competitive costs compared to fossil fuels and other renewable sources."
How are pledges, such as the one made at COP28, accelerating offshore wind capacity expansion?
A key example is the Global Offshore Wind Alliance, a partnership established by Denmark, the International Renewable Energy Agency (IRENA), the Global Wind Energy Council (GWEC), and now joined by about 20 governments globally. This alliance set a goal of reaching 380 gigawatts of offshore wind capacity by 2030, and we are now seeing significant progress toward that target. Current projections suggest that around 400 gigawatts of offshore wind capacity will be built over the next 8 to 10 years. Governments play a crucial role in this process by ensuring regulatory frameworks, grid development, and infrastructure planning are in place to enable swift and efficient project implementation. The collaboration between governments, industry, and investors is essential to meeting these targets within the necessary timeframe for achieving net-zero emissions.
"AI can help predict fluctuations in demand and supply, allowing for more dynamic management of the grid. By balancing variable renewable energy sources with storage solutions, we can create an intelligent grid that is more adaptive and resilient."
How have collaborations contributed to the industry, and how can they help resolve the bottlenecks it faces?
Collaborations like the Global Offshore Wind Alliance are instrumental in providing the right signals to the supply chain. Offshore wind development is not just about building turbines; it involves a complex web of infrastructure, including grids, cables, substations, transformers, installation vessels, and ports. Currently, many of these elements are not fully prepared to meet the demands of rapid expansion. These partnerships help create clarity and transparency, encouraging private sector investment in key areas such as cable factories, transformer production, and the construction of installation vessels. Governments, working in tandem with the private sector, can offer the necessary incentives and regulatory certainty to enable these critical investments, thus resolving supply chain bottlenecks and ensuring that infrastructure keeps pace with the industry's growth.
How do you see advanced technologies such as AI and blockchain playing a role in improving transparency and efficiency in offshore wind energy?
We are at the beginning stages of integrating advanced technologies like AI and blockchain into the offshore wind sector, but their potential is immense. AI, for instance, is already being widely adopted. One key area is weather forecasting—AI-driven models are significantly improving the accuracy of weather predictions, which in turn helps optimise turbine performance. By better understanding wind patterns, turbines can adjust to capture the maximum amount of energy, improving overall efficiency.
AI is also used in predictive maintenance, which allows us to monitor the stress on key components like blades, ball bearings, and gearboxes. This helps prevent equipment failures and reduces downtime, which is crucial for maintaining consistent energy production. Another important application is in grid management—AI can help predict fluctuations in demand and supply, allowing for more dynamic management of the grid. By balancing variable renewable energy sources with storage solutions, we can create an intelligent grid that is more adaptive and resilient.
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