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Energy Storage Modeling and Simulation

Enhancing models to capture the value of energy storage in evolving power systems

The Challenge 

Decarbonizing energy systems is critical in slowing the pace of climate change. Many countries are implementing and considering a range of policies and regulations to support the transition toward zero-carbon energy systems. For instance, the U.S. government has established ambitious decarbonization goals, led by the Biden Administration’s target to produce 100% electricity from carbon-free resources by 2035. The decarbonization of power systems requires replacing carbon-intensive thermal generation resources with low- or zero-carbon generation resources, such as variable renewable energy. Energy storage (ES) will be increasingly important as it can support the integration of variable renewable energy resources and help achieve the decarbonization goals. However, analyzing the role and value of ES in power system planning and operations requires simulation tools with appropriate modeling of the physical and operational characteristics of various ES technologies.

Argonne’s Approach 

Researchers at Argonne have developed several novel approaches to modeling energy storage resources in power system optimization and simulation tools including:

  • Capturing the unique attributes of different energy storage technologies
  • Improving the decision-making of location, capacity, and duration of ES
  • Grid services (energy, ancillary services, and capacity)
  • Multi-day state-of-charge management
  • Considering the impacts of battery degradation on investments and operations
  • Optimizing energy storage scheduling across a range of different wholesale markets

By integrating these capabilities into our models and tools, such as the Argonne Low-carbon Electricity Analysis Framework (A-LEAF), our team can better quantify the value of energy storage in evolving power systems. In addition to advancing the state-of-the-art of energy storage modeling, we are also able to apply our models to analyze the performance of various proposed real-world storage projects under different projected future electricity grids and system conditions.