Assessing domestic heat storage requirements for energy flexibility over varying timescales

Abstract This paper explores the feasibility of storing heat in an encapsulated store to support thermal load shifting over three timescales: diurnal, weekly and seasonal. A building simulation tool was used to calculate the space heating and hot water demands for four common UK housing types and a range of operating conditions. A custom sizing methodology calculated the capacities of storage required to fully meet the heat demands over the three timescales. Corresponding storage volumes were calculated for a range of heat storage materials deemed suitable for storing heat within a dwelling, either in a tank or as an integral part of the building fabric: hot water, concrete, high-temperature magnetite blocks, and a phase change material. The results indicate that with low temperature heat storage, domestic load shifting is feasible over a few days. Beyond this timescale, the very large storage volumes required make integration in dwellings problematic. Supporting load shifting over 1–2 weeks is feasible with high temperature storage. Retention of heat over periods longer than this is challenging, even with significant levels of insulation. Seasonal storage of heat in an encapsulated store appeared impractical in all cases modelled due to the volume of material required.

[1]  P Pieter-Jan Hoes,et al.  Analysis of control strategies for thermally activated building systems under demand side management mechanisms , 2014 .

[2]  Luisa F. Cabeza,et al.  Review on sorption materials and technologies for heat pumps and thermal energy storage , 2017 .

[3]  Nick Kelly,et al.  Modelling the behaviour of domestic micro-cogeneration under different operating regimes and with variable thermal buffering , 2008 .

[4]  Graeme Flett,et al.  An occupant-differentiated, higher-order Markov Chain method for prediction of domestic occupancy , 2016 .

[5]  J.L.M. Hensen Energy simulation in building design , 1992 .

[6]  Sugeng Mujiyanto,et al.  Secure energy supply in 2025: Indonesia's need for an energy policy strategy , 2013 .

[7]  Joseph Andrew Clarke,et al.  Energy Simulation in Building Design , 1985 .

[8]  Joseph Andrew Clarke,et al.  Using simulation to formulate domestic sector upgrading strategies for Scotland , 2004 .

[9]  Dan Zhou,et al.  Review on thermal energy storage with phase change materials (PCMs) in building applications , 2012 .

[10]  Michael I. Gentry,et al.  Central heating thermostat settings and timing: building demographics , 2010 .

[11]  Ian Richardson,et al.  A high-resolution domestic building occupancy model for energy demand simulations , 2008 .

[12]  Ian Richardson,et al.  Assessing heat pumps as flexible load , 2013 .

[13]  Georgios Kokogiannakis,et al.  History and development of validation with the ESP-r simulation program , 2008 .

[14]  Duncan S. Callaway Tapping the energy storage potential in electric loads to deliver load following and regulation, with application to wind energy , 2009 .

[15]  Adam Hawkes,et al.  Performance assessment of tariff-based air source heat pump load shifting in a UK detached dwelling featuring phase change-enhanced buffering , 2014 .

[16]  Weiwei Miao,et al.  Online voltage security assessment considering comfort-constrained demand response control of distributed heat pump systems , 2012 .

[17]  Michael Laughton Variable Renewables and the Grid: An Overview , 2012 .

[18]  Nicolas Kelly,et al.  Historical daily gas and electrical energy flows through Great Britain's transmission networks and the decarbonisation of domestic heat $ , 2013 .

[19]  G. Flett Modelling and analysis of energy demand variation and uncertainty in small-scale domestic energy systems , 2017 .

[20]  Fabio Polonara,et al.  Domestic demand-side management (DSM): Role of heat pumps and thermal energy storage (TES) systems , 2013 .