Economic potential for future demand response in Germany - Modeling approach and case study

The activation of demand response (DR) potentials offered by electricity consumer flexibility is one promising option for providing balancing power and energy in supply systems with high share of variable renewable energy (VRE) power generation. In this paper, a model-based assessment of the economic DR potential in Germany is presented. It relies on the extension of the REMix energy system model by flexible electric loads. In a case study considering a future German power supply system with a VRE share of 70%, possible cost reductions achieved by investment in DR are quantified. The sensitivity of the results to changes in the assumed DR costs and characteristics are analyzed in additional simulations. The results show that the major benefit of employing DR is its ability to substitute peak power generation capacity, whereas the impact on the integration of VRE power generation is lower. This implies that the focus of DR is on the provision of power, not energy. Even at rather pessimistic cost DR assumptions, more than 5GW of power plant capacity can be substituted. Consumer flexibility furthermore triggers an increase in the operation of back-up power plants, whereas it decreases the utilization of pumped storage hydro stations. In the model results, the reductions in annual power supply costs achieved by DR add up to several hundreds of millions of Euros.

[1]  Sarah C. Darby,et al.  Social implications of residential demand response in cool temperate climates , 2012 .

[2]  J. Torriti,et al.  A review of the costs and benefits of demand response for electricity in the UK , 2013 .

[3]  Jacopo Torriti,et al.  Demand Side Management for the European Supergrid: Occupancy variances of European single-person households , 2012 .

[4]  Carlos Silva,et al.  Demand response modeling: A comparison between tools , 2015 .

[5]  Claire Bergaentzlé,et al.  Demand-side management and European environmental and energy goals: an optimal complementary approach , 2014 .

[6]  David Infield,et al.  The evolution of electricity demand and the role for demand side participation, in buildings and transport , 2013 .

[7]  J. Aghaei,et al.  Demand response in smart electricity grids equipped with renewable energy sources: A review , 2013 .

[8]  C. H. Antunes,et al.  Categorization of residential electricity consumption as a basis for the assessment of the impacts of demand response actions , 2014 .

[9]  Furong Li,et al.  Demand response in the UK's domestic sector , 2009 .

[10]  Christoph Schillings,et al.  Solar electricity imports from the Middle East and North Africa to Europe , 2012 .

[11]  Zbigniew A. Styczynski,et al.  Potential of demand side integration to maximize use of renewable energy sources in Germany , 2015 .

[12]  Christopher L. Magee,et al.  On improvement rates for renewable energy technologies: Solar PV, wind turbines, capacitors, and batteries , 2014 .

[13]  Diego Luca de Tena Large scale renewable power integration with electric vehicles : long term analysis for Germany with a renewable based power supply , 2014 .

[14]  M. P. Moghaddam,et al.  Flexible demand response programs modeling in competitive electricity markets , 2011 .

[15]  Daniel Stetter,et al.  Enhancement of the REMix energy system model : global renewable energy potentials, optimized power plant siting and scenario validation , 2014 .

[16]  Goran Strbac,et al.  Demand side management: Benefits and challenges ☆ , 2008 .

[17]  Philipp Grünewald,et al.  Demand response from the non-domestic sector: Early UK experiences and future opportunities , 2013 .

[18]  Hans Christian Gils,et al.  Möglichkeiten und Grenzen des Lastausgleichs durch Energiespeicher, verschiebbare Lasten und stromgeführte KWK bei hohem Anteil fluktuierender erneuerbarer Stromerzeugung , 2014 .

[19]  Hans Christian Gils,et al.  Balancing of Intermittent Renewable Power Generation by Demand Response and Thermal Energy Storage , 2015 .

[20]  J. Schleich,et al.  Effects of feedback on residential electricity demand: Findings from a field trial in Austria , 2013 .

[21]  Martin Pehnt,et al.  Load management for refrigeration systems: Potentials and barriers , 2011 .

[22]  Hans Christian Gils,et al.  Assessment of the theoretical demand response potential in Europe , 2014 .

[23]  Sarah Busche,et al.  Power systems balancing with high penetration renewables: The potential of demand response in Hawaii , 2013 .

[24]  Susan Krumdieck,et al.  Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response , 2011 .

[25]  Wolfgang Ketter,et al.  Demand side management—A simulation of household behavior under variable prices , 2011 .

[26]  P. Ferrao,et al.  The impact of demand side management strategies in the penetration of renewable electricity , 2012 .

[27]  Frieder Borggrefe,et al.  The potential of demand-side management in energy-intensive industries for electricity markets in Germany , 2011 .

[28]  C.W. Gellings,et al.  The concept of demand-side management for electric utilities , 1985, Proceedings of the IEEE.

[29]  J. Torriti,et al.  Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy , 2012 .

[30]  M. Klobasa Analysis of demand response and wind integration in Germany's electricity market , 2010 .

[31]  Diego Luca de Tena,et al.  Integrated modelling of variable renewable energy-based power supply in Europe , 2017 .

[32]  Yvonne Scholz,et al.  Renewable energy based electricity supply at low costs - Development of the REMix model and application for Europe , 2012 .

[33]  Manuel Wickert,et al.  Long-term scenarios and strategies for the deployment of renewable energies in Germany in view of European and global developments , 2012 .

[34]  Matti Lehtonen,et al.  Combining the Demand Response of direct electric space heating and partial thermal storage using LP optimization , 2014 .

[35]  Ingo Stadler,et al.  Power grid balancing of energy systems with high renewable energy penetration by demand response , 2008 .

[36]  Esfandyar Mazhari,et al.  Integrated analysis of high-penetration PV and PHEV with energy storage and demand response , 2013 .