Evolutionary Algorithms for Planning Remote Electricity Distribution Networks Considering Isolated Microgrids and Geographical Constraints

In this study we propose obstacle-aware evolution-ary algorithms to identify optimised network topologies for electricity distribution networks including isolated microgrids or stand-alone power systems. We outline the extension of two evo-lutionary algorithms that are modified to consider different types of geographically constrained areas in electricity distribution planning. These areas are represented as polygonal obstacles that either cannot be traversed or cause a higher weight factor when traversing. Both proposed evolutionary algorithms are extended such that they find optimised network solutions that avoid solid obstacles and consider the increased cost of traversing soft obstacles. The algorithms are tested and compared on different types of problem instances with solid and soft obstacles and the problem-specific evolutionary algorithm can be shown to successfully find low cost network topologies on a range of different test instances.