How much energy can optimal control of domestic water heating save?

• Published in: Energy for sustainable development Vol. 51; pp. 73 - 85
• Main Authors: Booysen, M.J., Engelbrecht, J.A.A., Ritchie, M.J., Apperley, M., Cloete, A.H.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-08-2019
• Subjects: Domestic energy saving; Electric water heater; Optimal control; Scheduled control; Temperature control; Domestic energy saving; Electric water heater; Temperature control; Optimal control; Scheduled control
• ISSN: 0973-0826
• DOI: 10.1016/j.esd.2019.05.004

Scheduled control of domestic electric water heaters, designed to cut energy use while minimising the impact on users' comfort and convenience, has been fairly common for some time in a number of countries. The aim is usually load-shifting (by heating water at off-peak times) and/or maximising time-of-use pricing benefits for users. The scheduling tends not to be linked to actual hot water usage and depends largely on stored thermal energy. Heat losses therefore tend to be greater than if the heater ran without a break. The effect of such a control strategy is thus to worsen the energy loss and in most cases increase greenhouse gas emissions. Many developing countries have flat-pricing (no time-of-use incentives) and rely heavily on energy from fossil fuels, making these considerations even more pressing. We explore three strategies for optimal control of domestic water heating that do not use thermostat control: matching the delivery temperature in the hot water, matching the energy delivered in the hot water, and a variation of the second strategy which provides for Legionella sterilisation. For each of these strategies we examine the energy used in heating, the energy delivered at the tank outlet, and issues of convenience to the user. The study differs from most previous work in that it uses real daily hot-water usage profiles, ensures like-for-like comparison in delivered energy at the point of use, and includes a daily Legionella avoidance strategy. We tackled this as an optimal control problem using dynamic programming. Our results demonstrate a median energy saving of between 8% and 18% for the three strategies. Even more savings would be realised if intended and unintended usage events are correctly classified, and the optimal control only plans for intended usage events.
•Optimal scheduled control of electric water heater for known water profiles evaluated•Scheduled control with temperature-matching achieved median of 7.9.•Scheduled control with energy-matching achieved median of 17.8.•Energy matching with Legionella sterilisation achieved median of 13.1.•Savings resulted from reduced standing losses and reduced usage losses.