Unlocking Grid Flexibility Through Thermal Energy Storage:
Insights from the HYSTORE Project

Europe’s energy transition is driving rapid growth in renewable energy sources (RES) like wind and solar, yet the variable and decentralized nature of these resources presents significant challenges for grid stability and management. The HYSTORE project, a partnership of top European research institutes including Italy’s National Research Council (CNR), has advanced the integration of Thermal Energy Storage (TES) technologies combined with advanced control algorithms to address these challenges.

A cornerstone of this effort is the recently published paper by HYstore partners titled “Demonstration of sector-coupling based on advanced Thermal Energy Storage: a Model Predictive Control framework for load-shifting and grid-balancing” (Journal of Energy Storage, 2025). This work presents a novel Model Predictive Control (MPC) framework developed and applied to the Italian energy system, which optimizes sector coupling via TES to significantly reduce renewable energy surplus and shift loads effectively.

Challenges and Methodological Approach

The increasing penetration of RES creates frequent periods of surplus electricity that cannot be immediately used or exported, causing grid congestion and reliance on fossil-fuel backup plants. Particularly pronounced in the Italian context during winter months, where there were 1,899 hours/year with surplus RES generation, amounting to 1,256GWh across the year, with peak overflow up to 2,827MWh at certain hours. This surplus energy is a prime candidate for conversion and storage as thermal energy to meet heating and cooling demands.

The HYSTORE team modeled two classes of TES:

• Short-term storage using Phase Change Materials (PCM) optimized for daily load cycles and rapid response.
• Mid-term storage with Thermochemical Materials (TCM) designed for weekly to monthly seasonal storage needs.

The novel MPC algorithm coordinates the charging (absorbing surplus energy) and discharging (meeting thermal demand) of these TES systems with the following key features:

• A 12-hour prediction horizon, balancing responsiveness with computational tractability.
• Prioritization of PCM storage for fast daily balancing and TCM for longer-term flexibility.
• Charging constrained to occur only when there is forecasted heating or cooling demand within the next 12 hours, minimizing energy waste from storage losses.
• State of Charge (SoC) limits set between 20% and 75% for PCM and 15% to 80% for TCM to ensure efficient cycling and avoid slow dynamics near full capacity.
• Binary variables enforce mutually exclusive charging or discharging within the same time step, reflecting real operational constraints.
• Conversion factors dynamically calculated for heat pumps’ Coefficient of Performance (COP) and Energy Efficiency Ratio (EER), derived from publicly available weather data and heat pump statistics, ensure accurate electrical-to-thermal energy translations.

The methodology relies exclusively on publicly available data sources such as ENTSO-E’s electricity generation and consumption datasets, Eurostat heating and cooling demand statistics, and weather databases, ensuring transparency and replicability.

Key Results from the Italian Demonstration

The modeling revealed compelling benefits of TES integration:

• 58% annual reduction in renewable energy surplus, dropping surplus hours from 1,899 to 925 annually.
• Near 100% surplus absorption during peak winter days, thanks to timely TES charging during surplus periods.
• Approximately 13% load shifting achieved by moving electricity demand for heating and cooling into low-penalty hours when surplus renewables are available.
• PCM storage exhibited about 1,099 charge and 1,057 discharge cycles annually—ideal for frequent, rapid daily cycling.
• TCM storage performed around 748 charge and 648 discharge cycles yearly, reflecting its suitability for longer-term energy storage.
• TES utilization was highest in Southern Italy, aligning with regional abundance in wind and solar resources.
• The total thermal energy storage capacities were sized approximately equal to average hourly heating demand during the heating season (~1992 MWh thermal) and cooling demand during summer (~26,890 MWh thermal), split evenly between PCM and TCM systems for balanced short- and mid-term flexibility.

An illustrative example from a three-day winter period shows TES charging predominantly during hours of RES surplus (low penalty hours) and discharging during peak demand, successfully shifting loads by around 11%. 

Both TES types cycle concurrently during surplus hours, with PCM prioritized due to its faster response. The TES systems combined provide up to six hours of stored energy supply daily within the winter season.

Implications and Future Directions

The HYSTORE project’s work underscores TES technologies as a robust, cost-effective complement to conventional electrical storage, capable of enduring high cycling frequency with minimal degradation—an important advantage over batteries for daily and seasonal grid balancing. The MPC framework is fully transparent and replicable, providing a valuable foundation for public research and policy development across Europe. 

Future research avenues identified by the authors include:

• Extending the MPC-TES framework to other EU countries to tailor TES capacity and operation to local RES profiles and grid conditions.
• Incorporating grid topology and transmission constraints for refined spatial analyses.
• Multi-objective optimization including emissions, costs, and grid stability metrics for comprehensive system assessments.
• Downscaling the MPC control to district or microgrid levels, aligning with the development of Positive Energy Districts and decentralized energy communities.
• Exploring integration of alternative TES charging sources like waste heat or district heating to further leverage seasonal flexibility.

Policy frameworks and investments that support TES deployment and digital control systems will be essential to fully unlock these benefits as Europe moves toward highly electrified, decarbonized heating and cooling sectors.

In summary, while sector coupling with advanced TES offers a proven and data-backed solution for many grid flexibility and decarbonization problems—backed by robust data from both real-world deployment and simulation—challenges remain in scaling, regulation, economic model development, and system-level digital coordination. Major investments and an integrated policy-technology approach are needed to unlock the full benefits of TES for grids saturated with intermittent renewables.

Conclusion

The HYSTORE consortium’s work, as detailed in their 2025 Journal of Energy Storage paper, presents a scientifically rigorous, data-driven approach demonstrating that sector coupling via advanced thermal storage paired with predictive control can dramatically reduce renewable energy surplus and improve grid flexibility. This opens a promising pathway to enhance renewable penetration sustainably while minimizing carbon emissions and infrastructure costs across national grids.