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The European Physical Journal Special Topics

, Volume 223, Issue 12, pp 2423–2437 | Cite as

Models for the modern power grid

  • Pedro H.J. Nardelli
  • Nicolas Rubido
  • Chengwei Wang
  • Murilo S. Baptista
  • Carlos Pomalaza-Raez
  • Paulo Cardieri
  • Matti Latva-aho
Review
Part of the following topical collections:
  1. Resilient Power Grids and Extreme Events

Abstract

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different aspects that co-determine the spatio-temporal multilayer dynamics of power system. We start our review by showing how the generation, transmission and distribution characteristics of the traditional power grids are already subject to complex behaviour appearing as a result of the the interplay between dynamics of the nodes and topology, namely synchronisation and cascade effects. When dealing with smart grids, the system complexity increases even more: on top of the physical network of power lines and controllable sources of electricity, the modernisation brings information networks, renewable intermittent generation, market liberalisation, prosumers, among other aspects. In this case, we forecast a dynamical co-evolution of the smart grid and other kind of networked systems that cannot be understood isolated. This review compiles recent results that model electric power grids as complex systems, going beyond pure technological aspects. From this perspective, we then indicate possible ways to incorporate the diverse co-evolving systems into the smart grid model using, for example, network theory and multi-agent simulation.

Keywords

Power System European Physical Journal Special Topic Smart Grid Power Grid Electricity Market 
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

© EDP Sciences and Springer 2014

Authors and Affiliations

  • Pedro H.J. Nardelli
    • 1
  • Nicolas Rubido
    • 2
    • 3
  • Chengwei Wang
    • 2
  • Murilo S. Baptista
    • 2
  • Carlos Pomalaza-Raez
    • 4
  • Paulo Cardieri
    • 5
  • Matti Latva-aho
    • 1
  1. 1.Department of Communications EngineeringUniversity of OuluOuluFinland
  2. 2.Institute for Complex Systems and Mathematical Biology, SUPA, University of AberdeenAberdeenUK
  3. 3.Instituto de Física, Facultad de Ciencias, Universidad de la RepúblicaMontevideoUruguay
  4. 4.Department of EngineeringIndiana University – Purdue University Fort WayneFort WayneUSA
  5. 5.School of Electrical and Computer Engineering, University of CampinasCampinasBrazil

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