Subtasks

The following activities will be performed through 3 Subtasks:

Subtask A: Applications and Case Studies

A.1       Mapping and classification of TES applications

• A search and mapping will be conducted of currently active, commercially available TES technologies across temperature ranges and energy sectors/storage capacities (e.g. industry, buildings, data centers, households). The goal is to provide a practical and up-to-date overview of what is on the market today.

A.2   Collection and Analysis of Case Studies

• An Excel-based template will be developed and circulated to Task participants and industry partners to collect structured data on their active TES-related projects. From the mapped projects, a subset of case studies will be selected for detailed analysis. Selection criteria may include the level of innovation, potential for replication, relevance to key industrial sectors, and geographic or climatic diversity.

A.3    Synthesis and Knowledge Sharing

• Based on A1 and A2 findings, standardized data sheets will be developed summarizing different TES application categories (e.g., high-temperature industrial storage, district heating with latent TES). A white paper will be developed with industry, synthesizing the findings from the subtask into strategic recommendations. Annual webinars will invite selected partners to present their case studies. Each webinar may be thematic (e.g., industrial TES, building sector).

Subtask B: Design

B.1       Industry and literature review of past and current design approaches

• As a starting point, the Subtask will survey approaches already used by various stakeholders when it comes to the design process of TES components.

B.2       Round Robin TES Experimental Characterization

• Characterization of the TES components is essential for the understanding, generation and validation of any design approaches. However, a universal approach to the experimental characterization has not been developed and accepted by the community, and it has not been demonstrated how accurate such a characterization would be when performed in various labs around the world. In parallel to this, numerous countries now have certification guidelines for the testing of TES components or are currently developing them. How similar, accurate and valid are all those national guidelines? Therefore, taking advantage of the group of experience researchers making up this Task, a round robin testing related to the thermal/energy characterization of TES components is a natural step to be investigated.

B.3       Design metrics and design rules

• The work in subtask B.3 is extremely relevant and forms the research backbone of a few of the labs of the Task participants. It is also a task that is far from easy and can be helped by the sharing of data and the collective contributions of a larger group of researchers (as opposed to each researcher in isolation in their respective lab).

B.4       Artificial Intelligence in TES component design

• Artificial Intelligence (AI) is becoming a tool used in more and more areas, and various AI-based approaches could play a significant role in speeding up TES component designs. However, most AI models need to be trained on data already available to increase their predictive capabilities. The AI work in this subtask will float above Subtasks B.1 and B.3, part of the literature review and discussions with stakeholders will look at AI uses currently, and AI as a design tool will clearly play a role in the metrics and rules discussion. Results from the round robin test in Subtask B.2 will also offer the opportunity to further train AI approaches considered.

Subtask C: State of Charge

C.1       Update of inventory – measurement techniques and proof of concepts

•  Collection of further methods for PCM, with focus on proof-of-concept and applications and TCM, with focus on material bulk response and proof-of-concept, as well as measurement techniques for high-temperature sensible storage, which have been developed by the participating organization, or which have been published in literature. Proof-of-concepts based on small-scale experiments, demonstration projects as well as with numerical models on a component level (“digital twin”) and on a system level will be collected

C.2       Application-oriented SoC determination

• For TCM storage, the focus is on measurement techniques being applied on storage prototypes. For PCM and sensible TES the focus is on SoC determination in prototype and pilot TES in relation to system controls. In this context, AI tools can also be explored to short-cut the identification of the correlation between measurement signal and storage prototype SoC determination