Thesis Open Access
The decarbonization of the energy sector necessitates a large-scale expansion of low-voltage (LV) grids. Yet, such expansion is expensive and increasingly difficult to plan, particularly in face of the rising number of distributed energy generation facilities and the electrification of the transportation sector. To assist utilities in the planning of electricity grids, scholars have proposed a variety of tools that automatically search for optimal grid expansion strategies. Tools that implement ant colony optimization (ACO), a heuristic framework for the solution of combinatorial optimization problems, rank among the best. Nevertheless, only few researchers have studied the application of ACO to LV grid expansion planning; and existing research neglects the cost savings potential of combining conventional power line expansion with a reconfiguration of power switches. To fill this gap, I present AntPower, a tool that searches for a minimum cost strategy to expand a given LV grid, subject to topological and electrical requirements that are common in Europe. Unlike existing tools, AntPower integrates the installation, reinforcement, and dismantling of power lines with an optimization of power switch settings. For evaluation, I consider the case of expanding a heavily overloaded grid that powers an 800-inhabitant village in rural Germany. The expansion plan generated by AntPower is by 60% cheaper than an expansion plan obtained through conventional, manual planning based on expert knowledge, and is by 64% cheaper than the expansion plan generated using a local search algorithm. Finally, a sensitivity analysis indicates that AntPower is robust against changes in most of its parameters; and for the sensitive parameters, good default values exist.
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