Distributed energy generation

Distributed energy generation

Distributed energy generation
Distributed energy generation: Self-management techniques, that dynamically connect and disconnect parts of the grid to maintain robustness, have been deployed to this purpose.

Distributed energy generation: Increasing the Robustness of Smart Grids through distributed energy generation is a complex network approach

This research addressed the impact of large-scale integration of distributed wind/solar/micro-grid generation on the robustness of Smart Grids and containment of cascades of failures through intentional disconnection / rerouting of portions of the power grid.

  • Thema: physical infrastructures
  • Onderwerp: System Reliability

Why Distributed Energy Generation

Today’s grid was designed to move power from centralized supply sources to fixed, predictable loads;

  • the current grid is designed to deal with these loads
  • the loading capacity of components such as transformers, cables, etc. is currently determined on the basis of an assumed constant loading pattern

Current models for measuring the health of a network are based on known patterns. In the future grid, the Smart Grid, very large numbers of distributed (renewable) energy sources will be connected to the existing grid.

These physically distributed generation installations (e.g., gas turbines, micro turbines, fuel cells, solar panels, wind turbines) will be connected to existing infrastructure.

Self-management techniques

This proposal addresses the impact of large-scale integration of distributed wind/solar/micro-grid generation on the robustness of Smart Grids and containment of cascades of failures through intentional disconnection / rerouting of portions of the power grid (those augmented by distributed sources).

Self-management techniques, that dynamically connect and disconnect parts of the grid to maintain robustness, have been deployed to this purpose.

Wetenschappelijk artikelen

  • Y Koc, M.E. Warnier, R.E. Kooij, F.M. Brazier(2013): An Entropy-based Metric to Quantify the Robustness of Power Grids against Cascading Failures Safety Science pp. 126 – 134
  • Y. Koç, M.E. Warnier, P.F.A. van Mieghem, R.J. Kooij, FMT Brazier(2014): A Topological Investigation of Phase Transitions of Cascading Failures in Power Grids Physica A: Statistical Mechanics and its Applications pp. 273 – 284 ISSN: 0378-4371.
  • X. Wang, E. Pournaras, R.J Kooij, P.F.A. Van Mieghem(2014): Improving Robustness of Complex Networks via the Effective Graph Resistance The European Physical Journal B pp. 1 – 12
  • E. Pournaras, M. Vasirani, R.J. Kooij, K. Aberer(2014): Decentralized Planning of Energy Demand for the Management of Robustness and Discomfort IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS pp. 2280 – 2289 ISSN: 1551-3203.
  • Y. Koç, M.E. Warnier, P.F.A. Van Mieghem, R.J. Kooij, F.M.T. Brazier(2014): The Impact of the Topology on Cascading Failures in a Power Grid Model Physica A: Statistical Mechanics and its Applications pp. 169 – 179 ISSN: 0378-4371.
  • X Wang, E Pournaras, R Kooij, P Van Mieghem(2015): Improving robustness of complex networks via the effective graph resistanceEur. Phys. J. B pp. 221 – 233
  • E Pournaras, M Vasirani, R.E. Kooij, K Aberer(2015): Decentralized Planning of Energy Demand for the Management of Robustness and Discomfort IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS pp. 2280 – 2289

Hoofdstuk in boek

  • E Pournaras, M Yao, R Ambrosio, M.E. Warnier(2013): Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence, Studies in Computational Intelligence pp. 189 – 206 , Berlijn

Proefschrift

  • Y Koç(2015): On robustness of Power Grids: Measuring the Robustness of Power Grids: A Complex Networks Theory Approach , Delft  16 november 2015

Partners

NWO, TU Delft

Contact

  • TU Delft
  • Prof. dr. F.M. Brazier
  • E: F.M.Brazier@tudelft.nl
Scientists
Looptijd

01/09/2011 tot 11/07/2016

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