Optimization of Thermal Energy Storage Sizing Using Thermodynamic Analysis
The aim of this thesis is to examine the effect that Thermal Energy Storage (TES) sizing has on a building’s ability to meet heating and cooling demands in an energy and cost efficient manner. The focus of the research is the quantification the effects of TES for system sizing and boiler cycling. Re...
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| Format: | Others |
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ScholarWorks@UMass Amherst
2020
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| Online Access: | https://scholarworks.umass.edu/masters_theses_2/951 https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=2008&context=masters_theses_2 |
| Summary: | The aim of this thesis is to examine the effect that Thermal Energy Storage (TES) sizing has on a building’s ability to meet heating and cooling demands in an energy and cost efficient manner. The focus of the research is the quantification the effects of TES for system sizing and boiler cycling. Research is accomplished by modelling TES systems with various storage capacities using thermodynamic analysis. Energy costs are subject to increase during peak usage periods due to a limited supply of energy. Peak heating and cooling periods also force thermal systems to be sized for loads that are only experienced for a small fraction of the year leading to poor efficiencies and frequent cycling during off peak times of year. TES introduces the capability to mitigate this issue by shifting peak thermal loads from one period to another, theoretically reducing the minimum necessary boiler or chiller capacity for a given system and potentially improving the efficiency of 4 thermal systems. The scope of this research is to model the operation of thermal systems with varying storage capacities in order to quantify these capabilities with respect to capacity and cycling. This is accomplished with modelling in Transient Systems Simulation Program (TRNSYS). In this software, a simple heating loop and cooling loop are independently considered and subjected to hourly load data extrapolated from heating and cooling load data originating from a retirement community in Massachusetts. The model built is intended to be robust enough to be easily applied and adapted to assess similar problems with energy storage capacity sizing. |
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