Unit Commitment With Risk-Adjusted Tranching of Renewable Energy Resources

This paper presents a risk segmentation approach for scheduling generation in power systems with high penetration of renewable energy resources (RERs). This approach aims to facilitate risk-adjusted participation of RERs in the day-ahead market (DAM). It borrows from debt securitization techniques to define risk tranches and develops separate bid curves of RERs by the tranches of different grades of risk. Assigning a higher price to a tranche with greater risk can prevent a renewable asset owner from incurring losses when the asset cannot produce the day-ahead committed amount of energy and must buy energy from the real-time market (RTM). In the proposed approach, the system operator utilizes the risk-segmented bids from RERs and generation reliability constraints to solve a risk-adjusted unit commitment (UC) problem. To a system operator, this can be treated as a deterministic DAM dispatch. The stochasticity of this UC problem is embedded in the renewable bid curves. The resulting increase in DAM revenues due to additional DAM commitment benefits the renewable asset owners. The loads can also benefit from additional RER commitment in DAM as it lowers DAM energy prices. The paper will focus on using this risk-adjusted strategy for wind energy resources. The approach is illustrated on a synthetic 6,700- bus model of the 2030 Electric Reliability Council of Texas (ERCOT) system that has a significant penetration of wind resources.