TY - JOUR
T1 - Scalable Planning for Energy Storage in Energy and Reserve Markets
AU - Xu, Bolun
AU - Wang, Yishen
AU - Dvorkin, Yury
AU - Fernandez-Blanco, Ricardo
AU - Silva-Monroy, Cesar A.
AU - Watson, Jean Paul
AU - Kirschen, Daniel S.
N1 - Funding Information:
The authors would like to thank Dr. I. Gyuk and his colleagues at the US DOE Energy Storage Program for funding this research. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94AL85000.
Funding Information:
Manuscript received June 20, 2016; revised October 25, 2016 and January 13, 2017; accepted March 4, 2017. Date of publication March 15, 2017; date of current version October 18, 2017. This work was supported by the US Department of Energy under Grant 1578574. Paper. no. TPWRS-00938-2016.
Publisher Copyright:
© 2012 IEEE.
PY - 2017/11
Y1 - 2017/11
N2 - Energy storage can facilitate the integration of renewable energy resources by providing arbitrage and ancillary services. Jointly optimizing energy and ancillary services in a centralized electricity market reduces the system's operating cost and enhances the profitability of energy storage systems. However, achieving these objectives requires that storage be located and sized properly. We use a bilevel formulation to optimize the location and size of energy storage systems, which perform energy arbitrage and provide regulation services. Our model also ensures the profitability of investments in energy storage by enforcing a rate of return constraint. Computational tractability is achieved through the implementation of a primal decomposition and a subgradient-based cutting-plane method. We test the proposed approach on a 240-bus model of the Western Electricity Coordinating Council system and analyze the effects of different storage technologies, rate of return requirements, and regulation market policies on energy storage participation on the optimal storage investment decisions. We also demonstrate that the proposed approach outperforms exact methods in terms of solution quality and computational performance.
AB - Energy storage can facilitate the integration of renewable energy resources by providing arbitrage and ancillary services. Jointly optimizing energy and ancillary services in a centralized electricity market reduces the system's operating cost and enhances the profitability of energy storage systems. However, achieving these objectives requires that storage be located and sized properly. We use a bilevel formulation to optimize the location and size of energy storage systems, which perform energy arbitrage and provide regulation services. Our model also ensures the profitability of investments in energy storage by enforcing a rate of return constraint. Computational tractability is achieved through the implementation of a primal decomposition and a subgradient-based cutting-plane method. We test the proposed approach on a 240-bus model of the Western Electricity Coordinating Council system and analyze the effects of different storage technologies, rate of return requirements, and regulation market policies on energy storage participation on the optimal storage investment decisions. We also demonstrate that the proposed approach outperforms exact methods in terms of solution quality and computational performance.
KW - ancillary services
KW - arbitrage
KW - cutting-plane method
KW - energy storage (ES)
KW - power system planning
KW - primal decomposition
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U2 - 10.1109/TPWRS.2017.2682790
DO - 10.1109/TPWRS.2017.2682790
M3 - Article
AN - SCOPUS:85036473524
SN - 0885-8950
VL - 32
SP - 4515
EP - 4527
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 6
M1 - 7879307
ER -