We have proposed a method by which the topology of a network might be discovered through an algorithm like the distributed Bellman-Ford algorithm. We have explored the inner workings of two methods to automate power distribution network reconfiguration, the ILP Solver and the Heuristic Solver. We have seen how networks of different shapes can be translated into a flattened topology, which is necessary preprocessing to find a power assignment solution for a network. We have also seen some experimental results comparing the performance of the ILP Solver and the Heuristic Solver. The Heuristic Solver is a very fast, efficient algorithm to reconfigure power distribution, which is important in the case of an emergency. It performs consistently with near perfect results at a speed that is orders of magnitude quicker than the ILP Solver in almost all cases. In an application where a network is small and time is not an important constraint, the ILP Solver could possibly be preferable, but in any context where time is sensitive and near-perfect results are as acceptable as perfect results, the Heuristic Solver is much preferable. There is always room for improvement. Future tests should perhaps allow for non-integer capacity units, or loads that require other values than unit capacity. Optimizing each algorithm by rewriting them in C could give more optimized tests, though this may not be necessary to make judgments about implementing one or the other. There may be some ways to improve the Heuristic Solver, such as arranging the ordered_links in some way that could be more optimal. The algorithm could also be improved by taking advantage of the fact that once there are no more sources with capacity to provide any loads, the process of trying to assign loads to them for power supply can cease. Perhaps this method could be combined with other methods that do not presently account for load priorities or place as much value on fast execution.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-3108 |
| Date | 01 May 2017 |
| Creators | Ekstrand, Aaron Jordan |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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