Optimal Control for Battery Storage Using Nonlinear Models

Conference · Mon Jan 01 04:00:00 EST 2018

OSTI ID:1647339

Wu, Di ^[1]; Balducci, Patrick J. ^[1]; Crawford, Aladsair J. ^[1]; Viswanathan, Vilayanur V. ^[1]; Kintner-Meyer, Michael CW ^[1]

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1. BATTELLE (PACIFIC NW LAB)

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.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1647339
• Report Number(s): PNNL-SA-122197
• Country of Publication: United States
• Language: English

Related Subjects

battery
energy storage system
dynamic programming
nonlinear model
optimization