Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market

Active load shifting of the electricity demand unlocks a variety of benefits. Examples of such advantages include the increased stability of energy systems, reduced electricity costs and financial savings in the transmission as well as generation infrastructure. Although the technology necessary for demand response has been extensively studied for individual appliances or at the micro-grid level, evaluations of its nationwide impact are scarce. Yet governments and policy-makers require quantitative assessments in order to understand the underlying value and derive appropriate policies. For this purpose, this paper utilizes real-world data from the German-Austrian electricity market in order to calculate ex post the impact of demand response on electricity spot prices and load. As a result, we find that a 25% adoption rate of the available potential for load shifting could have decreased nationwide electricity expenses by approximately €500million, or 6%, in 2014. At the same time, we observe that the price volatility rises under this scheme and thus impairs non-flexible electricity customers. This observation entails significant implications in terms of designing effective policies.

[1]  D. Goldfarb,et al.  Dual and primal-dual methods for solving strictly convex quadratic programs , 1982 .

[2]  A. Faruqui,et al.  Household response to dynamic pricing of electricity: a survey of 15 experiments , 2010 .

[3]  Duc Minh Nguyen,et al.  A New Framework of Demand Response for Household Customers Based on Advanced Metering Infrastructure Under Smart Grids , 2016 .

[4]  D. Bunn,et al.  Supporting the externality of intermittency in policies for renewable energy , 2016 .

[5]  R. Walawalkar,et al.  Evolution and current status of demand response (DR) in electricity markets: Insights from PJM and NYISO , 2010 .

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

[7]  S. Stoft Power System Economics: Designing Markets for Electricity , 2002 .

[8]  Ahmad Faruqui,et al.  Unlocking the €53 Billion Savings from Smart Meters in the EU - How Increasing the Adoption of Dynamic Tariffs Could Make or Break the EU’s Smart Grid Investment , 2009 .

[9]  Donald Goldfarb,et al.  A numerically stable dual method for solving strictly convex quadratic programs , 1983, Math. Program..

[10]  Jacqueline C. K. Lam,et al.  Smart demand response in China: Challenges and drivers , 2017 .

[11]  Jiangfeng Zhang,et al.  An optimal control model for load shifting—with application in the energy management of a colliery , 2009 .

[12]  Ned Djilali,et al.  Renewable resources portfolio optimization in the presence of demand response , 2016 .

[13]  Dong Gu Choi,et al.  An electricity generation planning model incorporating demand response , 2012 .

[14]  Ned Djilali,et al.  Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets , 2018 .

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

[16]  Tobias Boßmann,et al.  Model-based assessment of demand-response measures—A comprehensive literature review , 2016 .

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

[18]  Zancanella Paolo,et al.  Demand response status in EU Member States , 2016 .

[19]  Lars Dannecker,et al.  Energy Time Series Forecasting , 2015, Springer Fachmedien Wiesbaden.

[20]  M. Behrangrad A review of demand side management business models in the electricity market , 2015 .

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

[22]  Shunsuke Managi,et al.  The effect of demand response on purchase intention of distributed generation: Evidence from Japan , 2016 .

[23]  Duncan S. Callaway,et al.  Using smart meter data to estimate demand response potential, with application to solar energy integration , 2014 .

[24]  Xue Song,et al.  Historical review of demand side management in China: Management content, operation mode, results assessment and relative incentives , 2013 .

[25]  Behnam Mohammadi-Ivatloo,et al.  Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program , 2017 .

[26]  Theodor S. Borsche,et al.  A review of demand response business cases , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[27]  Gengyin Li,et al.  Optimal residential community demand response scheduling in smart grid , 2018 .

[28]  K. Sathish Kumar,et al.  A survey on residential Demand Side Management architecture, approaches, optimization models and methods , 2016 .

[29]  S. Feuerriegel,et al.  Measuring the Financial Impact of Demand Response for Electricity Retailers , 2013 .

[30]  P. Cappers,et al.  Demand Response in U.S. Electricity Markets: Empirical Evidence , 2010 .

[31]  Stefan Feuerriegel,et al.  Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications , 2016 .

[32]  P. Warren A review of demand-side management policy in the UK , 2014 .

[33]  A. Faruqui,et al.  Fostering economic demand response in the Midwest ISO , 2010 .

[34]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[35]  Bo Shen,et al.  The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges , 2014 .

[36]  Stefan Feuerriegel,et al.  Decision model for sustainable electricity procurement using nationwide demand response , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[37]  Ming-Che Hu,et al.  Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty , 2016 .

[38]  Jean-Michel Glachant,et al.  Energy efficiency actions related to the rollout of smart meters for small consumers, application to , 2010 .

[39]  Changhui Yang,et al.  Residential electricity pricing in China: The context of price-based demand response , 2018 .

[40]  P. Siano,et al.  Assessing the benefits of residential demand response in a real time distribution energy market , 2016 .

[41]  Stefan Feuerriegel,et al.  Value and Granularity of ICT and Smart Meter Data in Demand Response Systems , 2015 .

[42]  D. Kirschen,et al.  Quantifying the Effect of Demand Response on Electricity Markets , 2007, IEEE Transactions on Power Systems.

[43]  Jin-ho Kim,et al.  Assessing demand response and smart metering impacts on long-term electricity market prices and system reliability , 2013 .

[44]  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 .

[45]  Mohammed H. Albadi,et al.  A summary of demand response in electricity markets , 2008 .

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

[47]  Javier Reneses,et al.  Regulatory and market barriers to the realization of demand response in electricity distribution networks: A European perspective , 2016 .

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

[49]  Yan Shi,et al.  Multiobjective optimization technique for demand side management with load balancing approach in smart grid , 2016, Neurocomputing.

[50]  Grigoris K. Papagiannis,et al.  Economic and environmental impacts from the implementation of an intelligent demand side management system at the European level , 2008 .

[51]  Hans Christian Gils,et al.  Economic potential for future demand response in Germany - Modeling approach and case study , 2016 .

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

[53]  Hanchen Xu,et al.  The values of market-based demand response on improving power system reliability under extreme circumstances , 2017 .

[54]  Ned Djilali,et al.  Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach , 2017 .

[55]  Nicholas Good,et al.  Review and classification of barriers and enablers of demand response in the smart grid , 2017 .

[56]  David P. Chassin,et al.  Aggregate modeling of fast-acting demand response and control under real-time pricing , 2016 .

[57]  Paras Mandal,et al.  Demand response for sustainable energy systems: A review, application and implementation strategy , 2015 .

[58]  Wolfgang Ketter,et al.  Effective demand response for smart grids: Evidence from a real-world pilot , 2016, Decis. Support Syst..