Thermal Energy Modeling in Microgrids

Dear Colleagues,

Due to the need for a low-carbon economy, high electric supply reliability, and the introduction of emerging technology, the deployment of microgrids is rapidly increasing. With a large acceleration in relation to renewable energy sources and with those that have an intermittent nature, there is a need to use energy storage systems (ESSs). However, typical battery-based ESSs are expensive, whereas thermal storage systems (TSSs) are a cheaper option that can meet the thermal heating demand, thereby allowing for the efficient use of diesel- and renewable-based distributed generation (DG) units. Therefore, there is a requirement to model TSSs and examine their contribution in the context of microgrid integration. As demand-side technologies such as electric vehicles, urban air mobility, and heat pumps emerge, these technologies create a transformative solution for future microgrids control and optimization. Thermal energy management becomes critical to ensuring efficient, sustainable, and resilient operations.

Microgrids can effectively integrate thermal, cooling, and electrical energy resources, as well as loads, to satisfy customer demands while providing technical, social, economic, and environmental benefits. An effective integration of microgrids with thermal energy systems requires optimization techniques that can minimize investment and risk while maximizing the deployment of the available technology. For example, with the consideration of the seasonal storage capability, the low temporal resolution of the available data can lead to inaccuracies in analysis and missed insights, potentially reducing the ability to monitor and respond to changes effectively.

Methods, recommendations, guidelines, good practice, and strategies are needed for the optimal use of technologies such as solar thermal, water heating, space heating, and thermal energy storage. A design should be available so that thermal energy storage systems can optimally store the heat, which can then be used in times when it is hardly available, such as in winter.

This Special Issue aims to publish multidisciplinary research on novel and scientific technological insights, principles, algorithms, and experiences relating to technologies, case studies, approaches, and visionary ideas to innovative or practice solutions to cope with the real-world challenges for thermal energy modeling in microgrids to support the growing demands of various infrastructure, including electric vehicles charging, urban air mobility vertiports charging, and heating and cooling.

Topics of interest include, but are not limited to, the following:

1. Thermal energy storage and management in microgrids.
2. Battery thermal regulation for microgrids.
3. Microgrid optimization for energy, cost, and emission efficiency.
4. AI and machine learning applications in thermal modeling for microgrids.
5. Renewable energy integration and waste heat recovery for microgrids.
6. Resilience strategies for microgrid-based infrastructure.
7. Thermal energy storage in microgrid design, optimization, operation, and control, involving renewable energy generation characteristics.
8. Applications, energy trading, and social issues.
9. Standards development towards successful system implementation.
10. Behavioral changes and monitoring—challenges, strategies, and lessons learned.
11. Demonstration projects.
12. Modeling and assessment of integrated multi-energy systems.

Prof. Dr. Chun Sing Lai
Dr. Yujie Yuan
Prof. Dr. Loi Lei Lai
Dr. Zhuoli Zhao
Guest Editors

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• electric thermal storage modeling
• energy management systems
• seasonal storage
• cooling, heating and power-based microgrids
• asset management
• thermal storage system
• standards development
• airport microgrid
• demonstration project
• energy trading