An Innovative Approach to Market Based Energy Storage Siting – A Case Study
Thursday, October 8, 2020
2:15 PM – 2:25 PM EDT
With the upsurge in renewable penetration throughout the U.S., a number of states are looking to achieve a carbon-neutral goal within the next 20 years. In parallel, the advancement in storage technologies has driven utilities and generation developers to supplement the existing and anticipated renewable infrastructure with utility-scale storage solutions. One of the key challenges faced by the industry in terms of planning for storage, is to analyze the best location for siting storage on the transmission grid to maximize the revenue obtained from energy arbitrage opportunities in the day-ahead and real-time energy markets. The analysis requires highly accurate nodal security constrained economic dispatch (SCED) models that have been vetted and benchmarked against historical data. Benchmarking is normally performed on the historical congestion on key transmission constraints within the system, average locational marginal price (LMP) differentials against the major hubs within the system and average LMP’s at various representative nodes. While this approach works for most renewable project siting scenarios, the additional complexity with siting storage is induced when benchmarking the expected intraday LMP volatility against the volatility observed in historical ISO/RTO markets. In this study, optimization techniques were used to benchmark the historical LMP volatility in the ERCOT energy market and use the results of the benchmarked models to predict the best locations for siting Energy storage on the transmission system. Further, the sensitivity of the price volatility and resulting arbitrage opportunity for high performing nodes was tested using various storage options and transmission sensitivity analysis. DNV GL will present the results of its case study and outline the approach to determine the key variables that need to be considered in the Energy markets that affect the sensitivity of the intraday LMP volatility to ultimately determine the key nodes for future storage siting.