Year21: Investment decision support for commercial wind

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Wind energy is playing an increasingly significant role in Canada's energy supply mix. As of 2015, over 11 gigawatts of nameplate generation have been installed nationally. Wind energy's light carbon and water footprints, coupled with proven capacity and reduced costs suggest a strong potential for sustained growth. While development continues, the industry is maturing. Many operational turbines are approaching, or are beyond the halfway mark of their commonly cited 20 year lifespan. As wind farms age, owners face questions of whether to invest to maintain these assets, invest to expand operations, or discontinue investment. The optimal policies for making these decisions are very complex as they depend not only on uncertain future regulatory and market conditions but also on the present physical condition of the assets, the replacement technology, insurance policies and local social climates. All power generation assets face similar challenges, they are particularly steep for wind as the industry has not yet been through an entire life cycle. Further, the conditions of aging are very sensitive to turbine location and the highly stochastic loading environment. The proposed study, led by the Universities of Windsor, Western Ontario, and supporting organizations, aims to develop an investment decision support system to shepherd owners through the dynamic operating climate ahead. Years of public domain and stakeholder supplied historical data will be used to produce estimates of Remaining Useful Life (RUL) of major wind energy assets. In parallel, the study will advance an inclusive model of present day and forecasted risk-adjusted wind farm valuation based on condition of assets (fed from RUL estimates), market, regulatory, and social factors. This decision support system will be developed in two phases. Phase 1 will follow a simple yet instructive, risk-adjusted discounted cash flow Investment Valuation Model of commercial wind farm operation projected beyond year 20. Phase 2 will be built on scenario analysis. It will account for management's flexibility to react to new information using real options valuation techniques to evaluate optimal decision paths of investment abandonment, delay, or expansion.