As distributed energy resources (DERs) gain traction in Texas and other important energy markets, a key question for developers and utilities is: where do battery programs make the most money?
Using Intertrust Flexworks, we modeled how a battery would perform in energy arbitrage across six ERCOT load zones between 2018 and mid-2025.
Our modeling tool, Intertrust Flexworks, is designed for energy companies to assess the value of distributed energy resources within their geographic area. Flexworks takes into account market structure, price dynamics, weather conditions, customer constraints, and program design to deliver robust valuations.
Simulation setup
We modeled an 11.5 kW battery participating in ERCOT’s real-time market (RTM) for energy arbitrage, excluding ancillary services or transmission costs. In this context, energy arbitrage means the battery charges when prices are low, which is often during midday solar generation peaks, and then discharges when prices are high, such as in the evening when demand ramps up. We used historical data provided by ERCOT, and the battery optimization was guided by forecasting price signals provided by Amperon.
The simulation was set up to optimize dispatch on a rolling weekly basis. This means the battery’s charge and discharge decisions were recalculated week by week, capturing seasonal effects and ensuring the model didn’t rely on perfect foresight over the entire period. Further, the battery was allowed to export power back to the ERCOT grid, not just to offset on-site load.
We configured the battery with the following settings:
- Input power max: 5.0 kW
- Output power max: 11.5 kW
- Storage capacity: 13.5 kWh
- Minimum state of charge: 20%
- Inverter efficiency: 95%
Simulations were run using Flexworks’ hourly optimization engine across the following ERCOT load zones: West, CPS, North, South, Austin, and Houston. We modeled the period from 2018 through mid-2025 to capture a wide range of market conditions.
This timeframe includes relatively stable years before the pandemic, extreme volatility during Winter Storm Uri in 2021, and elevated wholesale costs in 2023 driven by tight supply and load growth. By covering more than six years of data, the simulation smooths out short-term spikes while still reflecting the high-volatility environment developers face today.
Results
Our analysis of 60,000+ hours per zone revealed clear geographic winners:
| ERCOT Load Zone | Avg Monthly Revenue ($) | Avg $/kW-year |
| WEST | 63.55 | 66.31 |
| HOUSTON | 56.07 | 58.51 |
| Austin Energy | 55.39 | 57.80 |
| CPS Energy | 54.17 | 56.53 |
| NORTH | 52.94 | 55.24 |
| SOUTH | 52.78 | 55.07 |
What the revenue data shows
The West load zone emerged as the top-performing region, with an average value of $66 per kW-year. The lowest-performing zone, South, averaged $55 per kW-year—a 20% spread that shows location is everything for battery economics.
Even compared to Houston, the next highest load zone, West delivers about 13% more value. For developers and operators, that margin is meaningful: over the lifetime of a battery program, sitting in the right zone can translate into thousands of dollars in additional value per unit.
West Texas benefits from greater price spreads, driven by its high concentration of utility-scale solar and wind. When renewable generation floods the grid midday, prices can dip, creating opportunities for batteries to charge low and discharge high during evening ramps.
However, Houston, CPS, and AEN zones still delivered strong revenue due to increased market volatility in recent years, driven by weather events and load growth.
The power of Flexworks
Running this analysis manually would’ve taken weeks since collecting LMPs, configuring dispatch logic, and comparing revenue across would have to be done for multiple years and regions. Flexworks handled all of it in minutes.
The tool allowed us to run multi-year simulations across six ERCOT zones, configure and test realistic asset specs, and export results for custom visuals and interpretation.
Next steps
This simulation isn’t a financial model but more of a starting point. Knowing where the value lives is critical for developers, VPP operators, and utilities. While our focus was ERCOT, the methodology applies to any deregulated market with similar price volatility and renewable penetration. If you’re designing a DER program, pitching a battery project, or siting VPP capacity, locational revenue modeling is crucial.
Want to run your own simulation? Schedule a demo with the Flexworks team →