The purpose of this project is to demonstrate a proof-of-concept for a short-term wind forecasting engine. Installed wind power capacity across the nation has increased dramatically over the last decade. However, utility companies, grid operators and wind farm owners are facing major difficulties because of intermittent winds. The variability of wind is further exacerbated for wind farms that are located on complex terrain regions. Substantial technology gaps exist in short-term wind power forecasting and grid integration. Current practice relies on weather forecasting and historical wind analysis, but power forecasting using these approaches is prone to large errors. The forecasting engine developed by the research team is designed for fast execution on parallel computing clusters accelerated by modern graphics processing units in a multi-scale fashion, where micro-scale computations will be concurrently driven by meso-scale weather prediction models. The numerical methods and the turbulence model adopted inside the forecasting engine offer great flexibility for complex terrain and enable significantly improved predictions at the turbine hub height.
The availability of an accurate wind forecasting engine for utility companies, grid operators and wind farm owners has a broad impact on the efficient production and the economics of energy. A reliable wind forecasting engine will help increase the amount of wind power in the overall energy portfolio. Accurate forecasting is also expected to help lower the grid integration cost of wind energy and make this form of renewable energy competitive in a deregulated electricity market that is expected to be driven by smart-grid technologies. A forecasting engine has the potential to enhance the reliability of the electricity grid, because the grid is vulnerable to overload when winds suddenly ramp up without any advance information on the wind. In addition to forecasting power from existing wind farms, the proposed technology can be used to increase existing transmission line capacity and optimize wind farm layouts for maximum power generation.
I-Corps team explored the potential business value of a wind resource assessment and wind power forecasting technology. Following the I-CORPS curriculum, and with guidance from the I-CORPS instructors, the team developed value propositions for the technology, and interviewed over 95 people in the industry, including financiers, turbine manufacturers, wind farm developers, and utility companies. The team has reached out to potential customers in the U.S., Europe and Australia. The customer discovery process was highly informative in terms of understanding the pain points experienced in the wind energy industry. The interviews with stakeholders revealed that there are areas of fundamentral research that the industry truly cares about, such as atmospheric stability, complex terrain and ground cover. Interviews also revealed that the indusrty sees more immediate value in wind resource assessment over complex terrain than microscale power forecasting. The team has also discovered that the need for wind forecasting is evolving as new energy policies are being developed at the federal goverment level. Current methods that are in use in the industry appears to meet the needs, but with new policies, expansion to complex terrain areas, and market deregulation, the industry concurs with the team's value hypothesis on microscale power forecasting. Team also discovered that renewable energy credits are also a major driver in the wind industry, and any commercialization effort should carefully consider the timing of their launch. As of now, the wind industry is in a retreat for new project development. I-CORPS project also enabled the infusion of new ideas and technologies to the industy. Several industry members were ignoring technologies that could help improve the current state-of-the-art, but were unaware that new technologies are accessible to them. Through the customer discovery process, the PI and the entrepreneurial lead gained a highly unique training in commercialization of fundamental research, and became the first team in their state to have received this training. The knowledge and experiences gained as part of the I-CORPS curriculum will be integrated into the PIs educational activities. The I-CORPS team also submitted an NSF Partnership for Innovation, Technology-Transfer grant to secure funding for further development of the prototype technology. The I-CORPS team is also working on creating a start-up company around the proposed technology.
