Master of Science in Engineering (MSE)
First Committee Member
Second Committee Member
Third Committee Member
Joon Soo Lee
Fourth Committee Member
Number of Pages
Heavily populated metropolitan areas located in cooling-dominated climates, as are found in the Desert Southwest, pose a challenge to electrical utilities that service these areas. During the late afternoons of the summer months, residents of these metropolitan areas require larger than normal amounts of power to run their homes' air conditioning systems, at significant expense to the utilities. In the study reported here, interior temperature and power consumption data, accumulated over the course of a year and a half from seven houses within a Las Vegas neighborhood, are used to develop a predictive black-box statistical model for residential thermal transience. The model is able to predict when a collection of homes' air conditioners will either cycle on or off based on multiple measured inputs. When used in conjunction with a series of residential thermostats located in roughly the same area, the model can be used as a predictive controller to manipulate those homes' thermostats' setpoints in an attempt to level the homes' electrical demand by preventing the air conditioners from all running simultaneously, and alleviate utility expenses associated with producing power during peak demand periods.
Controls; Demand; Dwellings – Energy consumption; Electric power consumption; Nevada – Las Vegas; Peak; Peak load; Peak load – Forecasting; Response; Shifting; Smart-Grid; Smart power grids; Southwest; New
Engineering | Mechanical Engineering | Oil, Gas, and Energy | Power and Energy
University of Nevada, Las Vegas
Cross, Andrew, "Development of a Black-Box Transient Thermal Model for Residential Buildings" (2014). UNLV Theses, Dissertations, Professional Papers, and Capstones. 2175.
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