Evaluation of cooling setpoint setback savings in commercial buildings using electricity and exterior temperature time series data

Khalilnejad, Arash; French, Roger H.; Abramson, Alexis R.

doi:10.1016/j.energy.2021.121117

Evaluation of cooling setpoint setback savings in commercial buildings using electricity and exterior temperature time series data

Journal Article · Tue Jun 08 00:00:00 EDT 2021 · Energy

DOI:https://doi.org/10.1016/j.energy.2021.121117· OSTI ID:1977093

Khalilnejad, Arash ^[1]; ^[2]; ^[2]

Case Western Reserve University, Cleveland, OH (United States); OSTI
Case Western Reserve University, Cleveland, OH (United States)

Commercial buildings account for a significant amount of total energy produced in the US, and the Heating Ventilation and Cooling (HVAC) systems are one of the most significant components of their overall consumption. In this study, we proposed a new data-driven approach to evaluate HVAC cooling systems in commercial buildings and identify savings opportunities. The focus is an investigation of the impact of thermostat setpoint setback but using only whole building, electricity data taken at 15-min intervals for the analysis. We conducted a comparative study of setpoint setback characteristics on 432 commercial buildings with 5 building usage types across the United States. To accomplish this, both piecewise and Random Forest regression algorithms were employed using electricity and exterior temperature datasets to identify operational characteristics and the effective setpoints in the building to determine the corresponding savings opportunities. Both occupied and unoccupied time periods were studied across cooling degree days (CDD), when air conditioning is typically operational. Here the results show that in commercial buildings, on average, cooling systems account for 9.5% of total consumption. When a one degree setback during the cooling season is applied, an average of approximately 1.1% of annual consumption is achieved; retail and office buildings demonstrate the highest potential for savings. Additionally, we identified that the number of cooling degree days and base to peak ratio (BPR) are the most important variables for predicting the magnitude of the consumption of cooling systems.

View Accepted Manuscript (DOE)

Research Organization:: Case Western Reserve University, Cleveland, OH (United States)

Sponsoring Organization:: Ohio Third Frontier; USDOE; USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0000668

OSTI ID:: 1977093

Alternate ID(s):: OSTI ID: 1797319
OSTI ID: 23205111

Journal Information:: Energy, Journal Name: Energy Journal Issue: C Vol. 233; ISSN 0360-5442

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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