STTR Phase I: Physics-based models of wind variability

This Small Business Technology Transfer Research (STTR) Phase I project aims to develop quantitative models of wind variability to aid the design of reliable, low-carbon electric grid systems with high wind penetration. All abundant renewable resources are naturally variable, creating a challenge for their integra¬tion onto an ?always on? electric grid. While this variability challenge is now beginning to rival the importance of further reductions in the costs of generation hardware, existing variability models suffer numerous shortcomings that limit their accuracy and flexibility. This STTR project aims todevelop and validate new models with a high degree of generality and universal applicability based on atmospheric sciences and the physics of turbulent flows. The proposed models will provide new conceptual insights into the temporal and geographic aspects of wind variability along with superior performance for risk-assessment and reliability estimation based on rare and infrequent events including wind droughts. These models will enable design (without overdesign) of a reliable grid, including not only changes to its electrical system, but also changes to the policy, regulatory, and financial systems that are essential parts of the electricity delivery system. The broader impact/commercial potential of this project will be realized across multiple sectors. The project will provide enabling tools to broad engineering and financial constituencies involved in transforming the electricitysystem?s infrastructure and organization as it moves towards a sustainable and renewable future. Application of these tools will lower the costs of wind integration, thereby speeding grid transformation and hastening the reduction of electric-sector greenhouse gas emissions. Grid planners and operators will benefit from easier-to-use engineering and simulation modules in commercial grid software packages. In the financial sectors, the model tools will enable accurate estimation of wind energy risks, allowing new risk-management market instruments and contract structures. The fundamental conceptual understanding of variability along with actionable quantitative metrics made possible by the proposed models will enable the formation of new ventures and enterprises capitalizing on emerging opportunities in the smart-grid space.