The cost of wind energy has been on a downward trend over the last several years dropping from $70/MWh for subsidized Power Purchase Agreements (PPA) in 2009 to between $40/MWh and $20/MWh today, according to industry reports. This translates to roughly 4.0 c/kWh to less than 3.0 c/kWh on consumer electricity bills. Unsubsidized projects range from $32/MWh to $77/MWh, converting to between 4.0 c/kWh to 8.0 c/kWh on consumer bills.
Pricing terms vary based on the project financing, quality of wind resource, availability of transmission, turbine performance characteristics and more. The 20-year PPA agreement calls for investors to estimate the total revenue over the life of the project. If pricing is set too low, then the project is at risk for cash flow deficiencies and an unsustainable rate of return for its investors.
One factor taken into consideration when pricing the PPA is the strength and quality of the wind resource at the site. Advancements in the technologies allows developers and owners to capitalize on the wind resource by investing in longer and lighter blades, taller wind towers and higher MW-rated gearboxes that allow for more power connectivity to the grid. However, curtailment issues and prolonged downtime from supplier shortages can cripple the profitability of a site.
The only way to win profitable PPA auctions at competitive pricing is with digitalization. By digitalizing the wind farm, an owner/developer can project the short and long-term costs of operations, building multi-year budgets and predictive health maintenance forecasts that lower their cost of energy beyond the current $40/mWh to $20/mWh range. Forward visibility using a small data from material science-approach provides for the predicted failure rates of the fleet at a per asset, per critical component level. The owner/operators receive a “3D prognostics watchlist” with accompanying actions that extend asset life. When operators know when and where a failure in their fleet will occur, they can reduce inventory carrying costs, have better supply chain integration, and lower risk management costs.
Early adopters into this advanced prognostic technology benefit from reductions in their cost of energy, aiding in competitively priced PPA auctions and increased revenue.
