Research effort in analyzing the energy consumption of buildings in districts or cities is increasing as new paradigms of distributed energy production and sharing are spreading. In this work, the Urban Building Energy Model of the Quad, an area of the University of California Davis campus, is presented, validated, and analyzed for possible actions to reduce the district cooling energy consumption. Energy conservation measures involve buildings' air handling units and district chilled water generation. To investigate this system, a district cooling networks module has been developed in EUReCA, the Urban Building Energy Modeling tool used for the analyses. The model has been validated with energy demand and temperature data from 2018 to 2020, resulting in a district cooling demand deviation lower than 7% for 2018 and 2019. Normalized Root Mean Square Error is lower than 35% for each building, proving the reliability at the hourly time scale. Systems energy reduction actions like heat recovery units' installation and heuristic control of the air supply cooling temperature are beneficial in reducing the cooling demand, and they allow a more efficient discharging of the chilled water storage, reducing the average electricity price by load shifting during peak demand.

Exploiting district cooling network and urban building energy modeling for large-scale integrated energy conservation analyses

Prataviera E.;Zarrella A.;
2024

Abstract

Research effort in analyzing the energy consumption of buildings in districts or cities is increasing as new paradigms of distributed energy production and sharing are spreading. In this work, the Urban Building Energy Model of the Quad, an area of the University of California Davis campus, is presented, validated, and analyzed for possible actions to reduce the district cooling energy consumption. Energy conservation measures involve buildings' air handling units and district chilled water generation. To investigate this system, a district cooling networks module has been developed in EUReCA, the Urban Building Energy Modeling tool used for the analyses. The model has been validated with energy demand and temperature data from 2018 to 2020, resulting in a district cooling demand deviation lower than 7% for 2018 and 2019. Normalized Root Mean Square Error is lower than 35% for each building, proving the reliability at the hourly time scale. Systems energy reduction actions like heat recovery units' installation and heuristic control of the air supply cooling temperature are beneficial in reducing the cooling demand, and they allow a more efficient discharging of the chilled water storage, reducing the average electricity price by load shifting during peak demand.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3503740
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