Grant: Discovery Grants Program - Individual

Renewable Energy is critical to efforts to mitigate climate change and has subsequently attracted investment funds that have purchased swaths of assets in recent years. This diversifies asset ownership (and investment risk) into the public space. This is happening as Wind Energy in Canada and elsewhere, is nearing the end of initial 20-year performance contracts where wind farm operators have questions about what to do next: repair, repower, expand, or sell? The economics of these decisions are heavily influenced by the valuation of the wind farm. Proper valuation includes a knowledge of the physical state of remaining useful life (RUL) of the farm, but also the potential for revenue generation based on market opportunities. Accurate RUL estimation (RULE) for major wind turbine components is challenging even for historically normal loading conditions. Now new extreme weather events are creating environmental loads not anticipated by many RULE models. This "next generation" loading increases uncertainty in the calculation of the depreciation of wind energy assets. Accurate asset valuations affect pivotal investment parameters like financing rates, insurance premiums, and sale prices. This uncertainty is further increased with the advent of expanding market opportunities for wind in integrated grid services like frequency support, energy storage, and/or hydrogen production. Finally, how wind farms are contracted, and contract for services are also changing. Rising penetrations of renewables are requiring modifications across markets that were originally designed around fossil-fueled assets. Further as renewable energy operations become more flexible, their market tools need to follow suit to optimize value. The acceleration of artificial intelligence (AI) applications now presents an opportunity to leverage real-time data to support autonomous, real-time bidding and contracting that has the potential to generate more and better deals for renewable energy stakeholders. This Research Program will develop new tools to enable accurate, timely valuations of wind farm assets through the coupling of innovative climate-evolved RULE techniques with prospective and new market opportunities. This will be achieved by improving RULE models developed by the applicant in a previous NSERC Grant, to now capture the impact of extreme discrete loads caused by intense weather. Then new power purchase agreements (PPA) will be designed to better valorize wind's emerging ancillary service capabilities and reduce contract risks through new multi-party structures that go beyond buyer and seller. Autonomous AI bargaining agents will then be developed to engage in high frequency negotiations informed by real-time farm valuations and market demand that will advance the value of wind in the clean energy transition.