Identifying Isolated Microgrids in Rural Areas: An Evolutionary Algorithm Approach for a Graph Clustering Problem

The clustering of networks in order to optimise one or more given objectives is a highly researched field with many real-world applications. One of these applications is the clustering of a current or potential future electricity network in order to identify an optimised network topology that could consist of microgrids and stand-alone power systems. This research paper gives a brief overview of the current applications of network partitioning and the different methodologies found in the literature. Then, a novel evolutionary algorithm approach is presented which optimises the topology of rural electricity distribution networks considering a problem-specific objective cost function. Given a set of electricity customer loads and locations, the aim is to identify optimal microgrid and standalone power system formations to minimise the total network costs over a certain time period. The latter part entails a brief introduction to microgrids and some theoretical background, a description of the evaluated cost function, and an outline of the problem-specific evolutionary algorithm used for optimising the network.