January 1, 2018
Conference Paper

Optimal Control for Battery Storage Using Nonlinear Models

Abstract

Battery storage system (BSS) becomes increasingly popular for grid applications due to the advance in battery and power electronics technologies as well as the growing need of flexibility and reserve from power systems with rapidly developed renewable generation. Successful assessment and deployment of BSS requires optimizing its operation and therefore maximizing the potential benefits. Although there exist studies that develop optimal control for evaluation or operational scheduling of BSS, modeling of charging/discharging operation and the corresponding impacts on state-of-charge (SOC) is over simplified in these methods. This paper develops an optimal control for BSS evaluation and operational scheduling using a general nonlinear model that expresses the change of SOC as a function of charging/discharging power and SOC level. The proposed method is compared with a typical existing method through a real-world energy storage evaluation project to show the significance of the proposed method.

Revised: August 13, 2020 | Published: January 1, 2018

Citation

Wu D., P.J. Balducci, A.J. Crawford, V.V. Viswanathan, and M. Kintner-Meyer. 2018. Optimal Control for Battery Storage Using Nonlinear Models. In Electrical Energy Storage Applications and Technologies (EESAT 2017), October 11-13, 2017, San Diego, CA. Washington D.C.:US Department of of Energy/Office of Electricity. PNNL-SA-122197.