Sustainability through Intelligent Scheduling of Electric Water Heaters in a Smart Grid

• Published in: 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech) pp. 848 - 855
• Main Authors: Booysen, M.J., Cloete, A.H.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-08-2016
• Subjects: Big data analysis; Cloud control; Data models; Electric water heaters; Energy measurement; Load modeling; Mathematical model; Resistance heating; Temperature measurement; Water heating
• DOI: 10.1109/DASC-PICom-DataCom-CyberSciTec.2016.145

The ever-increasing demand for energy and resurgence in communications technology are fueling research and development in smart grid and demand-side management solutions. Water heating is responsible for 32% of domestic energy use. Given the usage patterns, the capacitive nature of water heaters, and the standing losses when hot, these devices are good candidates for schedule control to affect energy savings. Although effort has been made in investigating the benefits of scheduling, doubts remain, and research has been limited to theoretical models, constricted lab experiments. The use of smart grid technologies now enable large natural experiments to demonstrate the effects of personalised schedule control in actual households. This paper presents such an experiment, in which water heaters were equipped with ETSI-compliant smart grid technology to measure and understand the impact on energy of schedule control on electrical water heaters. A thermal model and lab experiment are used to validate the energy results, while a control and treatment group are used in the field experiment to control for the impact of seasonal and consumption variation. The results demonstrate a 29% energy saving, comprised of reduced standing losses and usage enthalpy.