Optimal Control of Customer-Sited Distributed Energy Resources in Electric Grid Services Programs
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Date: Thu, April 22, 2021
Time: 12:30pm - 2:30pm
Location: Zoom, see email for details (or contact our main office)
Speaker: Douglas Ellman, candidate for PhD
The topic of the proposed dissertation is optimal control of customer-sited distributed energy resources in electric grid services programs. This dissertation will explore the question of how to best manage customer energy resources (with a focus on battery energy storage systems) in order to reduce customer costs while participating in utility tariffs and grid services programs that encourage customers to adapt their electric load profile to the needs of the power system. The goals of this work are to develop insights and methods to improve the utilization of customer resources to support operation of the electric power system, in order to ultimately reduce system cost, improve reliability, and support integration of renewable generation. This dissertation will approach this topic from several angles: (1) analytically, with mathematical analysis of the underlying optimization problems, (2) numerically, by developing and evaluating performance of control algorithms, and (3) practically, by demonstrating and testing control algorithms on a hardware-in-the-loop test bed.
Date: Thu, April 22, 2021
Time: 12:30pm - 2:30pm
Location: Zoom, see email for details (or contact our main office)
Speaker: Douglas Ellman, candidate for PhD
The topic of the proposed dissertation is optimal control of customer-sited distributed energy resources in electric grid services programs. This dissertation will explore the question of how to best manage customer energy resources (with a focus on battery energy storage systems) in order to reduce customer costs while participating in utility tariffs and grid services programs that encourage customers to adapt their electric load profile to the needs of the power system. The goals of this work are to develop insights and methods to improve the utilization of customer resources to support operation of the electric power system, in order to ultimately reduce system cost, improve reliability, and support integration of renewable generation. This dissertation will approach this topic from several angles: (1) analytically, with mathematical analysis of the underlying optimization problems, (2) numerically, by developing and evaluating performance of control algorithms, and (3) practically, by demonstrating and testing control algorithms on a hardware-in-the-loop test bed.