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 2015–16 heating season indicate that the objectives are largely achieved. It is estimated that on an annualised and weather-adjusted basis most of the users have consumed less electricity than before intervention and their costs are less on the trial tariffs. Critical factors for success of this form of system are identified, particularly the need to facilitate hands-on control of heating by thrifty users and the importance of an effective and sustained user engagement programme when introducing the technology, to ensure users gain confidence through a readily-accessible source of support and advice.

[1]  Alex Summerfield,et al.  The reality of English living rooms - A comparison of internal temperatures against common model assumptions , 2013 .

[2]  Bruno Murari,et al.  Smart power , 1988, ESSCIRC '88: Fourteenth European Solid-State Circuits Conference.

[3]  Denis Fan,et al.  Exploring smart grid possibilities: a complex systems modelling approach , 2015 .

[4]  Marko Aunedi,et al.  Benefits of flexibility from smart electrified transportation and heating in the future UK electricity system , 2016 .

[5]  David J. C. MacKay Sustainable Energy - Without the Hot Air , 2008 .

[6]  Marko Aunedi,et al.  Smart control for minimizing distribution network reinforcement cost due to electrification , 2013 .

[7]  Stefan Bouzarovski,et al.  A global perspective on domestic energy deprivation: Overcoming the energy poverty-fuel poverty binary , 2015 .

[8]  Peter Boait,et al.  Accommodating renewable generation through an aggregator-focused method for inducing demand side response from electricity consumers , 2013 .

[9]  Hamed Mohsenian Rad,et al.  Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments , 2010, IEEE Transactions on Smart Grid.

[10]  Matti Lehtonen,et al.  Risk-constrained framework for residential storage space heating load management , 2015 .

[11]  G. Ault,et al.  Supporting high penetrations of renewable generation via implementation of real-time electricity pricing and demand response , 2010 .

[12]  P. Tuohya,et al.  Orchestration of Renewable Generation in Low Energy Buildings and Districts Using Energy Storage and Load Shaping , 2015 .

[13]  Sarah C. Darby Balancing the system comfortably? Electric storage heating and residential demand response , 2016 .

[14]  Therese Peffer,et al.  How people use thermostats in homes: A review , 2011, Building and Environment.

[15]  Sarah C. Darby,et al.  Metering: EU policy and implications for fuel poor households , 2012 .

[16]  Sarvapali D. Ramchurn,et al.  Agent-based control for decentralised demand side management in the smart grid , 2011, AAMAS.