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This paper presents a methodology based on genetic algorithms that allows the reordering of the existing park transformers voltage level I of the distribution systems of Bogotá city, Colombia, in order to maximize the recognition of assets that the regulator CREG (Comisión Reguladora de Energía y Gas) made to the various network operators, as set out in resolution 097 of 2008. For the application of the algorithm, we obtained maximum active power measurements for each hour of the year 2009 in a number of transformers of different capacities, chosen at random, installed in the distribution system CODENSA SA ESP, the company that provides electric service in the Bogotá city. With this information we built representative daily load curves and developed a database that contains the operating costs of moving equipment and tariffs, from which it was possible to model the objective function and constraints of the problem, obtaining a high number of possible combinations (about 1 * 10134) due to the large number of nodes and processors present in the distribution system. Conventional search of a solution in the above situation implies the use of prohibitive times. For this reason we implemented a classical genetic algorithm, thus obtaining an optimal solution that offers a financial gain in the first year, associated with the increase in the usage charge, of $ 253.446.362,47 (COP), profits that could be increased considerably when running the algorithm on larger transformers parks. [ABSTRACT FROM AUTHOR]

This paper presents a methodology based on genetic algorithms that allows the reordering of the existing park transformers voltage level I of the distribution systems of Bogotá city, Colombia, in order to maximize the recognition of assets that the regulator CREG ( Comisión Reguladora de Energía y Gas) made to the various network operators, as set out in resolution 097 of 2008. For the application of the algorithm, we obtained maximum active power measurements for each hour of the year 2009 in a number of transformers of different capacities, chosen at random, installed in the distribution system CODENSA SA ESP, the company that provides electric service in the Bogotá city. With this information we built representative daily load curves and developed a database that contains the operating costs of moving equipment and tariffs, from which it was possible to model the objective function and constraints of the problem, obtaining a high number of possible combinations (about 1 * 10134) due to the large number of nodes and processors present in the distribution system. Conventional search of a solution in the above situation implies the use of prohibitive times. For this reason we implemented a classical genetic algorithm, thus obtaining an optimal solution that offers a financial gain in the first year, associated with the increase in the usage charge, of $ 253.446.362,47 (COP), profits that could be increased considerably when running the algorithm on larger transformers parks. [ABSTRACT FROM AUTHOR]