This paper presents the application of a new genetic algorithm for the optimal design of large distribution systems, solving the optimal sizing and locating problems of feeders and substations using the corresponding fixed costs as well as the true non-lineal variable costs. It can be also applied to single stage or multistage distribution designs.The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning.Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has been also used to include several relevant design aspects in the distribution network optimization.
This paper presents a new methodology for automated route selection for the construction of new power lines, based on geographic information systems (GIS). It uses a dynamic programming model for route optimization. Environmental restrictions are taken into account together with all of the operating, maintenance, and equipment installation costs, including a new approach to the costs associated with the slope of the terrain crossed by the power lines. The computing and visual representation capacities of GIS are exploited for the selection of economic corridors, keeping the total costs under a threshold imposed by the user. Intensive simulation examples illustrate the power and flexibility of the proposed methodology.
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