Optimal reconfiguration algorithms for low voltage distribution networks

Renewables will play a major role in the transition to a clean energy system. This transition has a number of effects related to the electricity system: (1) an increasingly decentralized injection of renewable generation showing a high simultaneity of generated electricity, (2) an increase of the electrical load caused by a shift from fossil fuelled systems towards high efficient electrical equipment for transport and heating, and (3) an increased need for flexibility in the electricity system due to the high intermittency of renewable generation. This phd aims to develop technology to optimize DSO operational planning and operations to deal with the foreseen distribution network evolution, to make sure network capacity is used optimally, and network investments are minimized. One of the control options the network operator has, is to reconfigure existing feeders and lines. However, further research is needed to be able to find an optimal network lay-out, i.e. the network configuration where the risk for network congestions is minimized, given the evolutions in connected load and generation. In this PhD, optimal reconfiguration algorithms for low voltage distribution networks, will be explored. An inherent complexity of low-voltage networks is that there are many uncertainties: for example electricity consumption and generation of (residential) customers is hard to predict, but also the phase connectivity of each connection remains largely unknown. The development of any tool for distribution network operators must therefore be able to work with these existing unknowns and complexities.