Demand response represents an additional option for reserve capacity as first market experiences have demonstrated. An analysis for Germany shows capacities up to 3 GW and costs starting at 30 euro/MWh in the industrial sector, 8 GW in the commercial sector and more than 20 GW in the residential sector including night storage heating. Simulations of the German power system showed that using these potentials together with improved wind power predictions can limit the additional balancing costs in Germany to below 2 euro/MWh feed-in by wind turbines with 48 GW wind power in 2020
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Marc BrunnerEffects of feedback on residential electricity demand -Findings from a field trial in Austria
AbstractThis paper analyzes the effects of providing feedback on electricity consumption in a field trial involving more than 1,500 households in Linz, Austria. About half of these households received feedback together with information about electricitysaving measures (pilot group), while the remaining households served as a control group. Participation in the pilot group was random, but households were able to choose between two types of feedback: access to a web portal or written feedback by post. Results from cross section OLS regression suggest that feedback provided to the pilot group corresponds with electricity savings of around 4.5 % for the average household. Our results from quantile regressions imply that for households in the 30th to the 70th percentile, feedback on electricity consumption is statistically significant and effects are highest in absolute terms and as a share of electricity consumption. For percentiles below or above this range, feedback appears to have no effect. Finally, controlling for a potential endogeneity bias induced by non random participation in the feedback type groups, we find no difference in the effects of feedback provided via the web portal and by post.
Highlights• We estimate the effects of feedback on household electricity use in a field trial in Linz, Austria.• Providing feedback on electricity use corresponds with average savings of around 4.5 %.• Effects of feedback are most pronounced in the 30th to the 70th percentile.• Feedback provided via a web portal and by post appears equally effective.
International audienceAs countries move toward larger shares of renewable electricity, the slow diffusion of activeelectricity load management should concern energy policy makers and users alike. Activeload management can increase capacity factors and thereby reduce the need for new capacity,improve reliability, and lower electricity prices. This paper conceptually and empiricallyexplores barriers to load shift in industry from an end-user perspective. An online survey,based on a taxonomy of barriers developed in the realm of energy efficiency, was carried outamong manufacturing sites in mostly Southern Germany. Findings suggest that the mostimportant barriers are risk of disruption of operations, impact on product quality, anduncertainty about cost savings. Of little concern are access to capital, lack of employee skills,and data security. Statistical tests suggest that companies for which electricity has higherstrategic value rate financial and regulatory risk higher than smaller ones. Companies with acontinuous production process report lower barrier scores than companies using batch or justin-time production. A principal component analysis clusters the barriers and multivariateanalysis with the factor scores confirms the prominence of technical risk as a barrier to loadshift. The results provide guidance for policy making and future empirical studies
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