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Original Articles

Demand response potential of district heating and ventilation in an educational office building

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References

  • Alimohammadisagvand, B. 2018a. Influence of demand response actions on thermal comfort and electricity cost for residential houses. (Article dissertation). Aalto University, School of Engineering, Finland.
  • Alimohammadisagvand, B., J. Jokisalo, and K. Sirén. 2016b. The potential of predictive control in minimizing the electricity cost in a heat-pump heated residential house. Proceedings of the 3rd IBPSA-England Conference BSO 2016, Great North Museum, Newcastle, 12th-14th September 2016, Link of Proceedings: http://www.ibpsa.org/proceedings/BSO2016/p1049.pdf.
  • Alimohammadisagvand, B., S. Alam, M. Ali, M. Degefa, J. Jokisalo, and K. Siren. 2015. Influence of energy demand response actions on thermal comfort and energy cost in electrically heated residential houses. Indoor and Built Environment. doi:10.1177/1420326X15608514
  • Alimohammadisagvand, B., J. Jokisalo, S. Kilpeläinen, M. Ali, and K. Sirén. 2016. Cost-optimal thermal energy storage system for a residential building with heat pump heating and demand response control. Applied Energy 174:275–87. doi:10.1016/j.apenergy.2016.04.013
  • Alimohammadisagvand, B., J. Jokisalo, and K. Sirén. 2018. Comparison of four rule-based demand response control algorithms in an electrically and heat pump-heated residential building. Applied Energy 209:167–79. doi:10.1016/j.apenergy.2017.10.088
  • Arabzadeh, V., B. Alimohammadisagvand, J. Jokisalo, and K. Siren. 2018. A novel cost-optimizing demand response control for a heat pump heated residential building. Building Simulation 11 (3):533–47. doi:10.1007/s12273-017-0425-5
  • Bauman, F., and M. McClintock, 1993. A study of occupand comfort and workstation performance in PG&E’s advanced office systems testbed, Final report to PG&E Research and development, Center for Envrionmental design research, Berkeley: University of California. Retrieved from https://escholarship.org/uc/item/4zc1s0sw#author.
  • Bozorg Chenani, S., M. T. Vaaja, M. Kurkela, I. Kosonen, and T. Luttinen. 2017. Target detection distances under different road lighting intensities. European Transport Research Review 9 (2):17. doi:10.1007/s12544-017-0234-z
  • Bozorg Chenani, S., R.-S. Räsänen, and E. Tetri. 2018. Advancement in Road Lighting. Light & Engineering 26:99–109.
  • Bring, A., P. Sahlin, and M. Vuolle, 1999. Models for Building Indoor Climate and Energy Simulations. A report of IEA Task 22. http://www.equa.se/dncenter/T22Brep.pdf.
  • Cai, H., C. Ziras, S. You, R. Li, K. Honoré, and H. W. Bindner. 2018. Demand side management in urban district heating networks. Applied Energy 230:506–18. doi:10.1016/j.apenergy.2018.08.105
  • Cetin, K. S., L. Manuel, and A. Novoselac. 2016. Thermal comfort evaluation for mechanically conditioned buildings using response surfaces in an uncertainty analysis framework. Science and Technology for the Built Environment 22 (2):140–52. doi:10.1080/23744731.2015.1100022
  • Chang, Y., C. S. Kim, J. I. Miller, J. Y. Park, and S. Park. 2016. A new approach to modeling the effects of temperature fluctuations on monthly electricity demand. Energy Economics 60:206–16. doi:10.1016/j.eneco.2016.09.016
  • Claessens, B. J., D. Vanhoudt, J. Desmedt, and F. Ruelens. 2018. Model-free control of thermostatically controlled loads connected to a district heating network. Energy and Buildings 159:1–10. doi:10.1016/j.enbuild.2017.08.052
  • Coss, S., V. Verda, and O. Le-Corre. 2018. Multi-objective optimization of district heating network model and assessment of demand side measures using the load deviation index. Journal of Cleaner Production 182:338–51. doi:10.1016/j.jclepro.2018.02.083
  • D3 Finnish code of building regulation. (2012). Rakennusten energiatehokuus (Energy management in buildings, regulations and guidelines), Regulations and guidelines 2012. Helsinki, Finland. [In Finnish]. (2012). Retrieved from http://www.finlex.fi/data/normit/37188-D3-2012_Suomi.pdf
  • D5 Finnish code of building regulation. 2012. Rakennusten energiankulutuksen ja lämmitystehontarpeen laskenta (calculation of power and energy needs for heating of buildings), Guidelines 2012. Helsinki, Finland: Ministry of the Environment [In Finnish]. (2012). Ministry of Environment, Regulations and guidelines.
  • Difs, K., M. Bennstam, L. Trygg, and L. Nordenstam. 2010. Energy conservation measures in buildings heated by district heating – a local energy system perspective. Energy 35 (8):3194–203. doi:10.1016/j.energy.2010.04.001
  • Dominković, D. F., P. Gianniou, M. Münster, A. Heller, and C. Rode. 2018. Utilizing thermal building mass for storage in district heating systems: Combined building level simulations and system level optimization. Energy 153:949–66. doi:10.1016/j.energy.2018.04.093
  • EN 308. 1997. Heat exchangers. Test procedures for establishing performance of air to air and flue gases heat recovery devices. Brussels: European Committee for Standardization (CEN).
  • Energy District Heating. 2017. Diverse renewables mix in district heating - Finnish Energy. Retrieved April 13, 2018, from https://energia.fi/en/news_and_publications/publications/energy_year_2016_district_heating_diverse_renewables_mix_in_district_heating.html
  • Equa Simulation AB. (2010a). Validation of IDA Indoor Climate and Energy 4.0 build 4 with respect to ANSI/ASHRAE Standard 140-2004.
  • Equa Simulation AB. (2010b). Validation of IDA indoor climate and Energy 4.0 with respect to CEN Standard EN 15265-2007.
  • Finnish Society of Indoor Air Quality (FiSIAQ). 2018. Classification of indoor environment, Helsinki: Rakennustieto Oy.
  • Fortum, Agency of Electricity in Finland. 2019. Fortum Tarkka - pörssisähköä. Retrieved from https://www.fortum.fi/kotiasiakkaille/sahkoa-kotiin/sahkosopimukset/tarkka-porssisahko
  • Hu, Z., J. Kim, J. Wang, and J. Byrne. 2015. Review of dynamic pricing programs in the U.S. and Europe: Status quo and policy recommendations. Renewable and Sustainable Energy Reviews 42:743–51. doi:10.1016/j.rser.2014.10.078
  • International Energy Agency Solar Heating & Cooling Programme. 1999. Empirical Validation of EDF ETNA and GENEC Test-Cell Models: A Report of Task 22 Building Energy Analysis Tools.
  • International Energy Agency. 2016. World Energy Statistics 2016. Retrieved April 5, 2018, from http://www.iea.org/bookshop/723-World_Energy_Statistics_2016
  • Kalamees, T., K. Jylhä, H. Tietäväinen, J. Jokisalo, S. Ilomets, R. Hyvönen, and S. Saku. 2012. Development of weighting factors for climate variables for selecting the energy reference year according to the EN ISO 15927-4 standard. Energy and Buildings 47 (0):53–60. doi:10.1016/j.enbuild.2011.11.031
  • Kim, Y., and L. K. Norford. 2017. Optimal use of thermal energy storage resources in commercial buildings through price-based demand response considering distribution network operation. Applied Energy 193:308–24. doi:10.1016/j.apenergy.2017.02.046
  • Kontu, K., J. Vimpari, P. Penttinen, and S. Junnila. 2018. City scale demand side management in three different-sized district heating systems. Energies 11 (12):3370. doi:10.3390/en11123370
  • Korkas, C. D., S. Baldi, I. Michailidis, and E. B. Kosmatopoulos. 2015. Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule. Applied Energy 149:194–203. doi:10.1016/j.apenergy.2015.01.145
  • Korkas, C. D., S. Baldi, I. Michailidis, and E. B. Kosmatopoulos. 2016. Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage. Applied Energy 163:93–104. doi:10.1016/j.apenergy.2015.10.140
  • Le Dréau, J., and P. Heiselberg. 2016. Energy flexibility of residential buildings using short term heat storage in the thermal mass. Energy 111:991–1002. doi:10.1016/j.energy.2016.05.076
  • Li, W., and P. Xu. 2016. A fast method to predict the demand response peak load reductions of commercial buildings. Science and Technology for the Built Environment 22 (6):633–42. doi:10.1080/23744731.2016.1145533
  • Lund, H., S. Werner, R. Wiltshire, S. Svendsen, J. E. Thorsen, F. Hvelplund, and B. V. Mathiesen. 2014. 4th Generation District Heating (4GDH): Integrating smart thermal grids into future sustainable energy systems. Energy 68:1–11. doi:10.1016/j.energy.2014.02.089
  • Maniccia, D., B. Rutledge, M. S. Rea, and W. Morrow. 2013. Occupant use of manual lighting controls in private offices. 28 (2):42–56. doi:10.1080/00994480.1999.10748274
  • Martin, K. 2017. Demand response of heating and ventilation within educational office buildings. (Master thesis, Aalto University). Retrieved from http://urn.fi/URN:NBN:fi:aalto-201712187947.
  • Martin, K., J. Jokisalo, R. Kosonen, and B. Vand. 2018. Demand response of space heating and ventilation - impact on indoor environmental quality. Roomvent & Ventilation 2018. Presented at the Roomvent & Ventilation 2018, Finland.
  • McKenna, E., and M. Thomson. 2014. Demand response behaviour of domestic consumers with photovoltaic systems in the UK: an exploratory analysis of an internet discussion forum. Energy, Sustainability and Society 4 (1):13. doi:10.1186/2192-0567-4-13
  • Mishra, A. K., J. Jokisalo, R. Kosonen, T. Kinnunen, M. Ekkerhaugen, H. Ihasalo, and K. Martin. 2019. Demand response events in district heating: Results from field tests in a university building. Sustainable Cities and Society 47:101481. doi:10.1016/j.scs.2019.101481
  • Nassif, N., and S. Moujaes. 2008. A cost-effective operating strategy to reduce energy consumption in a HVAC system. International Journal of Energy Research 32 (6):543–58. doi:10.1002/er.1364
  • Nord Pool Spot. 2015. Leading power market in Europe. Retrieved May 20, 2014, from http://www.nordpoolspot.com/
  • Page, J., D. Robinson, N. Morel, and J.-L. Scartezzini. 2008. A generalised stochastic model for the simulation of occupant presence. Energy and Buildings 40 (2):83–98. doi:10.1016/j.enbuild.2007.01.018
  • Romanchenko, D., J. Kensby, M. Odenberger, and F. Johnsson. 2018. Thermal energy storage in district heating: Centralised storage vs. storage in thermal inertia of buildings. Energy Conversion and Management 162:26–38. doi:10.1016/j.enconman.2018.01.068
  • Rotger-Griful, S., R. H. Jacobsen, D. Nguyen, and G. Sørensen. 2016. Demand response potential of ventilation systems in residential buildings. Energy and Buildings 121:1–10. doi:10.1016/j.enbuild.2016.03.061
  • Sahlin, P. 1996. Modelling and simulation methods for modular continuous systems in buildings (Royal Institute of Technology). Retrieved from http://www.equa.se/dncenter/thesis.pdf
  • Salo, S., A. Hast, J. Jokisalo, R. Kosonen, S. Syri, J. Hirvonen, and K. Martin. 2019. The impact of optimal demand response control and thermal energy storage on a district heating system. Energies 12 (9):1678. doi:10.3390/en12091678
  • Sameti, M., and F. Haghighat. 2017. Optimization approaches in district heating and cooling thermal network. Energy and Buildings 140:121–30. doi:10.1016/j.enbuild.2017.01.062
  • Sehar, F., M. Pipattanasomporn, and S. Rahman. 2016. A peak-load reduction computing tool sensitive to commercial building environmental preferences. Applied Energy 161:279–89. doi:10.1016/j.apenergy.2015.10.009
  • SFS-EN 15251. 2007. Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. Finnish Standards Association. Retrieved from http://www.sfs.fi/en
  • Shan, K., S. Wang, C. Yan, and F. Xiao. 2016. Building demand response and control methods for smart grids: A review. Science and Technology for the Built Environment 22 (6):692–704. doi:10.1080/23744731.2016.1192878
  • Swing Gustafsson, M., J. A. Myhren, and E. Dotzauer. 2018. Potential for district heating to lower peak electricity demand in a medium-size municipality in Sweden. Journal of Cleaner Production 186:1–9. doi:10.1016/j.jclepro.2018.03.038
  • Valogianni, K., and W. Ketter. 2016. Effective demand response for smart grids: Evidence from a real-world pilot. Decision Support Systems 91:48–66. doi:10.1016/j.dss.2016.07.007
  • Vand, B., Y. K. Lopes, E. A. Hathway, and P. Rockett. 2019. Sensitivity analysis of building physical parameters to maximize heating energy saving using MPC. Presented at the 3rd International Conference on Energy Harvesting, Storage, and Transfer. https://doi.org/10.11159/ehst19.136.
  • Vandermeulen, A., B. van der Heijde, and L. Helsen. 2018. Controlling district heating and cooling networks to unlock flexibility: A review. Energy 151:103–15. doi:10.1016/j.energy.2018.03.034
  • Vinha, J., M. Korpi, T. Kalamees, J. Jokisalo, L. Eskola, J. Palonen, J. Kurnitski, H. Aho, M. Salminen, K. Salminen., et al. 2009. Asuinrakennusten ilmanpitävyys, sisäilmasto ja energiatalous (Air tightness, indoor climate and energy economy). Research report 140. Structural Engineering laboratory, Tampere University of Technology, Tampere, Finland.
  • Wang, S. 2016. Making buildings smarter, grid-friendly, and responsive to smart grids. Science and Technology for the Built Environment 22 (6):629–32. doi:10.1080/23744731.2016.1200888
  • Yoon, J. H., R. Baldick, and A. Novoselac. 2016. Demand response control of residential HVAC loads based on dynamic electricity prices and economic analysis. Science and Technology for the Built Environment 22 (6):705–19. doi:10.1080/23744731.2016.1195659

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