Pimentel Filho, Max ChiancaAzevedo, Thales Bruno Costa de2019-12-092019-12-092019-09-12AZEVEDO, Thales Bruno Costa de. Otimização da demanda de potência contratada utilizando algoritmos genéticos: o caso do campus central da UFRN. 2019. 78f. Dissertação (Mestrado Profissional em Energia Elétrica) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2019.https://repositorio.ufrn.br/jspui/handle/123456789/28173For consumers served by the voltage higher than 2,3 kV, belonging to the group A, the active power demand value to be contracted with power distribution company comes to be one the most important factors in the final value power bill. In moments that the resources are few, the great choice of this demand, as well as of the most useful tariff modality, it will need be done of such way that the power and energy demanded are available with no additional costs, and the value to be paid be as small as possible. This work shows a optimization purpose by the genetic algorithms, applied to the problem of the active power demand contraction, faced by the clients of group A, included in the blue horary tariff modality, where is necessary to be contracted a demand value at the peak hours and another value demand at the out of peak hours. The data used in this work were the measured demand values available by the central campus of the Federal University of Rio Grande do Norte. Simulations were done, considering its historical of the energy bills, since the its particular power substation of 69/13,8 kV began to operate, it was began the billing in this new tariff modality. The results were compared with the costs by the current contracted demand values, they were also compared with the exhaustive search method, and they show that the optimization model with genetic algorithms is a nice tool to the determine the optimal demand value to be contracted.Acesso AbertoOtimizaçãoDemanda contratadaAlgoritmos genéticosmasterThesisCNPQ::ENGENHARIAS::ENGENHARIA ELETRICA