Award Date

5-1-2025

Degree Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Electrical and Computer Engineering

First Committee Member

Yahia Baghzouz

Second Committee Member

Emma Regentova

Third Committee Member

Pushkin Kachroo

Fourth Committee Member

George Rhee

Number of Pages

78

Abstract

The recent increase in energy production from renewable resource introduces a new challenge in managing and maintaining balance between electricity supply and demand, due to uncertainty and variability of wind speed and solar irradiance. To address this growing problem, demand-side management, such as Demand Response (DR) programs, is employed to adjust power consumption. Residential air conditioners (ACs) are the most suitable candidates for DR, due to their intensive power consumption and inherent thermal inertia that allows flexibility in their operations (by adjusting their set-point temperatures) without sacrificing customer comfort. Most prior research on AC load models assumes that such a load draws constant rated power when the unit is powered on. However, the power consumption depends on outdoor temperature. Furthermore, previous works focused on houses with a single AC load. However, a significant fraction of the homes, especially two-story buildings, have 2 AC units. Unlike AC cycling behavior observed in single-zone houses, where the duty cycles of an AC unit are relatively constant, the two-zone case exhibits varying duty cycles due to the air movement through the stairwells and the different temperature set-points. This thesis proposes an improved RC model of an AC load that takes into account the power consumption’s dependence on the ambient temperature. The model is then extended to a premise with two AC units, by coupling the air temperature dynamics between zones. Model parameters will be estimated using recorded historical data of some local homes. Some applications, including customer bill management under Time-of-Use (TOU) electricity rates and potential participation in grid services (ramping grid service, peak load management), will be assessed through time-series numerical simulation using local weather data.

Keywords

air conditioning; modeling; peak load management; power; time of use rate

Disciplines

Electrical and Computer Engineering

File Format

pdf

File Size

2037 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Download


Share

COinS