Stacked Services

Energy Storage Systems (ESS) have become an essential component for the modern electricity grid to handle the increasing wind and solar energy integration and the emerging new challenges on the demand side such as electric vehicle charging. In recent years, many new grid energy storage solutions have reached market maturity, including advanced lithium ion batteries, flow batteries, and aqueous batteries, among others.

The ARPA-E CHARGES project is investigating better value proposition for energy storage systems in the grid energy storage markets by participating in multiple applications on the grid. The research team has developed new testing duty cycles for grid energy storage applications incorporating five different single-use applications: 1) demand charge management (DCM) for commercial and industrial applications, energy time shifting in both 2) day ahead market (DA-ETS) and 3)real-time markets (RT-ETS), 4) flexible ramping (FXR), and 5) frequency regulation (FQR). These applications are based on using market data obtained from the California independent system operator (CAISO) dated from 2015-2017.

The research team has reviewed the product designs of each individual application, and implemented time series forecasting of market prices and application demands, and developed a mixed integer linear programming (MILP) based optimization algorithm that simulates stacking of applications to maximize benefits of energy storage utilization. This stacked service duty cycles can be used as an important tool to evaluate the performance of a specific ESS under real market operations prior to deployment.

By examining the compatibility and the rules of different applications, the team is furthering this work by developing four different stacking approaches, i.e. (1) exclusive approach, (2) combined approach, (3) concurrent approach, and (4) progressive approach. The exclusive approach identifies the DA-ETS as the primary application, which is optimized and dispatched day-ahead, and then identifies the RT-ETS as the secondary application, which is dispatched at real time filling the idle gaps of the primary application. The combined approach divides a battery into two subsystems and participates in the RT-ETS and FR applications independently, to hedge the biddings. The concurrent approach examines four applications, RT-ETS, FXR, FQR, and dispatches the battery for one of the applications in each optimization interval based on economic incentives. The progressive approach examines five applications, RT-ETS, FR, FQR, DCM, and dispatches the battery in a combination of the applications in each optimization interval based on economic incentives.
In addition, this work also examined possible impact of energy market rules reform allowing energy storage to be more fully utilized, resulting in revenue improvements by relaxing some of the energy market rules, such as allowing self-dispatching in the regulation market and reducing the bidding lead-time in the real-time market. The source code and additional duty cycle data will soon be shared on this webpage, along with a detailed user manual.

Research Team: 

  • Principal Investigator - William Torre, Energy Storage Program Director, Center for Energy Research
  • Dr. Y. Shirley Meng, Professor, Nano Engineering
  • Dr. Graham Elliott, Professor, Economics
  • Dr. Antonio Tong, R&D Engineer, Center for Energy Research
  • Handa Yang, Graduate Student Researcher
  • Dan Davis, Graduate Student Researcher

Program Resources

  • Download example data set of a single application duty cycles that are ratio-fitted for a 1MW/2MWh battery system over a period of 1 year.
  • Download presentation slides from Dr. Tong's webinar: "Energy storage systems testing and modeling of stacked application duty cycles", Center for Energy Research Webinar, August 30th, 2017.

Energy Storage