Energy-Storage Modeling: State-of-the-Art and Future Research Directions

Ramteen Sioshansi; Paul Denholm; Juan Arteaga; Sarah Awara; Shubhrajit Bhattacharjee; Audun Botterud; Wesley Cole; Andres Cortes; Anderson De Queiroz; Joseph Decarolis; Zhenhuan DIng; Nicholas DIorio; Yury Dvorkin; Udi Helman; Jeremiah X. Johnson; Ioannis Konstantelos; Trieu Mai; Hrvoje Pandzic; Daniel Sodano; Gord Stephen; Alva Svoboda; Hamidreza Zareipour; Ziang Zhang

doi:10.1109/TPWRS.2021.3104768

Energy-Storage Modeling: State-of-the-Art and Future Research Directions

Ramteen Sioshansi, Paul Denholm, Juan Arteaga, Sarah Awara, Shubhrajit Bhattacharjee, Audun Botterud, Wesley Cole, Andres Cortes, Anderson De Queiroz, Joseph Decarolis, Zhenhuan DIng, Nicholas DIorio, Yury Dvorkin, Udi Helman, Jeremiah X. Johnson, Ioannis Konstantelos, Trieu Mai, Hrvoje Pandzic, Daniel Sodano, Gord StephenAlva Svoboda, Hamidreza Zareipour, Ziang Zhang

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Given its physical characteristics and the range of services that it can provide, energy storage raises unique modeling challenges. This paper summarizes capabilities that operational, planning, and resource-adequacy models that include energy storage should have and surveys gaps in extant models. Existing models that represent energy storage differ in fidelity of representing the balance of the power system and energy-storage applications. Modeling results are sensitive to these differences. The importance of capturing chronology can raise challenges in energy-storage modeling. Some models 'decouple' individual operating periods from one another, allowing for natural decomposition and rendering the models relatively computationally tractable. Energy storage complicates such a modeling approach. Improving the representation of the balance of the system can have major effects in capturing energy-storage costs and benefits.

Original language	English (US)
Pages (from-to)	860-875
Number of pages	16
Journal	IEEE Transactions on Power Systems
Volume	37
Issue number	2
DOIs	https://doi.org/10.1109/TPWRS.2021.3104768
State	Published - Mar 1 2022

Keywords

Energy storage
modeling
power system economics
power system expansion planning
power system operations

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/TPWRS.2021.3104768

Cite this

Sioshansi, R., Denholm, P., Arteaga, J., Awara, S., Bhattacharjee, S., Botterud, A., Cole, W., Cortes, A., Queiroz, A. D., Decarolis, J., DIng, Z., DIorio, N., Dvorkin, Y., Helman, U., Johnson, J. X., Konstantelos, I., Mai, T., Pandzic, H., Sodano, D., ... Zhang, Z. (2022). Energy-Storage Modeling: State-of-the-Art and Future Research Directions. IEEE Transactions on Power Systems, 37(2), 860-875. https://doi.org/10.1109/TPWRS.2021.3104768

Sioshansi, R, Denholm, P, Arteaga, J, Awara, S, Bhattacharjee, S, Botterud, A, Cole, W, Cortes, A, Queiroz, AD, Decarolis, J, DIng, Z, DIorio, N, Dvorkin, Y, Helman, U, Johnson, JX, Konstantelos, I, Mai, T, Pandzic, H, Sodano, D, Stephen, G, Svoboda, A, Zareipour, H & Zhang, Z 2022, 'Energy-Storage Modeling: State-of-the-Art and Future Research Directions', IEEE Transactions on Power Systems, vol. 37, no. 2, pp. 860-875. https://doi.org/10.1109/TPWRS.2021.3104768

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Energy-Storage Modeling: State-of-the-Art and Future Research Directions

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Keywords

ASJC Scopus subject areas

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