A primary approach for addressing climate change is putting greater emphasis on the use of renewable sources to address increasing global demand for energy. However, one of the key limitations facing power generation from renewable energy is balancing energy supply with demand. Technologies such as wind and solar often produce energy intermittently, varying by time of day and season. The mismatch between the supply of renewable energy and the demand for power as well as the lack of efficient energy storage media can limit the implementation of sustainable, low-carbon technologies. Development of efficient, large-scale energy storage systems is foundational to expanding the use of renewable energy.
Aquifer thermal energy storage (ATES) is a technology that can provide large-scale seasonal storage of cold and heat in natural underground sites. ATES relies on pumping heated (or cooled) fluids into the subsurface and then extracting those fluids for use during peak demand. However, all sites are not equal candidates for ATES systems. Before a site is selected, it must be evaluated to determine if it meets certain criteria, including whether it can maintain the necessary temperatures and be protective of underground resources.
HGL has expertise in developing models that can simulate the coupled-fluid/heat flow in highly heterogenous reservoirs to evaluate potential ATES system sites. This expertise can also be applied to determining the optimal location of system components for peak performance.
HGL’s PBMO™-ATES can optimize ATES system design that by simulating sites under consideration for, or currently operating with, ATES systems where the maximum temperatures are either above or below the boiling point of water.
The PBMO™ optimization application works with HGL’s physically based simulator MODFLOW-SURFACT™ (MODFLOW compatible) for the non-isothermal density-dependent fluid flow and heat transport computations. MODFLOW-SURFACT™ is the simulator of choice for these types of problems given its speed, robustness, and demonstrated ability to be used in conjunction with PBMO™.
PBMO™-ATES optimally solves design problems by characterizing the following:
- Objective functions such as energy stored or extracted as well as the reliability, resilience, and long-term sustainability of the ATES system and its ability to efficiently heat and cool facilities.
- Decision variables including number, location, and depth of injection and extraction wells along with their well-specific and time-specific operational flow rates and temperatures.
- Constraints such as well flow rates, transfer piping capacities, and building system operational requirements.
PBMO™-ATES has modules for optimizing systems operating both above and below the boiling point. The PBMO™-ATES high-temperature module is used for systems operated above the boiling point, where a multiphase flow and transport simulator is needed. This module has the same basic framework as the low-temperature module, but uses the COMPFLOW code, which is specifically designed to perform multiphase, non-isothermal-density dependent fluid flow and heat transport simulations. COMPFLOW is the simulator of choice for more complex problems given its speed, robustness, and demonstrated success in simulating challenging conditions.
Where a physically based numerical simulator is unavailable, but where operational data exist, the power of artificial intelligence/machine learning in the PBMO™-AI/ML module can be leveraged to develop a model of system behavior from existing data. PBMO™ then uses this information as a surrogate of a physics-based model for optimization analysis.