Denmark’ goal of being independent of fossil energy sources in 2050 puts forward great demands on all energy subsystems (electricity, heat, gas and transport, etc.) to be operated in a holistic manner. The Danish experience and challenges of wind power integration and the development of district heating systems are summarized in this paper. How to optimally use the cross-sectoral flexibility by intelligent control (model predictive control-based) of the key coupling components in an integrated heat and power system including electrical heat pumps in the demand side, and thermal storage applications in buildings is investigated.
Cite this paper
Zong, Y. , Ahmed, A. , Wang, J. , You, S. , Træholt, C. and Xiao, X. (2017) Enhancing Wind Power Integration through Optimal Use of Flexibility in Multi-Carrier Energy Systems from the Danish Perspective. World Journal of Engineering and Technology
, 78-88. doi: 10.4236/wjet.2017.54B009
 Andersen, A.V. (2016) 42%: Danish Wind Power Sets World Record. State of Green.
 Danish Energy Agency (2012) Energy Policy in Denmark.
 ICIS (2009) Danish Spot Hits Negative Value for First Time.
 Abeysekera, M., Wu, J. and Jenkins, N. (2016) Integrated Energy System: An Overview of Benefits, Analysis Methods, Research Gaps and Opportunities.
 Smart Energy Networks (2015) Vision for Smart Energy in Denmark.
 Road Map for Smart Grid Research, Development and Demonstration up to 2020.
 The Danish Experience with Integrating Variable Renewable Energy
 You, S., Lin, J., Zong, Y. and Bindner, H. (2015) The Danish Perspective of Internet of Energy: From Service-Oriented Flexibility Trading to Integrated Design, Planning and Operation of Multiple Cross-Sectoral Energy Systems. China Soc. for Elec. Eng, 35, 3470-3481.
 Papaefthymiou, G., Grave, K. and Dragoon, K. (2014) Flexibility Options in Electricity Systems. ECOFYS Germany GmbH, Berlin.
 White Papers for a Green Transition: Smart Buildings.
 Heier, J., Bales, C. and Martin, V. (2015) Combining Thermal Energy Storage with Buildings—A Review. Renewable and Sustainable Energy Reviews, 42, 1305-1325.
 District Heating-Danish Experience.
 Danish Energy Agency, Energistatistik (2015) Technical Report, Danish Ministry of Energy.
 Lund, H., Werner, S., Wiltshire, R., et al. (2014) 4th Generation District Heating (4GDH): Integrating Smart Thermal Grids into Future Sustainable Energy Systems. Energy, 68, 1-11. https://doi.org/10.1016/j.energy.2014.02.089
 State of Green. Heat pumps.
 Cigler, J., Tomáskoa, P. and Siroky, J. (2013) Building LAB: A Tool to Analyze Performance of Model Predictive Controllers for Buildings. Energy and Buildings, 57, 34-41. https://doi.org/10.1016/j.enbuild.2012.10.042
 Zong, Y., Böning, G.M. and Santos, R.M. (2016) Challenges of Implementing Economic Model Predictive Control Strategy for Buildings Interacting with Smart Energy Systems. Journal of Applied Thermal Engineering, 114, 1476-1486.
 Awadelrahman, M.A., Zong, Y., Li, H.W. and Agert, C. (2017) Economic Model Predictive Control for Hot Water Based Heating Systems in Smart Building. Journal of Energy and Power Engineering, 9, 112-119.
 Zong, Y., Kullmann, D., Thavlov, A., Gehrke, O. and Bindner, H. (2012) Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration. IEEE Transactions on Smart Grid, 3, 1055-1062. https://doi.org/10.1109/TSG.2011.2177282
 Chen, C., et al. (2013) MPC-Based Appliance Scheduling for Residential Building Energy Management Controller. IEEE Transactions on Smart Grid, 4, 1401-1410.
 Lindelöf, D., Afshari, H., et al. (2015) Field Tests of an Adaptive, Model-Predictive Heating Controller for Residential Buildings. Energy and Buildings, 99, 292-302.
 Power Lab DK. http://www.powerlab.dk/Facilities/PowerFlexHouses
 EnergyLab Nordhavn Project. http://www.energylabnordhavn.dk/
 The Nord Pool Spot Market.
 Böning, G.M. (2016) Model Predictive Control (MPC)-Based Energy Management of Smart Buildings, in Regenerative Energiesysteme, Fakultät III—Prozesswissenschaften. Technische Universität Berlin.