Making legacy thermal storage heating fit for the smart grid

Abstract

Thermal storage heaters, charged using overnight off-peak electricity, have been used for domestic space heating in the UK and other countries since the 1980s. However, they have always been difficult for consumers to manage efficiently and, with the advent of a high proportion of renewables in the electricity generation mix, the time of day when they are charged needs to be more flexible. There is also a need to reduce peaks in the demand profile to allow distribution networks to support new sources of demand such as electric vehicles. We describe a trial of a smart control system that was retrofitted to a group of six dwellings with this form of heating, with the objectives of providing more convenient and efficient control for the users while varying the times at which charging is performed, to flatten the profile of demand and make use of locally-generated renewable electricity. The trial also employs a commercially-realistic combination of a static time-of-day tariff with a real time tariff dependent on local generation, to provide consumers with the opportunity and incentive to reduce their costs by varying times of use of appliances. Results from operation over the

Smart technology in the home: time for more clarity

“…Homes and their occupants can be more obviously connected to network operation than before, through devices and processes such as time-varying tariffs, improved feedback, net metering, load capping and direct load control, in networks and grids that rely increasingly on interactions between distributed actors. Examples are the local use of microgeneration (Boait et al, 2017) or direct load control of water heating (Saele & Grande, 2011). Far from being severed from its contexts, as Robins and Hepworth (1988) envisaged, the smartened home may be more tightly connected than before, at least where energy supply is concerned.…”

“…But the main problem lies with the term 'smart' itself, weighed down with many meanings and applied to many possibilities. There will be differences in terms of user involvement and outcomes between, say, a householder who decides to programme a washing machine through a 'smart plug' so that it will not operate at peak times, one who makes storage heaters available to facilitate use of locally generated electricity (Boait, Snape, Darby, Hamilton, & Morris, 2017), one who uses a smart thermostat with 'learning' features to control the heating (Yang & Newmand, 2013) and one who adopts a fuller smart home package (Takayama, Pantofaru, Robson, Soto, & Barry, 2012). All could be described as using smart home technology, but it would be misleading to lump them all together as living in smart homes, or to assume improvements in wellbeing and environmental impact in all cases.…”

The Practice and Potential of Renewable Energy Localisation: Results from a UK Field Trial

“…Charging of these useful thermal energy stores was controlled such that user comfort requirements as expressed on the Hestia user interface were prioritized, but was otherwise optimized against a tariff-dependent signal from the database server that ensured cost effective use of local generation and the time-of-day tariff while preventing peaks in aggregate demand at tariff boundaries by randomizing dispatch of loads. This signaling and optimization methodology is fully described in [25,26] and the peaking risk that is mitigated, which has been identified in many simulation studies, is identified for example in [27,28]. An example page from the Hestia Hub display is shown in Figure 3a.…”

Analysis of the temperature distribution in a space heated by a dynamic (fan) storage heater

“…In [12], the temperature record of dwellings, heated with storage heaters, made only through one temperature sensor in the room is shown. Six users took part in the research.…”