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Unlock ERCOT's Energy Storage Economics

Energy storage systems are emerging as essential assets in ERCOT to seamlessly integrate renewable energy, ensure grid reliability and resiliency, and to cost-effectively meet increasing peak demand. With the future shift to energy applications such as energy arbitrage and ERCOT policy changes supporting resource adequacy underway, developers and asset owners should rethink the shorter duration paradigm that was the norm in ERCOT for BESS. Through comprehensive revenue simulations, Stem has demonstrated that a 2-hour BESS can increase cash flows relative to a 1-hour system – with at least 15% improvements in the internal rate of returns (IRR) in each major zone of ERCOT.  

 

We invite you to join us as we dive into ERCOT’s energy storage economics and the case for a 2-hour battery. Our agenda will cover:

  • Stem’s revenue simulation results favoring a 2-hour BESS relative to 1-hour

  • BESS optimization analytics and state-of-the-art revenue simulation process utilized by Stem

  • Review of the ERCOT Contingency Reserve Service (ECRS), the newest ancillary service deployed by ERCOT

  • Preliminary analysis of ECRS prices and insights gleaned

  • Notable policy changes underway that will support longer duration BESS

FEATURED SPEAKERS

Amit Gohil, Senior Director, Wholesale Markets (Front-of-the-Meter) at Stem
Amit Gohil, Senior Director, Wholesale Markets (Front-of-the-Meter) at StemAmit brings 20+ years of experience working in power, renewable energy, and financial services industries and expertise in optimizing energy storage portfolios, analyzing the various storage value streams, and de-risking renewable energy projects in general.
Vlad Miklyukh, Senior Product Manager at Stem
Vlad Miklyukh, Senior Product Manager at StemVlad manages the development of Stem’s simulation team and has been instrumental in assessing the expansion of Stem's energy storage solutions into new BTM and FTM markets. He successfully spearheaded the development of cutting-edge ERCOT model predictive control simulations, enabling accurate and reliable asset performance simulations.

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