Stacking the Deck in Your Favor with Multiple Value Streams
One of the most important benefits of a well-designed and optimized energy storage system (ESS) is the opportunity for “stacking services,” i.e. providing several functions to a distribution network and to commercial and industrial (C&I) customers on it. A broader definition of stacking services would be leveraging the same equipment, system, or process to deliver multiple benefits – most of which can be valued economically. Some examples of this are demand charge reduction; time-of-use supply charge reduction; PV self-consumption (especially with zero net export); demand response; resiliency; frequency regulation; voltage support / VAR injection; and carbon offsets.
Traditionally, this has been accomplished by ESS controllers considering one value stream at a time. These rule-based and time-partitioned approaches generally rely on a set of logic rules to determine control set-points. Modern controllers may have the ability to switch back and forth between functions, but these strategies are far less sophisticated – and less effective – when compared to real-time optimal control.
According to the Energy Storage Association, the challenge has been benefits compatibility:
“Benefits must be both technically and operationally compatible if they are to be stacked. A combination of benefits is technically compatible if the storage system has all technical characteristics necessary to perform as needed when used for all targeted benefits. Benefits are operationally compatible if no operational conflicts arise when used for the respective benefits.
It sounds complicated – and it can be – unless real-time optimal control techniques are utilized.
This is precisely the approach that Demand Energy takes with our Distributed Energy Network Optimization System (DEN.OSÔ). DEN.OS continually balances participation in multiple value streams simultaneously while considering battery degradation impacts. Put another way, DEN.OS makes it possible to optimize and deliver the greatest total value from a system given all possible opportunities – especially when they may compete with one another. The result is an ESS that can produce dramatically better economics in almost all use cases across the widest range of locations, rate structures and end user applications.
For example, on a given day, an ESS may be able to perform renewable energy firming and provide some capacity reserve support, but the amount and timing of each maneuver would be dependent on system sizing, cloud cover, and other factors on that specific day. With so many variables and options, how can a control system intelligently extract maximum value from multiple competing value streams, i.e. stack services? The answer is real-time optimal control.
How optimization is done
To make this magic happen, the DEN.OS platform uses sophisticated machine learning and artificial intelligence elements to optimize economic returns on system investment with the least degradation on the batteries. It does so by considering a given a set of initial conditions, sizing, system models, tariffs, and load forecasts. Demand Energy configures each DEN.OS implementation with information on all aspects of the customer’s energy situation (tariffs, incentives, battery chemistry and sizing, etc.) and then allows it to “watch” system activity and learn energy consumption patterns. Armed with this data, the system plans and executes on a control strategy that delivers the maximum total economic value from all value streams.
An analogous problem is determining the best altitude to fly a passenger jet from Seattle to New York while balancing passenger ride quality, fuel consumption, safety, and time of arrival. While this is happening, the winds are changing throughout the flight path and must be considered – just as changing electrical loads must be considered in an optimal control system for a building.
What about the batteries?
Everyone gets why it’s a good idea to stack services to generate maximum value from a storage system: to improve ROI. But why is it also important to optimize the batteries themselves?
First, batteries are typically the most expensive component in an energy storage system, and they wear out or degrade over time. Each battery’s chemistry and configuration has different degradation properties as a function of usage profile (i.e., all those stacked value streams). For example, lithium-ion batteries tend to degrade faster at very high states of charge, while lead-acid batteries tend to degrade faster at low states of charge.
Second, each battery’s chemistry and configuration also has different relationships between discharge efficiency and usage profile. Battery degradation can be a very complex function of battery charge/discharge rate, temperature, and state of charge. Whether to keep the battery at a low or high state of charge depends upon the battery. Our patent-pending Optimization Engine technology treats battery degradation as a negative value stream, and therefore manages degradation simultaneously with all other “opportunities,” or value streams. DEN.OS will not undertake a maneuver or usage profile using the battery unless the benefit exceeds the battery degradation cost. This process is automatic and scalable; DEN.OS will automatically use lithium batteries at lower states of charge than lead-acid batteries.
Similarly, optimizing battery storage involves knowing when to use the battery and when not to. If the energy lost during the operation exceeds the potential benefit because the round-trip efficiency is too low, why do it? Intelligent control and real-time optimization are the keys to making the right control decision and producing a better economic outcome than would be the case otherwise.
The days of deploying energy storage systems for only one purpose and one value stream are ending. With today’s evolving rate structures, market demands and incentive programs, system ROI has become a more complex – and economically beneficial calculation, based on the real possibility of stacked services. Only true real-time optimal control, such as that provided by the DEN.OS platform, can facilitate effective energy storage optimization.
If you are interested in learning more about our DEN.OS platform or how Demand Energy can help you to optimize your energy storage systems, please fill out our project request form. We look forward to discussing how DEN.OS can improve your energy storage project.