Extração de regras operacionais ótimas de sistemas de distrubuição de água através de algoritmos genéticos multiobjetivo e aprendizado de máquina / Extraction of optimal operation rules of the water distribution systems using multiobjective genetic algorithms and machine learning




The efficient operation of a system is a fundamental tool to postpone the system’s service life as much as possible, thus ensuring a good service to the consumer while keeping electrical energy and maintenance costs at acceptable levels. Efficient operation requires knowledge of the system, for this knowledge, supported by tools such as models for hydraulic simulation, optimization, and definition of rules, provides the operator with proper conditions for the rational operating of the system’s units without depending exclusively on personal experience while maintaining the system’s reliability. In this work is developed a computational model for the optimal operation control of macro water distribution systems using a hydraulic simulator, an optimization algorithm, and a learn algorithm to extract operational rules (strategies) for the system. These studies are to be based on the macro system of the city of Goiânia, in Brazil. The results show that solutions for satisfactory operation can be quickly produced as a substitute to the personal judgment of the operator.


aprendizado de máquina operação ótima otimização multiobjetivo algoritmos genéticos genetic algorithms machine learning optimal operation multiobjective optimization

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