Stated preferences based estimation of power interruption costs in private households: An example from Germany

Concerns regarding supply security are increasingly raised in reaction to the transition of the German energy system toward a renewable and nuclear-free system called “Energiewende”. The goal of this work is to contribute to a measurability of supply security by quantifying the consequences of power interruptions monetarily. The focus lies within the investigation of power interruption costs in private households. An online survey with 859 participants in 2011 is used to gather the necessary data. Based on this data, a two-staged bottom-up regression model was estimated to describe interruption costs for durations of 15 min, 1 h, 4 h, 1 day and 4 days. Finally, micro-data from 55,000 households were used to perform Monte Carlo simulations to increase the representativeness of the estimations. The frequency distributions of the estimated interruption costs indicate potentials for load-shedding measures. Such measures could be an economically viable contribution to a successful integration of large shares of renewable fluctuating generation like wind or solar power.

[1]  Langche Zeng,et al.  Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models , 1999, Political Analysis.

[2]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[3]  K. Train.  Discrete Choice Methods with Simulation: Simulation-Assisted Estimation , 2009 .

[4]  John J. Boland,et al.  The benefits of environmental improvement : theory and practice , 1982 .

[5]  Hans Fleischer,et al.  Grundlagen der Statistik , 1988 .

[6]  Aaron Praktiknjo,et al.  Assessing energy supply security: Outage costs in private households , 2011 .

[7]  John E. Walsh.  Large sample nonparametric rejection of outlying observations , 1959 .

[8]  B. Johansson.  Security aspects of future renewable energy systems–A short overview , 2013 .

[9]  J. Hop,et al.  Pricing power outages in the Netherlands , 2009 .

[10]  F. Massey.  The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .

[11]  N. Stern.  The Economics of Climate Change: Implications of Climate Change for Development , 2007 .

[12]  M. Thayer.  Contingent valuation techniques for assessing environmental impacts: Further evidence , 1981 .

[13]  M. J. Sullivan,et al.  Outage cost estimation guidebook , 1995 .

[14]  Dagmar Blatná,et al.  OUTLIERS IN REGRESSION , 2006 .

[15]  Joseph H. Eto,et al.  Cost of Power Interruptions to Electricity Consumers in the United States (U.S.) , 2006 .

[16]  H. Varian.  Intermediate Microeconomics: A Modern Approach , 1987 .

[17]  C. Goldman,et al.  Option value of electricity demand response , 2005 .

[18]  W. Michael Hanemann,et al.  Willingness To Pay and Willingness To Accept: How Much Can They Differ? Comment , 2003 .