Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Jared Williams, Senior Casey Troxler, Graduate Student
Lead Presenter's Name
Jared Williams
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Dr. Sandra Boetcher & Dr. Rafael Rodriguez
Abstract
As decarbonization of the power grid increases with renewable power generation sources, the intermittent nature of power generation also increases. With intermittent sources of power, there is a greater chance of excess power at specified parts of the day. To ensure that all power generated can be used rather than lost, ways to store excess energy need to be investigated. Currently the most prevalent form of energy storage is through electrochemical batteries. Electrochemical batteries however, are expensive and require added infrastructure for deployment. An alternative to electrochemical batteries is thermal energy storage (TES), that can aid in reducing buildings heating ventilation and air conditioning (HVAC) loads on the power grid. TES is commonly conducted by using phase change materials (PCM) which melt or solidify at specified temperatures. By taking advantage of the latent heat energy stored in the PCM, this energy can be used to condition a space later, reducing the peak thermal loads for a building. One way to use PCM for TES is through tube bank heat exchangers, which assembles a bundle of PCM encapsulated tubes in a particular spacing. Once the tube bank is configured, air would then pass over the tube bank exchanging heat with the PCM encapsulated tubes. This project focuses on optimizing the tube bank configuration to ensure the time taken to charge & discharge the TES would allow for the thermal battery to be used daily. Predictions for the heat exchangers performance is made through an analytical model while varying specified conditions including the tube bank spacing, encapsulation methods, the specified PCM used, and the incoming air temperatures. By modifying these conditions in the analytical model, estimations can be made before a physical test bed is produced for validation.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
Yes, Spark Grant
Modeling Predictions of the Performance of Tube Bank Heat Exchangers with Phase Change Materials
As decarbonization of the power grid increases with renewable power generation sources, the intermittent nature of power generation also increases. With intermittent sources of power, there is a greater chance of excess power at specified parts of the day. To ensure that all power generated can be used rather than lost, ways to store excess energy need to be investigated. Currently the most prevalent form of energy storage is through electrochemical batteries. Electrochemical batteries however, are expensive and require added infrastructure for deployment. An alternative to electrochemical batteries is thermal energy storage (TES), that can aid in reducing buildings heating ventilation and air conditioning (HVAC) loads on the power grid. TES is commonly conducted by using phase change materials (PCM) which melt or solidify at specified temperatures. By taking advantage of the latent heat energy stored in the PCM, this energy can be used to condition a space later, reducing the peak thermal loads for a building. One way to use PCM for TES is through tube bank heat exchangers, which assembles a bundle of PCM encapsulated tubes in a particular spacing. Once the tube bank is configured, air would then pass over the tube bank exchanging heat with the PCM encapsulated tubes. This project focuses on optimizing the tube bank configuration to ensure the time taken to charge & discharge the TES would allow for the thermal battery to be used daily. Predictions for the heat exchangers performance is made through an analytical model while varying specified conditions including the tube bank spacing, encapsulation methods, the specified PCM used, and the incoming air temperatures. By modifying these conditions in the analytical model, estimations can be made before a physical test bed is produced for validation.