Integrated Energy Systems
Enable an economically sustainable, equitable, zero-carbon energy economy and society by creating an integrated energy system simulation capability and a validation testbed.
The term Integrated Energy Systems (IES) broadly describes a holistic approach to finding coordinated energy and economic solutions from across a wide range of energy options. These energy systems include production (solar, wind, hydro, biofuels), conveyance (electricity, thermal, hydrogen), storage (daily and seasonal), and customer-level use (buildings, transportation, industry). At present, these systems are linked, but they usually function separately or respond individually depending on a wide range of disparate system-operation goals . The inability to link these systems may limit our ability to find economically feasible zero-carbon energy solutions across sectors. We also may underappreciate the future opportunities available as vehicles, storage, and buildings become more connected to and interactive with the electricity grid.
The IES domain is broad and rapidly expanding. A wide range of active research programs fall naturally under its umbrella, including many in the Energy Technologies Area (ETA). The following examples highlight some ongoing research efforts that are elements in now-formidable research programs in ETA. This work builds upon strong ties to the ETA’s previous initiatives in sustainable transportation, urban building energy infrastructure, and grid modernization.
For more details on this initiative, take a look at ETA's 2021 Strategic Plan.
Short Term (six months – two years)
In the first year of this initiative, we will focus on (1) the breakthroughs needed to link smart buildings, local energy generation and storage, and electric vehicles, so these systems can cooperate for a common optimal goal of minimizing total carbon, with constraints on economic costs; and (2) computational methods for identifying and mitigating cybersecurity threats and other system instabilities in the electric power grid. Specific goals include:
- Development of a simulation testbed, including detailed building physics models, distributed energy resources, smart buildings, and the bulk power system. Local control loops will be included within each energy subsystem.
- Analysis of the feasible and attainable benefits of energy integration for various economic and reliability constraints.
- Artificial intelligence (AI)-driven reduced order models of energy systems suitable for testing fast co-simulation of energy systems.
- New solutions for identifying regions of stable grid operation.
- Simulation prototype for near-real time controls of multiple energy systems.
- Validation using an existing field testbed.
Medium Term (three – five years)
Based on the learnings from the Year 1 testbed data, we will develop a roadmap and a series of solutions for how physics-based models can supplement AI models to overcome the typical hurdles of using each type.
Long Term (five years and beyond)
Over five years, the team will develop the scientific toolset and a series of techniques to train and test the use of high-fidelity simulations of a microgrid with a high penetration of renewable energy. If we are successful, this work will change the ways research is conducted in the dynamic systems and controls community, realizing multi-sector decarbonization at scale and at acceptable cost.