Coupling Variable Renewable Electricity Production to the Heating Sector through Curtailment and Power-to-heat Strategies for Accelerated Emission Reduction

The Paris Climate Accord and recent IPCC analysis urges to strive towards carbon neutrality by the middle of this century. As most of the end-use energy in Europe is for heating, or well above 60%, these targets will stress more actions in the heating sector. So far, much of the focus in the emission reduction has been on the electricity sector. For instance, the European Union has set as goal to have a carbon-free power system by 2050. Therefore, the efficient coupling of renewable energy integration to heat and heating will be part of an optimal clean energy transition. This paper applies optimization-based energy system models on national (Finland) and sub-national level (Helsinki) to include the heating sector in an energy transition. The models are based on transient simulation of the energy system, coupling variable renewable energies (VRE) through curtailment and power-to-heat schemes to the heat production system. We used large-scale wind power schemes as VRE in both cases. The results indicate that due to different energy system limitations and boundary conditions, stronger curtailment strategies accompanied with large heat pump schemes would be necessary to bring a major impact in the heating sector through wind power. On a national level, wind-derived heat could meet up to 40% of the annual heat demand. On a city level, the use of fossil fuel in combined heat and power production (CHP), typical for northern climates, could significantly be reduced leading even close to 70% CO2 emission reductions in Helsinki. Though these results were site specific, they indicate major opportunities for VRE in sectoral coupling to heat production and hence also a potential role in reducing the emissions.

[1]  Ali Elkamel,et al.  Design of an energy hub based on natural gas and renewable energy sources , 2014 .

[2]  Peter Lund,et al.  Review of energy system flexibility measures to enable high levels of variable renewable electricity , 2015 .

[3]  Peter D. Lund,et al.  Capacity matching of storage to PV in a global frame with different loads profiles , 2018, Journal of Energy Storage.

[4]  Goran Andersson,et al.  The role of electric vehicles in smart grids , 2013, Advances in Energy Systems.

[5]  Aie World Energy Outlook 2017 , 2017 .

[6]  Hiroaki Suzuki,et al.  Eco2 Cities: Ecological Cities as Economic Cities , 2010 .

[7]  Peter Lund,et al.  Large-scale urban renewable electricity schemes - integration and interfacing aspects , 2012 .

[8]  Peter Lund,et al.  Effect of major policy disruptions in energy system transition: Case Finland , 2018 .

[9]  Genku Kayo,et al.  Energy sharing and matching in different combinations of buildings, CHP capacities and operation strategy , 2014 .

[10]  Carlos Moreira,et al.  Handling renewable energy variability and uncertainty in power systems operation , 2014 .

[11]  Peter Lund,et al.  Smart energy system design for large clean power schemes in urban areas , 2015 .

[12]  Juha Jokisalo,et al.  A novel cost-optimizing demand response control for a heat pump heated residential building , 2018 .

[13]  Peter Lund,et al.  Modeling flexibility and optimal use of existing power plants with large-scale variable renewable power schemes , 2016 .

[14]  Shan Zhou,et al.  Smart‐grid policies: an international review , 2013 .

[15]  Aie Cities, Towns and Renewable Energy , 2009 .

[16]  Ala Hasan,et al.  On-site energy matching indices for buildings with energy conversion, storage and hybrid grid connections , 2013 .

[17]  Lin Gao,et al.  System study of combined cooling, heating and power system for eco‐industrial parks , 2008 .