Microgrids are foreseen within public distribution grids and therefore suitable study case networks are required to perform simulation and analysis tasks. Moreover, standardizing study case grids to provide “benchmark” networks suitable for Microgrid design would further enhance their merit and utility.
The increasing penetration of distributed generation resources to the low voltage (LV) grids, such as photovoltaics, CHP micro-turbines, small wind turbines in certain areas and possibly fuel cells in the near future, alters the traditional operating principle of the grids. A particularly promising aspect, related to the proliferation of small-scale decentralized generation, is the possibility for parts of the network comprising sufficient generating resources to operate in isolation from the main grid, in a deliberate and controlled way. These are called Microgrids and the study and development of technology to permit their efficient operation has recently started with a great momentum ([1,2]). % b C3 d5 t5 ~& D: O0 lMicrogrids are foreseen within public distribution grids and therefore suitable study case networks are required to perform simulation and analysis tasks. Moreover, standardizing study case grids to provide “benchmark” networks suitable for Microgrid design would further enhance their merit and utility. + ~) x1 Q* \, B/ ~6 uThe objective of this paper is to present and discuss a benchmark LV network developed within the EU project “Microgrids”, Contract ENK5-CT-2002-00610 and later adopted as a benchmark LV system by CIGRE TF C6.04.02: “Computational Tools and Techniques for Analysis, Design and Validation of Distributed Generation Systems”. The network consists of an LV feeder, while a more extended multi-feeder version is also included in the Appendix. The emphasis is placed on the network itself, rather than on the microsources connected and the control concepts applied. The benchmark network maintains the important technical characteristic of real utility grids, whereas, at the same time, it dispenses with the complexity of actual networks, to permit efficient modeling and simulation of microgrid operation.