Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Bistline, John; Cole, Wesley; Damato, Giovanni; DeCarolis, Joseph; Frazier, Will; Linga, Vikram; Marcy, Cara; Namovicz, Chris; Podkaminer, Kara; Sims, Ryan; Sukunta, Manussawee; Young, David

doi:10.1088/2516-1083/ab9894

Title: Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Journal Article · Fri Jul 24 00:00:00 EDT 2020 · Progress in Energy

DOI:https://doi.org/10.1088/2516-1083/ab9894· OSTI ID:1782594

Bistline, John;

; Damato, Giovanni; DeCarolis, Joseph; Frazier, Will; Linga, Vikram; Marcy, Cara; Namovicz, Chris; Podkaminer, Kara; Sims, Ryan; Sukunta, Manussawee; Young, David

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Strategic Programs (EE-SP); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Water Power Technologies Office (EE-4W); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind Energy Technologies Office (EE-4W)

DOE Contract Number:: DE-AC36-08GO28308

OSTI ID:: 1782594

Report Number(s):: NREL/JA-5C00-75624; MainId:6934; UUID:d1b2668b-991b-ea11-9c2a-ac162d87dfe5; MainAdminID:22410

Journal Information:: Progress in Energy, Vol. 2, Issue 3

Country of Publication:: United States

Language:: English

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Title: Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

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