‘Set it and forget it’: California BESS operators miss out on millions with static bidding strategies, Gridmatic says
Energy-Storage.news Premium speaks with David Miller, CCO of Gridmatic, about the company’s latest report from CAISO.
Energy Storage News4 min read58 views
Miller, who wrote the report, said the initial expectation was that CAISO would be less volatile than ERCOT because of its predictable daily duck curve, allowing batteries to charge during periods of high solar generation and discharge later in the day. Based on that pattern, the assumption was that California would present a relatively straightforward environment for battery operators to generate revenue, with fewer market complexities than ERCOT.
The research results, however, did not support that assumption.
According to Miller, the most significant conclusion from the study was the wide spread in earnings measured on a dollars-per-kilowatt basis. He said battery performance differed substantially across assets, with revenue outcomes showing a high degree of variation.
The study determined that a large number of battery operators rely on fixed bidding strategies that stay unchanged for long stretches of time instead of modifying their bids in response to evolving market conditions.
Miller said many batteries effectively follow what he described as a "set it and forget it" approach. In these cases, operators simply decide on a specific bid price and quantity and continue submitting those same values every hour over an extended period, rather than actively adjusting their strategy.
He added that this behavior leaves considerable revenue unrealized and suggests that market operations are less advanced than Gridmatic had originally expected.
Miller explained that such a strategy becomes especially restrictive during periods of exceptionally high prices. He noted that an operator might reasonably decide to focus only on the duck curve by charging during daylight hours and discharging in the evening. Under normal conditions, that could mean buying power at US$0 and selling it at US$50. On days with extreme price spikes, however, charging could occur at US$100 while discharging reaches US$500. A static bidding strategy would fail to capture those additional gains.
Gridmatic's research highlighted three main approaches that separated the highest-performing battery systems from the rest.
The first involved static bidding practices. Many battery owners continued using identical bid prices and quantities for prolonged periods, without adjusting their offers to reflect shifting market dynamics or responding to high-price events.
The second factor was restricted market participation. Certain battery systems took part only in day-ahead energy markets, overlooking revenue opportunities available in real-time energy markets as well as ancillary service markets.
The third differentiator, closely related to limited participation but focused on the products being offered rather than the timing, was a single-product strategy. Lower-performing batteries frequently depended on only one source of income instead of optimising simultaneously across both energy markets and ancillary service markets.
Geography also played an important role in operational results. Batteries located in Southern California's SP zone benefited more from stronger duck curve dynamics driven by higher levels of solar generation, while batteries operating in Northern California's NP zone generally had greater opportunities to earn revenue from ancillary service markets.
Preparing the analysis required Gridmatic to overcome data limitations specific to CAISO that are not present in markets such as ERCOT.
Miller explained that CAISO does not disclose the same level of information about the activities of individual resources that is available in ERCOT.
To address that challenge, the company created what it calls a "shadow clearing engine," a tool designed to estimate market awards by combining publicly available bidding information with market clearing prices.
Miller said the shadow clearing engine effectively reproduces the CAISO market logic by determining how batteries would be dispatched according to their submitted bids and the market clearing prices that existed at that point in time.
The company verified the methodology by comparing its estimates with available Federal Energy Regulatory Commission (FERC) data and by measuring the model's predictions against the performance of a battery asset operated directly by Gridmatic.
The study's conclusions are especially significant in light of recent developments in California battery storage contracting. Utilities such as PG&E and Southern California Edison, together with Community Choice Aggregators, have increasingly moved toward "resource adequacy plus financial settlement" agreements.
Under these contracts, utilities compensate battery owners for providing resource adequacy (RA) capacity and also pay a fixed amount. In return, battery owners are required to settle financially based on the "top-bottom" (TB) value, which represents the spread between peak and off-peak electricity prices.
Miller explained that the battery owner assumes responsibility for a variable payment. He described the arrangement as a financial swap in which the owner pays an amount tied to the TB value while the utility provides a fixed payment.
He added that if operators earn 100% of that TB value, the outcome is essentially revenue neutral. If they exceed that amount, they generate additional earnings beyond the utility contract. However, if they earn less than the TB value, the long-term agreement creates an obligation that prevents them from capturing the full revenue available.
According to Gridmatic's findings, the company's operated asset—the 100MW/400MWh Caballero BESS located in San Luis Obispo County and owned by Fengate Asset Management and Alpha Omega Power (AOP)—achieved 141% of its TB value, the highest ratio recorded in the study. In contrast, many of the other battery systems analyzed produced results below the 100% level.
Gridmatic has operated battery storage assets within CAISO since 2024 and in ERCOT since 2023. The company is now evaluating whether to extend the same analytical methodology to additional electricity markets, although the amount of available data differs from one region to another.
The company has previously released comparable analyses covering Texas' ERCOT market, where higher levels of data transparency made the research process more straightforward. The successful use of the shadow clearing methodology in CAISO indicates that similar studies could also be carried out in markets where disclosure at the individual resource level is more limited.
Originally reported by Energy Storage News on Jul 21, 2026.
