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DOE OSTI · 1669521

Residential Battery Modeling for Control-Oriented Techno-Economic Studies: Preprint

Abstract

Electrochemical batteries, which serve as electric energy storage devices, are becoming increasingly popular among residential buildings that incorporate solar photovoltaic (PV) systems to help meet their energy needs. Battery economics are affected by performance degradation over time, and managing this degradation can help extend the battery's lifespan. The tradeoff between operational costs/benefits and managing battery degradation is of significant research interest. One of the key factors for assessing battery degradation is the dispatch strategy used to control the charging and discharging of the battery. Conventional dispatch strategies typically use simple rule-based methods, and these overly aggressive charging/discharging cycles can significantly reduce a battery’s life span. Our research seeks to develop optimized dispatch strategies for grid-connected PV homes with a goal of extending battery life while simultaneously taking into consideration utility costs and occupant comfort. To achieve this goal, we adapted lithium-ion battery life- and cyclic-degradation models for use in high-fidelity building simulations, so whole-building and grid-interactive controllers can dispatch the batteries along with other flexible loads. With the help of a co-simulation platform, we performed a simulation study to compute the optimized dispatch strategies for relevant operating conditions brought about by changing geographical locations, weather conditions, and utility pricing. Comparing the optimized strategies with the conventional strategies resulted in a >50% decrease in capacity degradation and >10% average reduction in operational costs during the months of January and July in Fort Collins, Colorado; Phoenix, Arizona; and Portland, Oregon.

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BibTeXRIS

Chintala, Rohit (ORCID:0000000191439788), Polly, Benjamin (ORCID:0000000257004163), Jin, Xin, Christensen, Dane (ORCID:0000000245392402), Merket, Noel (ORCID:0000000278505696). 2020-09-04. Residential Battery Modeling for Control-Oriented Techno-Economic Studies: Preprint. https://www.osti.gov/biblio/1669521

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