Intelligence in Electricity Networks for Embedding Renewables and Distributed Generation

  • J. K. KokEmail author
  • M. J. J. Scheepers
  • I. G. Kamphuis
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 42)


Over the course of the 20th century, electrical power systems have become one of the most complex systems created by mankind. Electricity has made a transition from a novelty, to a convenience, to an advantage, and finally to an absolute necessity. The electricity infrastructure consists of two highly-interrelated subsystems for commodity trade and physical delivery. To ensure the infrastructure is up and running in the first place, the increasing electricity demand poses a serious threat. Additionally, two other trends force a change in infrastructure management. Firstly, there is a shift toward intermittent sources, which gives rise to a higher influence of weather patterns on generation. At the same time, introducing more combined heat and power generation (CHP) couples electricity production to heat demand patterns. Secondly, the location of electricity generation relative to the load centers is changing. Large-scale generation from wind is migrating towards and into the seas and oceans, and, with the increase of distributed generators (DG), the generation capacity embedded in the (medium and low voltage) distribution networks is rising. Due to these developments, intelligent distributed coordination will be essential to ensure the efficient operation of this critical infrastructure in the future. As compared to traditional grids, operated in a top-down manner, these novel grids will require bottom-up control. As field test results have shown, intelligent distributed coordination can be beneficial to both energy trade and active network management. In future power grids, these functions need to be combined in a dual-objective coordination mechanism. To exert this type of control, alignment of power systems with communication network technology as well as computer hardware and software in shared information architectures will be necessary.


Wind Turbine Multiagent System Electricity Market Electricity Network Demand Response 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    H. Akkermans, J. Schreinemakers, and K. Kok. Microeconomic distributed control: Theory and application of multi-agent electronic markets. In Proceedings of the 2nd International Conference on Critical Infrastructures, Grenoble, France, 2004.Google Scholar
  2. 2.
    J. Berst, P. Bane, M. Burkhalter, and A. Zheng. The electricity economy. White paper, Global Environment Fund, August 2008.Google Scholar
  3. 3.
    R. K. Dash, D. C. Parkes, and N. R. Jennings. Computational mechanism design: A call to arms. IEEE Intelligent Systems, 18(6):40–47, November/December 2003.Google Scholar
  4. 4.
    L. J. de Vries. Securing the public interest in electricity generation markets, The myths of the invisible hand and the copper plate. PhD thesis, Delft University of Technology, Delft, The Netherlands, 2004.Google Scholar
  5. 5.
    Energy Information Administration. International Energy Outlook 2007. EIA, Paris, France, 2007.Google Scholar
  6. 6.
    Energy Information Administration. /RecentElectricityGenerationByType.xls, December 2008.
  7. 7.
    ENIRDGnet. Concepts and opportunities of distributed generation: The driving European forces and trends. Project Deliverable D3, ENIRDGnet, 2003.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • J. K. Kok
    • 1
    Email author
  • M. J. J. Scheepers
    • 1
  • I. G. Kamphuis
    • 1
  1. 1.Energy research Centre of the Netherlands (ECN), Power Systems and Information TechnologyPettenThe Netherlands

Personalised recommendations