Energy-Storage Modeling: State-of-the-Art and Future Research Directions (CROSBI ID 306970)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Sioshansi, Ramteen ; Denholm, Paul ; Arteaga, Juan ; Awara, Sarah ; Bhattacharjee, Shubhrajit ; Botterud, Audun ; Cole, Wesley ; Cortes, Andres ; de Queiroz, Anderson ; DeCarolis, Joseph ; Ding, Zhenhuan ; DiOrio, Nicholas ; Dvorkin, Yury ; Helman, Udi ; Johnson, Jeremiah ; Konstantelos, Ioannis ; Mai, Trieu ; Pandžić, Hrvoje ; Sodano, Daniel ; Gord, Stephen ; Svoboda, Alva ; Zareipour, Hamidreza ; Zhang, Ziang
engleski
Energy-Storage Modeling: State-of-the-Art and Future Research Directions
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.
Energy storage ; Computational modeling ; Power systems
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o izdanju
37 (2)
2022.
860-875
objavljeno
0885-8950
1558-0679
10.1109/TPWRS.2021.3104768