Masters Theses

Date of Award


Degree Type


Degree Name

Master of Science


Engineering Science

Major Professor

Dr. Fran Li

Committee Members

Dr. Kai Sun, Dr. Hector Pulgar


Life in the modern era is inextricably tied to energy and the unending, ever-growing need for more. The technologies that drive society, in fields such as communication, infrastructure, and heavy industry, are dependent on that electrical energy being reliable and readily available. This places an extreme importance on the power generation sector as a function of meeting the demand required for stability. However, as seen with increased climate volatility due to misused or otherwise mismanaged resources in the heavy industry, and the uncertain and variable renewable energy generation; there must also be ecological as well as economic consideration when discussing modern energy. Therefore, a balance between sustainability and energy demand must be met, to increase the desire for better use of energy resources.

This thesis focuses on an application of a demand response (DR) program that may increase the performance of energy resources while also maximizing monetary savings for end-users in the commercial sector. This DR may provide support for the uncertain and intermittent nature of renewable generation. By targeting Heating, Ventilation, Air Conditioning, and Refrigeration loads (HVAC-R) utilities have access to non-critical loads that they may be able to shed during times of high energy demand. This allows for the allocation of less resources during peak hours, which may lead to less strain the electrical grid and could increase the threshold for which additional energy resources will need to be constructed.

Based on relay to substitute the analog parts of a refrigerator and a development PC to drive the control logic a closed loop, Automated Demand Response (ADR) is implemented to utilize both static and dynamic Time of Use (TOU) events as well as Critical Peak Pricing (CPP) events. This enables the end user to respond to two types of unique events, resulting in potential increased energy efficiency, and monetary savings for the end user via load shifting.


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