BatterySimm™ identifies configurations and operating strategies to maximize value. BatterySimm’s advanced algorithms help developers and utilities define and implement strategies to co-optimize the joint value for both energy and ancillary services markets.
Get the insight you need to make the right decisions.
BatterySimmTM has three different modules to maximize project value through any point of the project life:
Maximizing value means
optimizing battery charge and discharge strategy across Day-Ahead and Real-Time energy and ancillary service markets under real-life conditions, inclusive of physical battery performance attributes over time.
Optimal sizing for energy cycling capabilities and duration specifications
Valuate projects under both perfect and imperfect foresight of energy and ancillary service prices
Determine optimal operating strategies for ISO bidding and integrated utility operations
Features of BatterySimmTM
Finds the most cost-effective battery configuration for a given node or utility system
Add batteries to renewable projects to realize higher Day-Ahead prices and take advantage of investment tax credit
Track daily performance and invoke self-learning routines to improve profitability
Discovers the optimal dispatch strategy by co-optimizing between energy and ancillary services
Generate location and project specific operating strategies to maximize profitability
Captures realistic revenues of the asset given imperfect foresight
BatterySimmTM Modeling Features
BatterySimm™ offers superior modeling of market price dynamics, and operational constraints, providing comprehensive resource valuation and optimal operation strategy.
Project developers, EPCs, capital funds, utilities, and market operators will benefit from the analytic insights of BatterySimmTM. Find and execute the right strategy for any battery and storage technology.
BatterySimmTM pairs an in-depth representation of storage devices with forecasting and analytics of market prices, including predictions of price spikes and trends in volatility. This allows the mixed-integer linear program to solve for optimal dispatch between energy ancillaries in day-ahead and real-time markets under a variety of optimization policies to characterize both realistic revenue and the value of better forecasting.
BatterySimmTM has been applied by over a dozen utilities and developers alike to identify and execute optimal storage configurations and operating strategies.
Due to its MODULAR NATURE, Ascend Analytics software can be rapidly deployed.
Our dedicated deployment team will provide a turn-key-solution, minimizing impacts to your staff.
Ascend offers the option of deploying to client sites, or a robust HOSTED ENVIRONMENT with dedicated hardware, complete database and software support.
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