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

被引：41

作者：

Sioshansi, Ramteen ^{[1
,2
]}

Denholm, Paul ^{[3
]}

Arteaga, Juan ^{[4
]}

Awara, Sarah ^{[3
]}

Bhattacharjee, Shubhrajit ^{[4
]}

Botterud, Audun ^{[5
,6
]}

Cole, Wesley ^{[3
]}

Cortes, Andres ^{[7
]}

Queiroz, Anderson de ^{[8
]}

DeCarolis, Joseph ^{[8
]}

Ding, Zhenhuan ^{[9
]}

DiOrio, Nicholas ^{[3
]}

Dvorkin, Yury ^{[10
]}

Helman, Udi ^{[11
]}

Johnson, Jeremiah X. ^{[8
]}

Konstantelos, Ioannis ^{[12
]}

Mai, Trieu ^{[3
]}

Pandzic, Hrvoje ^{[13
]}

Sodano, Daniel ^{[8
]}

Stephen, Gord ^{[3
]}

Svoboda, Alva ^{[14
]}

Zareipour, Hamidreza ^{[4
]}

Zhang, Ziang ^{[9
]}

机构：

[1] Ohio State Univ, Dept Integrated Syst Engn, Columbus, OH 43210 USA

[2] Ohio State Univ, Dept Elect & Comp Engn, Columbus, OH 43210 USA

[3] Natl Renewable Energy Lab, Strateg Energy Anal Ctr, Golden, CO 80401 USA

[4] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada

[5] MIT, Lab Informat & Decis Syst, 77 Massachusetts Ave, Cambridge, MA 02139 USA

[6] Argonne Natl Lab, Energy Syst Div, 9700 S Cass Ave, Argonne, IL 60439 USA

[7] Elect Power Res Inst, Palo Alto, CA 94304 USA

[8] North Carolina State Univ, Dept Civil Construct & Environm Engn, Raleigh, NC 27695 USA

[9] SUNY Binghamton, Dept Elect & Comp Engn, Binghamton, NY 13902 USA

[10] New York Univ, Tandon Sch Engn, Dept Elect & Comp Engn, New York, NY 10003 USA

[11] Helman Analyt, Oakland, CA 94612 USA

[12] Imperial Coll London, Fac Engn, Dept Elect & Elect Engn, London SW7 2AZ, England

[13] Univ Zagreb, Fac Elect Engn & Comp, Unska 3, HR-10000 Zagreb, Croatia

[14] Pacific Gas & Elect Co, San Francisco, CA 94105 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2022年 / 37卷 / 02期

关键词：

Energy storage; Computational modeling; Modeling; Power systems; Planning; Biological system modeling; Mathematical model; power system operations; power system expansion planning; power system economics; modeling; REDOX FLOW BATTERY; OPTIMAL POWER-FLOW; FREQUENCY REGULATION; UNIT-COMMITMENT; STOCHASTIC OPTIMIZATION; WIND POWER; CAPACITY EXPANSION; SCALE STORAGE; SOLAR POWER; SYSTEM;

D O I：

10.1109/TPWRS.2021.3104768

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：860 / 875

页数：16

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