This paper presents a method for sizing grid-level flywheel energy storage systems using optimal control. This method allows the loss dynamics of the flywheel system to be incorporated into the sizing procedure, and allows data-driven trade studies to be performed which trade peak grid power requirements and flywheel storage capacity. A demonstration of the sizing methodology will be illustrated through a case study based on home consumption and solar generation data collected from the largest smart grid in Austin, Texas, USA.
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Hearn et al. (2013) studied this question.
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