An optimisation framework for thermal energy storage integration in a residential heat pump heating system

Applied Energy

Volumn 186, Issue , 2017, Pages 520-529

  Renaldi, R ^a   Kiprakis, A ^a   Friedrich, D ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Heat demand model; Heat pump; Mixed integer linear programming; Optimisation; Thermal energy storage

Indexed keywords

CARBON; COSTS; DISTRICT HEATING; ELECTRIC ENERGY STORAGE; ENERGY STORAGE; ENERGY UTILIZATION; FOSSIL FUELS; GAS EMISSIONS; GREENHOUSE GASES; HEAT PUMP SYSTEMS; HEAT STORAGE; HEATING EQUIPMENT; INTEGER PROGRAMMING; OPTIMIZATION; PUMPS; THERMAL ENERGY;

DISTRICT HEATING SYSTEM; HEAT DEMAND MODEL; HEAT PUMPS; MIXED INTEGER LINEAR PROGRAMMING; OPTIMISATION PROCEDURES; OPTIMISATIONS; RENEWABLE POWER GENERATION; TOTAL ENERGY CONSUMPTION;

HEATING;

ELECTRICITY GENERATION; ELECTRIFICATION; FOSSIL FUEL; FUEL CONSUMPTION; GREENHOUSE GAS; HEATING; LINEAR PROGRAMING; OPTIMIZATION; PERFORMANCE ASSESSMENT; PUMP; RENEWABLE RESOURCE; STORAGE; THERMAL POWER;

EID: 84959144692     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2016.02.067     Document Type: Article

References (41)

1. [1] DECC, Energy consumption in the UK; 2015. < www.gov.uk/government/statistics/energy-consumption-in-the-uk>.
2. [2] The Scottish Government, Energy in Scotland 2015; 2015. < www.gov.scot/Topics/Statistics/Browse/Business/Energy/EIS2015>.
3. [3] Kesicki, F., Costs and potentials of reducing CO2 emissions in the UK domestic stock from a systems perspective. Energy Build 51 (2012), 203–211, 10.1016/j.enbuild.2012.05.013 < http://linkinghub.elsevier.com/retrieve/pii/S037877881200268X>.
4. [4] Bianco, V., Scarpa, F., Tagliafico, L.A., Analysis and future outlook of natural gas consumption in the Italian residential sector. Energy Convers Manage 87 (2014), 754–764, 10.1016/j.enconman.2014.07.081 < http://www.sciencedirect.com/science/article/pii/S0196890414007201>.
5. [5] Chiu, L.F., Lowe, R., Raslan, R., Altamirano-Medina, H., Wingfield, J., A socio-technical approach to post-occupancy evaluation: interactive adaptability in domestic retrofit. Build Res Inform 42:5 (2014), 574–590, 10.1080/09613218.2014.912539 < http://www.tandfonline.com/doi/abs/10.1080/09613218.2014.912539>.
6. [6] Arteconi, A., Hewitt, N., Polonara, F., Domestic demand-side management (DSM): role of heat pumps and thermal energy storage (TES) systems. Appl Therm Eng 51:1–2 (2013), 155–165, 10.1016/j.applthermaleng.2012.09.023 < http://linkinghub.elsevier.com/retrieve/pii/S1359431112006357>.
7. [7] Tassou, S., Marquand, C., Wilson, D., Energy and economic comparisons of domestic heat pumps and conventional heating systems in the British climate. Appl Energy 24 (1986), 127–138.
8. [8] Staffell, I., Brett, D., Brandon, N., Hawkes, A., A review of domestic heat pumps. Energy Environ Sci, 5(11), 2012, 9291, 10.1039/c2ee22653g < http://xlink.rsc.org/?DOI=c2ee22653g>.
9. [9] Dunbabin, P., Charlick, H., Green, R., Detailed analysis from the second phase of the Energy Saving Trust's heat pump field trial. 2013, Department of Energy and Climate Change.
10. [10] Cabrol, L., Rowley, P., Towards low carbon homes – A simulation analysis of building-integrated air-source heat pump systems. Energy Build 48 (2012), 127–136, 10.1016/j.enbuild.2012.01.019 < http://linkinghub.elsevier.com/retrieve/pii/S0378778812000345>.
11. [11] Kelly, N.J., Tuohy, P.G., Hawkes, A.D., Performance assessment of tariff-based air source heat pump load shifting in a UK detached dwelling featuring phase change-enhanced buffering. Appl Therm Eng 71:2 (2014), 809–820, 10.1016/j.applthermaleng.2013.12.019 < http://linkinghub.elsevier.com/retrieve/pii/S135943111300896X>.
12. [12] Renaldi R, Kiprakis A, Friedrich D. Optimisation of thermal energy storage integration in a residential heating system. In: SusTEM 2015, Newcastle, UK. 2015. p. 131.
13. [13] Ikeda, S., Ooka, R., Metaheuristic optimization methods for a comprehensive operating schedule of battery, thermal energy storage, and heat source in a building energy system. Appl Energy 151 (2015), 192–205, 10.1016/j.apenergy.2015.04.029.
14. [14] Shiba, T., Yokoyama, R., Ito, K., Optimal sizing of a heat pump/thermal storage system based on the linear programming method. Int J Energy Res 19 (1995), 665–674.
15. [15] Ashouri, A., Fux, S.S., Benz, M.J., Guzzella, L., Optimal design and operation of building services using mixed-integer linear programming techniques. Energy 59 (2013), 365–376, 10.1016/j.energy.2013.06.053 < http://linkinghub.elsevier.com/retrieve/pii/S0360544213005525>.
16. [16] Harb, H., Reinhardt, J., Streblow, R., Müller, D., MIP approach for designing heating systems in residential buildings and neighbourhoods. J Build Perform Simul(June), 2015, 1–15, 10.1080/19401493.2015.1051113 < http://www.tandfonline.com/doi/full/10.1080/19401493.2015.1051113>.
17. [17] Girardin, L., Marechal, F., Dubuis, M., Calame-Darbellay, N., Favrat, D., EnerGis: a geographical information based system for the evaluation of integrated energy conversion systems in urban areas. Energy 35:2 (2010), 830–840, 10.1016/j.energy.2009.08.018 < http://linkinghub.elsevier.com/retrieve/pii/S0360544209003582>.
18. [18] Rogers, J., Cooper, S., OGrady, A., McManus, M., Howard, H., Hammond, G., The 20% house an integrated assessment of options for reducing net carbon emissions from existing UK houses. Appl Energy 138 (2015), 108–120, 10.1016/j.apenergy.2014.10.047 < http://linkinghub.elsevier.com/retrieve/pii/S0306261914010976>.
19. [19] Ofgem, Domestic Renewable Heat Incentive. < https://www.ofgem.gov.uk/environmental-programmes/domestic-renewable-heat-incentive> [accessed 12.01.2015].
20. [20] UK Energy Research Centre. UKERC Energy Data Centre. 2015. < http://ukedc.rl.ac.uk/>.
21. [21] Swan, L.G., Ugursal, V.I., Modeling of end-use energy consumption in the residential sector: a review of modeling techniques. Renew Sustain Energy Rev 13:8 (2009), 1819–1835, 10.1016/j.rser.2008.09.033 < http://linkinghub.elsevier.com/retrieve/pii/S1364032108001949>.
22. [22] Kelly, S., Shipworth, M., Shipworth, D., Gentry, M., Wright, A., Pollitt, M., Crawford-Brown, D., Lomas, K., Predicting the diversity of internal temperatures from the English residential sector using panel methods. Appl Energy 102 (2013), 601–621, 10.1016/j.apenergy.2012.08.015 < http://linkinghub.elsevier.com/retrieve/pii/S0306261912005855>.
23. [23] Kane, T., Firth, S., Lomas, K., How are UK homes heated? A city-wide, socio-technical survey and implications for energy modelling. Energy Build 86 (2014), 817–832, 10.1016/j.enbuild.2014.10.011 < http://linkinghub.elsevier.com/retrieve/pii/S0378778814008317>.
24. [24] Collin, A.J., Tsagarakis, G., Kiprakis, A.E., McLaughlin, S., Development of low-voltage load models for the residential load sector. IEEE Trans Power Syst, 2014, 1–9.
25. [25] Heller, A., Heat-load modelling for large systems. Appl Energy 72:1 (2002), 371–387, 10.1016/S0306-2619(02)00020-X < http://linkinghub.elsevier.com/retrieve/pii/S030626190200020X>.
26. [26] Yao, R., Steemers, K., A method of formulating energy load profile for domestic buildings in the UK. Energy Build 37:6 (2005), 663–671, 10.1016/j.enbuild.2004.09.007 < http://linkinghub.elsevier.com/retrieve/pii/S037877880400307X>.
27. [27] Jordan U, Vajen K. DHWcalc: Program to generate domestic hot water profiles with statistical means for user defined conditions. In: ISES solar world congress, Orlando, USA, 2005.
28. [28] Walker S. Energy use in the home – measuring and analysing domestic energy use and energy efficiency in Scotland. Scottish House Condition Survey, The Scottish Government, 2012. < http://www.gov.scot/Topics/Statistics/SHCS/EnergyUse2012>.
29. [29] Met Office. UK Hourly Weather Observation Data, Part of the Met Office Integrated Data Archive System (MIDAS). NCAS British Atmospheric Data Centre; 2006.
30. [30] Verhelst, C., Logist, F., Van Impe, J., Helsen, L., Study of the optimal control problem formulation for modulating air-to-water heat pumps connected to a residential floor heating system. Energy Build 45 (2012), 43–53, 10.1016/j.enbuild.2011.10.015 < http://linkinghub.elsevier.com/retrieve/pii/S0378778811004592>.
31. [31] Mitsubishi Electric. ecodan renewable heating technology data book, 2013. < http://library.mitsubishielectric.co.uk/pdf/book/Ecodan_PUHZ_Databook_FTC4>.
32. [32] Glover, F., Improved linear integer programming formulations of nonlinear integer problems. Manage Sci 22:4 (1975), 455–460, 10.1287/mnsc.22.4.455.
33. [33] Kingspan Environmental. Albion Aerocyl: Unvented hot water cylinder for heat pump and solar input. 2015. < www.kingspanenviro.com/details/albion-aerocyl-plus-heat-pump-and-solar-input>.
34. [34] Hahne, E., Chen, Y., Numerical study of flow and heat transfer characteristics in hot water stores. Sol Energy 64:1–3 (1998), 9–18, 10.1016/S0038-092X(98)00051-6.
35. [35] EDF Energy. Standard (Variable) Tariff Information. 2013. < https://my.edfenergy.com/product-closures-pdfs/SV-Tariff-Information.pdf>.
36. [36] Hart, W.E., Laird, C., Watson, J.-P., Woodruff, D.L., Pyomo–optimization modeling in python, vol. 67, 2012, Springer Science & Business Media.
37. [37] IBM. IBM CPLEX Optimizer. 2015. < http://www-01.ibm.com/software/commerce/optimization/cplex-optimizer/index.html>.
38. [38] Energy Saving Trust. Our calculations. 2015. < http://www.energysavingtrust.org.uk/content/our-calculations>.
39. [39] Charlick H. Investigation of the interaction between hot water cylinders, buffer tanks and heat pumps, Kiwa GASTEC at CRE. Department of Energy & Climate Change; 2013. < www.gov.uk/government/publications/investigation-of-the-interaction-between-hot-water-cylinders-buffer-tanks-and-heat-pumps>.
40. [40] Schütz, T., Streblow, R., Müller, D., A comparison of thermal energy storage models for building energy system optimization. Energy Build 93 (2015), 23–31, 10.1016/j.enbuild.2015.02.031 < http://linkinghub.elsevier.com/retrieve/pii/S037877881500136X>.
41. [41] Voll, P., Klaffke, C., Hennen, M., Bardow, A., Automated superstructure-based synthesis and optimization of distributed energy supply systems. Energy 50 (2013), 374–388, 10.1016/j.energy.2012.10.045 < http://linkinghub.elsevier.com/retrieve/pii/S0360544212008079>.