Aaron K. Ball

An empirical method for estimating thermal system parameters based on operating data in smart grids

An experimental methodology was developed for online system identification of a thermal system or heated space. In this setting, the intelligent controller detects system parameters during normal operation and adapts its performance accordingly. The ultimate goal is to demonstrate that load leveling with demand side management can be used to reduce peak power consumption while maintaining residential room temperatures at a comfortable level. A prototype enclosure was built and equipped with a heater and thermal measuring equipment. Data was collected during a 17 hour temperature regulation experiment using a bang-bang controller similar to those commonly used for residential heating control. First and second order mathematical models were developed for thermal system identification. The mathematical models utilized the collected temperature data to estimate the net thermal resistance and capacitance using system identification techniques. Results showed the second order model to match the real system characteristics reasonably well. It was found that even for a small prototype enclosure, the estimated thermal parameters showed quite large values of thermal capacitance which can be a great asset for demand side management and control applications in a smart grid. The system identification method developed here is an important step toward the development of intelligent controllers.

An Investigation of Parametric Load Leveling Control Methodologies for Resistive Heaters in Smart Grids

The main goal in this study is to demonstrate that load levelling with demand side management in smart grids can be achieved to reduce peak power consumption while maintaining residential room temperatures at a comfortable level. A prototype enclosure was built and equipped with a heater and thermal measuring equipment. Data was collected during a 17 hour temperature regulation experiment using a traditional on-off (bang-bang) controller similar to those commonly used for residential heating control. A second order mathematical model was utilized to estimate the net thermal resistances and capacitances using system identification techniques at two different temperature set points. The enclosure system was used to determine if peak power could be reduced by slowly varying loads utilizing a different type of controller. Two different linear control techniques (using K-Factor and PI approaches) and the associated power electronics circuitry were implemented and tuned. Both controller systems successfully leveled the load and reduced the peak power demand.

Global Warming in Asheville, North Carolina

As predicted by Svante Arrhenius in 1896, global warming is taking place as evidenced by documented rises in average sea level of about 1.7 mm/year during the 20th century. There have been naturally occurring cycles of global warming and cooling throughout the history of the world. Much has been written about the catastrophe that global warming would present to humankind, but the effects of elevated atmospheric carbon dioxide concentrations upon ambient annual mean temperatures at the local level in western North Carolina are not easily recognized at this time. Observation of annual mean temperatures in western NC did not immediately indicate a detectable temperature increase over the period of analysis. However, annual weather data for Asheville, North Carolina from 1965 until 2006 indicated an upward trend in annual mean surface temperatures of about 1.3°F (0.72°C) while global atmospheric carbon dioxide concentrations have risen about 62 ppm. This paper will present an examination of regional ambient annual surface temperature trends in western North Carolina relative to global atmospheric carbon dioxide concentrations. The focus will be on analysis of data to determine cyclical patterns.

Residential Water Heating Dehumidifier (WHD) With Devoted Dehumidification

A new a dual-service dehumidifier water heater (WHD) appliance is being researched and developed by the authors. Prior research on a similar appliance, a heat pump water heater (HPWH), has demonstrated the unit’s increased performance and energy saving, and through collaboration, significant progress has been made toward developing the WHD into a potentially marketable product. The primary energy use in residential households is space conditioning (49%), and the second major energy use is hot water consumption. In DOE’s 2004 Buildings Data Book, 15.5 percent of residential energy utilization is consumed by water heating (DOE 2004, Table 1.2.3). The two major types of residential water heaters are direct gas fired (~55%) and electric resistance (~45%) (DOE 2004, Appliance Magazine 2005). The maximum efficiency of a standard electric resistance water heater is 1 (100%), and progress has been made to increase the efficiency of the current standard heaters to approximately 95 percent (DOE 2004, Table 5.10.6), which is roughly the maximum available with today’s technology. However, if the standard system is replaced by a Heat Pump Water Heater (HPWH), the performance can be increased by 140 percent (Zogg and Murphy 2004). The WHD operates as a HPWH while heating water and as a dedicated dehumidifier when water heating is not necessary. This paper presents the general design and laboratory testing results of a WHD. Preliminary performance data reveal coefficient of performances (COP) of approximately 2.2 during water heating. Further, market analysis has revealed that a potential need for this new technology is in regions with high humidity (Ashdown et al. 2004). These regions are primarily in the Northeast, Southeast and some coastal areas of the U.S. Current HPWH units do not have dedicated dehumidification and have a very small share of the residential water heat market. Of the 9.55 million residential water heaters sold in 2003 only about 2,000 of them were HPWHs (DOE 2004, Table 5.10.15).Copyright