In Stem’s recent webinar, our energy experts – Mike Alter, Director, Optimization Solutions and David Rothblum, Sr Data Scientist – delve into the ERCOT wholesale market insights and key takeaways from benchmarking the performance of battery energy storage assets with our Athena® optimization platform. The webinar on-demand is now available and reflects the 2022 analysis of energy storage systems within our Benchmarking ERCOT Performance of Stem’s Athena® Optimization Platform whitepaper. This blog serves as a recap of the key insights shared during the webinar and whitepaper, elaborating on our objectives, methodology and some of the insights gained.
Why Benchmark Performance in ERCOT
ERCOT’s energy-only market structure and current grid conditions have driven significant value in the ancillary services market making it particularly attractive to utility-scale battery storage systems. First, Texas’ population and economic growth have produced record electricity demand. Second, Texas has also seen massive renewable expansion while solar deployment has surpassed records originally set by CAISO. Third, weather volatility impacts electric demand and affects generator production and availability, making it more difficult for grid operators to manage supply and demand. Finally, the energy-only market structure combined with the above conditions leads to large price spikes that are meant to incentivize the entrance of new energy resources and offer considerable opportunities for revenue generation.
ERCOT is also unique in its data transparency, providing extensive data that enables in-depth analysis of market actions and participant behavior. Looking at the evolving grid conditions and policy landscape in ERCOT, we see a prime opportunity for well-managed batteries to enhance their value. We believe the key to realizing this opportunity is a dynamic strategy that can adapt battery behavior based on real-time market signals and one that remains agile amidst changing market rules and grid needs.
The Goals & Scope of Our Analysis
Our primary goals are to simulate how the operations of Stem’s energy optimization platform, Athena, would have translated into the ERCOT market through this back-cast benchmarking analysis, document key factors that affect energy storage performance, and derive actionable insights to inform future operational strategies and technical improvements. We believe a well-rounded approach that pursues and balances opportunities across all products is critical for sustained performance in the face of an evolving market landscape.
In our report, we select six standalone assets that started commercial operations prior to January 2022 to provide a performance baseline. The assets are geographically dispersed across various load zones, range in capacity, and are managed by a variety of operators. This sample allows us to understand the impact of various locations, hardware capabilities, and an array of management strategies and operational practices.
Simulation Scenarios
We leveraged publicly available ERCOT data to reconstruct each asset’s market behavior and revenues. The actual revenues provide a benchmark for various back-cast simulation scenarios we conducted with our digital twin simulation engine.
The first scenario is the perfect forecast scenario, which uses actual prices as forecasts and allows for optimization across any market product in order to maximize revenue. This scenario represents what we believe to be the theoretical maximum revenue for the asset and serves as an upper bound for comparison.
The second scenario is what we call the Stem scenario. It uses Stem’s state-of-the-art price forecasts when optimizing bids and offers across the market products. This scenario represents how we’d expect to operate in real conditions. We use a fixed strategy that does not reflect human insights and interventions that might further improve operations.
Finally, there is a naïve scenario. It uses simple persistence forecasts and limits participation to RRS and real-time energy. This scenario provides a less complex operating strategy and a lower bound for performance comparisons.
These scenarios offer a spectrum of possibilities from a perfect market prediction to more conservative strategies, helping us to establish benchmarks and identify areas for improvement.
Leveraging Stem’s Unparalleled Experience
As we dissect these scenarios, we see how Athena’s advanced optimization and state-of-the-art forecasting can lead to better market outcomes, even in a landscape as complex and dynamic as ERCOT. The analysis is not just about numbers, it is about understanding operational nuances. We want to understand how the variability in management and operations could affect overall performance and profitability in the real world.
Our hands-on experience with a multitude of ESS hardware products also informs our model, enabling us to factor in unique characteristics that can significantly impact performance details
that are essential for reliable simulation.
Our simulation platform mirrors exactly how Stem operates energy storage systems in real-time market conditions. Our aim is accuracy in replicating the full wholesale market participation process for energy storage plants. The core of this is our Athena PowerBidder™ application, code, and algorithms which generate the optimized bids. The consistency between our operational code and simulation platform is vital. It ensures that each what-if scenario we analyzed aligns with the real-world strategies we would employ.
Watch the webinar on-demand or download the whitepaper to dive into the workings of the simulation, which played a critical role in informing our results and insights.
