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Smart Metering and Privacy in Europe: Lessons from the Dutch Case

  • Colette CuijpersEmail author
  • Bert-Jaap Koops
Chapter

Abstract

The future of energy supply lies in smart grids, which enable energy supply to and from consumers. These two-way energy networks require smart energy metering systems. The vision of smart grids will require one or more decades yet to be fully realised, but since a roll-out of smart meters is a lengthy process, countries are already starting to implement smart metering legislation, following the European legal framework on energy efficiency. Rolling out smart meters, however, requires smart legislation. The Dutch example, where the Senate blocked two smart metering bills in 2009, demonstrates that introducing smart meters can be significantly delayed if the underlying legislation is flawed. In particular, the Dutch case shows that privacy is a crucial element in smart metering legislation. Energy consumption reveals details of personal life, in the most privacy-sensitive place – the home, and therefore smart metering has to strike a careful balance between detailed energy metering and privacy protection.

In this paper, we present the recent developments in smart metering and describe the Dutch case in detail. From this, we draw key lessons for countries that want to introduce smart metering. In terms of substance, the level of detail of smart meter readings and the mandatory or voluntary character of smart meters are crucial issues to take into account. Legislators must make a trade-off between the ‘smartness’ of the meter versus a comprehensive, mandatory roll-out. In terms of procedure, a privacy impact assessment is vital, and pitfalls of function creep should be avoided by resisting the temptation of making a meter ‘too smart’ all at once. From the outset, privacy and data protection law must be taken into account as an important requirement for the design of smart metering systems.

Keywords

Personal Data Data Protection Smart Grid Grid Operator Energy Supplier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Tilburg Institute for Law, Technology, and Society (TILT)Tilburg UniversityTilburgThe Netherlands
  2. 2.FRW-TILTTilburg UniversityTilburgThe Netherlands

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