Location, location, location: Model IDs best spots for offshore energy projects

Researchers have developed a computational model that identifies the best combination of location and energy technologies to maximize offshore energy production, reducing the financial risk associated with investing in offshore projects. The model accounts for different types of wind and marine hydrokinetic technologies, the best location for co-siting these technologies, and the best size of the relevant technologies.

“Offshore energy technologies – such as marine hydrokinetic devices that convert the the ocean’s tides, current and waves into electricity – hold tremendous potential for producing sustainable energy at a reasonable cost,” says Anderson de Queiroz, co-author of a paper on the work and an associate professor of civil, construction and environmental engineering at North Carolina State University. “We also know that putting wind turbines and marine hydrokinetic devices in the same location makes it possible to ensure a reliable flow of energy from offshore sites.

“However, the initial cost of building these offshore sites is considerable, so it is important for utilities to know that a project is going to maximize the return on their investment,” de Queiroz says. “That’s where our work comes in.”

The researchers have developed a model called a portfolio optimization framework. If a utility is considering a range of possible locations for an offshore power facility, the model can determine not only which location is best suited for maximizing energy output, but which combination of wind and hydrokinetic technologies would be able to make the most of that location. The model demonstrated in this paper focused on the use of wind turbines and marine hydrokinetic kites.

“Kites are a subset of hydrokinetic devices that use underwater sails to spin turbines, generating electricity from the movement of the ocean,” de Queiroz says. “However, the model can be modified to account for a range of other marine hydrokinetic technologies.”

To demonstrate the potential of their portfolio optimization framework, the researchers conducted a case study focusing on coastal North Carolina. The case study drew on a wide range of data, covering variables such as windspeeds, ocean currents, the depth of each location, distance from shore, and so on.

“We found that location makes a tremendous difference,” de Queiroz says. “Some places work well for wind turbines, but not for kites; other places work well for kites, but not for turbines.

“But when you find a location that works for both turbines and kites, there are two significant benefits,” de Queiroz says. “First, the cost of energy generation goes down significantly. Second, the stability of energy production goes up – the turbines offset periods when hydrokinetic energy production goes down, and the hydrokinetic devices offset periods when wind production goes down. It really underscores the difference our model can make in terms of maximizing investment in offshore power.

“We’re open to working with the energy sector to help them explore how they might use the model to inform long-term planning decisions related to sustainability and energy security,” says de Queiroz.

The paper, “Fused Portfolio Optimization for Harnessing Marine Renewable Energy Resources,” is published open access in the journal Energy. Corresponding author of the study is Mary Maceda, a Ph.D. student at NC State. The paper was co-authored by Rob Miller, a Ph.D. student at NC State; Victor de Faria, a recent Ph.D. graduate from NC State; Matthew Bryant, a professor of mechanical and aerospace engineering at NC State; and Chris Vermillion, an associate professor of mechanical engineering at the University of Michigan.

This research was done with support from the North Carolina Renewable Ocean Energy Program.