Enhanced Representations of Lithium-Ion Batteries in Power Systems Models and Their Effect on the Valuation of Energy Arbitrage Applications

22 Pages Posted: 15 Nov 2016

See all articles by Apurba Sakti

Apurba Sakti

MIT Energy Initiative

Kevin Gallagher

Argonne National Laboratory - Chemical Sciences and Engineering Division

Nestor Sepulveda

Massachusetts Institute of Technology (MIT)

Canan Uckun

Argonne National Laboratory

Claudio Vergara

Massachusetts Institute of Technology (MIT)

Fernando de Sisternes

World Bank

Dennis Dees

Argonne National Laboratory - Chemical Sciences and Engineering Division

Audun Botterud

Argonne National Laboratory; Massachusetts Institute of Technology (MIT) - Laboratory for Information and Decision Systems

Date Written: November 12, 2016

Abstract

We develop three novel enhanced mixed integer-linear representations of the power limit of the battery and its efficiency as a function of the charge and discharge power and the state of charge of the battery, which can be directly implemented in large-scale power systems models and solved with commercial solvers. Using these representations, we conduct a techno-economic analysis of the performance of a 10MWh lithium-ion battery system testing the effect of a 5-min vs. a 60-min period price signal on profits using real time prices from a selected node in the MISO electricity market. Results show that models of lithium-ion batteries where the power limits and efficiency are held constant overestimate profits by 10% compared to those obtained from an enhanced representation that closely matches the real behavior of the battery. When the battery system is exposed to a 5-min price signal, the profitability from energy arbitrage improves by 60% compared to that from hourly price exposure. These results indicate that a more accurate representation of li-ion batteries as well as the market rules that govern the frequency of electricity prices can play a major role on the estimation of the value of battery technologies for power grid applications.

Keywords: Enhanced Battery Representation; Li-Ion MILP Models; Power Systems Arbitrage Modeling; Real-Time Pricing Effects

Suggested Citation

Sakti, Apurba and Gallagher, Kevin and Sepulveda, Nestor and Uckun, Canan and Vergara, Claudio and de Sisternes, Fernando and Dees, Dennis and Botterud, Audun, Enhanced Representations of Lithium-Ion Batteries in Power Systems Models and Their Effect on the Valuation of Energy Arbitrage Applications (November 12, 2016). Available at SSRN: https://ssrn.com/abstract=2868414 or http://dx.doi.org/10.2139/ssrn.2868414

Apurba Sakti (Contact Author)

MIT Energy Initiative ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Kevin Gallagher

Argonne National Laboratory - Chemical Sciences and Engineering Division ( email )

9700 South Cass Avenue
Argonne, IL 60439
United States

Nestor Sepulveda

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Canan Uckun

Argonne National Laboratory ( email )

9700 S. Cass Avenue
Argonne, IL 60439
United States

Claudio Vergara

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Fernando De Sisternes

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

Dennis Dees

Argonne National Laboratory - Chemical Sciences and Engineering Division ( email )

9700 South Cass Avenue
Argonne, IL 60439
United States

Audun Botterud

Argonne National Laboratory ( email )

9700 S. Cass Avenue
Argonne, IL 60439
United States

Massachusetts Institute of Technology (MIT) - Laboratory for Information and Decision Systems ( email )

77 Massachusetts Ave
32-D608
Cambridge, MA 02139
United States

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