Maximizing the Cost Savings for Utility Customers Using Behind-the-Meter Energy Storage
Presented by: Tu Nguyen, Sandia National Laboratories
Thursday, May 31, 2018 | 1:00pm – 2:00pm ET
The transformation of today’s grid toward smart grid has given the energy storage systems (ESSs) the opportunity to provide more services to the electric grid, as well as the end customers. On the grid’s side, ESSs can generate revenue streams participating in electricity markets by providing services such as energy arbitrage, frequency regulation or spinning reserves. On the customers’ side, ESSs can provide a wide range of applications from on-site back-up power, storage for off-grid renewable systems to solutions for load shifting and peak shaving for commercial/industrial businesses.
This webinar focuses on the benefits of behind-the-meter (BTM) ESSs to the utility customers and the method for optimizing these benefits. A nonlinear optimization problem is formulated to find the optimal operating scheme for ESSs to minimize the energy and demand charges of time-of-use (TOU) customers, or to minimize the energy charge of net-metering (NEM) customers. The problem is then transformed to a Linear Programming (LP) problem using Minmax technique. Case studies are conducted for residential and commercial customers in California and an industrial customer in New Mexico.
WHO SHOULD ATTEND: CEO, CTO, CIO, C-Level, Managers and Electrical/Power/IT Engineers
About the Speaker:
Tu A. Nguyen is a Postdoctoral Appointee in the Energy Storage Technology and Systems Department at Sandia National Laboratories. He received his B.S degree in Power Systems from Hanoi University of Science and Technology, Vietnam in 2007. He worked as a Power Transformer Test Engineer in the ABB High Voltage Test Department in Vietnam from 2008 to 2009. He received his Ph.D. degree from Missouri University of Science and Technology in December 2014. From 2015 to 2016, he worked as a Research Associate at the University of Washington. His research interests include energy storage economics, microgrid modeling and analysis, and the integration of distributed resources into power grids.
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