Performance characterization of thermal energy storage devices for use in high efficiency HVAC systems by Alanna Cooney

Alanna Cooney

UC Berkeley | Bailey & Chris Meyer

My current research focuses on developing predictive tools to optimize the use of thermal storage batteries in building heating, ventilation, and air conditioning (HVAC) systems. Thermal batteries are used to offset peak heating and cooling loads by storing latent energy in a phase change material. Adding thermal storage to HVAC systems leads to energy savings, a broader use of renewables, and reduces electrical grid inefficiency.


Thermal storage batteries containing phase change material can be used to offset peak heating and cooling loads in buildings using latent energy storage. Some benefits of using thermal storage include energy savings due to operating baseline HVAC equipment when they are most efficient, broadening the use of renewable energy, reducing electrical grid inefficiency, and shifting loads to take advantage of local time-of-use tariffs. Experiments were performed in order to characterize the performance of thermal batteries under a variety of operating conditions to better understand how they would function in a real system. The next steps of this research include using the experimental data to develop predictive tools using machine learning methods such as neural networks and genetic algorithms in order to optimize the use of thermal storage in HVAC systems.


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