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Full-Text Articles in Engineering
Estimating Smart Wi-Fi Thermostat-Enabled Thermal Comfort Control Savings For Any Residence, Abdulelah D. Alhamayani, Qiancheng Sun, Kevin Hallinan
Estimating Smart Wi-Fi Thermostat-Enabled Thermal Comfort Control Savings For Any Residence, Abdulelah D. Alhamayani, Qiancheng Sun, Kevin Hallinan
Mechanical and Aerospace Engineering Faculty Publications
Nowadays, most indoor cooling control strategies are based solely on the dry-bulb temperature, which is not close to a guarantee of thermal comfort of occupants. Prior research has shown cooling energy savings from use of a thermal comfort control methodology ranging from 10 to 85%. The present research advances prior research to enable thermal comfort control in residential buildings using a smart Wi-Fi thermostat. "Fanger's Predicted Mean Vote model" is used to define thermal comfort. A machine learning model leveraging historical smart Wi-Fi thermostat data and outdoor temperature is trained to predict indoor temperature. A Long Short-Term-Memory neural network algorithm …
Toward Cost-Effective Residential Energy Reduction And Community Impacts: A Data-Based Machine Learning Approach, Adel Naji, Badr Al Tarhuni, Jun-Ki Choi, Salahaldin Alshatshati, Seraj Ajena
Toward Cost-Effective Residential Energy Reduction And Community Impacts: A Data-Based Machine Learning Approach, Adel Naji, Badr Al Tarhuni, Jun-Ki Choi, Salahaldin Alshatshati, Seraj Ajena
Mechanical and Aerospace Engineering Faculty Publications
Many U.S. utilities incentivize residential energy reduction through rebates, often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating assets. The assumption built into incentive programs is that the least efficient residences will be more likely take advantage of the rebates. This, however, is not always the case. The main goal of this study was to determine the potential for prioritized incentivization, i.e., prioritizing incentives that deliver the greatest energy savings per investment through an entire community. It uses a data mining approach that leverages known building …
Automated Residential Energy Audits Using A Smart Wifi Thermostat-Enabled Data Mining Approach, Abdulrahman Alanezi, Kevin Hallinan, Kefan Huang
Automated Residential Energy Audits Using A Smart Wifi Thermostat-Enabled Data Mining Approach, Abdulrahman Alanezi, Kevin Hallinan, Kefan Huang
Mechanical and Aerospace Engineering Faculty Publications
Smart WiFi thermostats, when they first reached the market, were touted as a means for achieving substantial heating and cooling energy cost savings. These savings did not materialize until additional features, such as geofencing, were added. Today, average savings from these thermostats of 10–12% in heating and 15% in cooling for a single-family residence have been reported. This research aims to demonstrate additional potential benefit of these thermostats, namely as a potential instrument for conducting virtual energy audits on residences. In this study, archived smart WiFi thermostat measured temperature data in the form of a power spectrum, corresponding historical weather …
Using Smart-Wifi Thermostat Data To Improve Prediction Of Residential Energy Consumption And Estimation Of Savings, Abdulrahman Alanezi, Kevin P. Hallinan, Rodwan Elhashmi
Using Smart-Wifi Thermostat Data To Improve Prediction Of Residential Energy Consumption And Estimation Of Savings, Abdulrahman Alanezi, Kevin P. Hallinan, Rodwan Elhashmi
Mechanical and Aerospace Engineering Faculty Publications
Energy savings based upon use of smart WiFi thermostats ranging from 10 to 15% have been documented, as new features such as geofencing have been added. Here, a new benefit of smart WiFi thermostats is identified and investigated; namely, as a tool to improve the estimation accuracy of residential energy consumption and, as a result, estimation of energy savings from energy system upgrades, when only monthly energy consumption is metered. This is made possible from the higher sampling frequency of smart WiFi thermostats. In this study, collected smart WiFi data are combined with outdoor temperature data and known residential geometrical …