Stochastic Valuation of Energy Storage Systems Considering Degradation

Nanpeng Yu, UC Riverside

May 18, 2016, 11:00 - 12:00pm, EBU-II 479

   

Abstract:  Driven by environmental regulations and rapidly falling renewable prices, the share of renewable generation in global electrical energy mix is expected to increase significantly over time. Energy storage system is well poised to mitigate uncertainties of renewable generation outputs. Gird-scale energy storage projects are major investments which call for rigorous valuation and risk analysis. This talk provides a stochastic energy storage valuation framework in wholesale power markets to spearhead optimal deployment of energy storage systems. Within the valuation framework, an energy storage system operation optimization model is developed to determine the optimal dispatch sequences. In addition, a future curve dynamics model is built to capture the volatilities of electricity prices. The simulation results reveal that majority of energy storages market revenue comes from ancillary services. The conditional value-at-risk metric shows that the risk associated with energy storage system investment is relatively high compared with the expected net-revenue.

Previous energy storage valuations have been conducted by optimizing the battery’s actions over the course of its lifetime, but their establishment did not consider the influence of these actions on the lifetime itself. This talk also re-evaluates storage system profitability with realistic battery aging taken into account. An approximate model of degradation suitable for co-optimization with the set of battery actions is then developed. It is shown via simulation that co-optimization through this model almost completely mitigates the loss of value caused by cycle degradation.

   

Bio:  Dr. Yu received his B.S. in Electrical Engineering from Tsinghua University, Beijing, China, in 2006. Dr. Yu also received his M.S. degrees in Electrical Engineering and Economics and Ph.D. degree from Iowa State University in 2010. Before joining University of California, Riverside, Dr. Yu was a senior power system planner and project manager at Southern California Edison from Jan, 2011 to July 2014. Currently, he is a tenure track assistant professor of Electrical and Computer Engineering at the University of California, Riverside, CA. Dr. Yu’s research interests include energy storage valuation and optimization, big data analytics in power distribution systems, and demand response. In the past 2 years, Dr. Yu has been PI and Co-PI for over ten smart grid research projects with a total budget of over $6 Million.

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