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Navegando por Assunto "Cadeias de Markov"

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    Desenvolvimento a eventos discretos de um controlador de balanceamento de fases para sistemas legados de baixa tensão e microgrids
    (Universidade Federal do Pará, 2019-06-10) VILCHEZ, José Ruben Sicchar; SILVA, José Reinaldo; http://lattes.cnpq.br/9317869378701106; COSTA JÚNIOR, Carlos Tavares da; http://lattes.cnpq.br/6328549183075122
    In the up-grading of the legacy low-voltage system as urban microgrids, phase - balance algorithm development becomes useful and important to ensures robust and reliable load balancing, establish an efficient automation workflow among consumers, the legacy lowvoltage grid and the supervision center of the distribution network of electrical power. It constituting an alternative. This may constitute an alternative phase-balancing control system based on consumer units dynamic switching rather than electrical current injection by microgrids. Formal automation design of these algorithms become an interesting milestone for performance evaluation and properties validation for their insertion in the new microgrid architecture. This may evaluate the system's reliable performance when verifying dynamic properties as well as, the univocal solutions that ensure load transfer and load stability robustness of low-voltage grid, without operation interruptions neither conflicting events. This work, proposes a new phase-load- balancing control system based on combined algorithms resulting from a Hierarchical Petri net system design. Through this model it was obtained an optimized and reliable automated workflow of load balance in the low-voltage grid phases, with an efficient choice of consumer units for the switching process, aiming to obtain a robust steady state of load against unbalances between phases, and neutral current minimized. From the model obtained called “Transformer- Phase Balancing Controller” (T-PBC) were developed four integrated algorithms: the Load Transfer Algorithm, that calculates the load imbalance level and power to be transferred in the transformer phases; the Consumption Diagnose Algorithm, that identifies the load levels margins in each consumer unit; the Consumption Forecast Algorithm, that forecast the monthly energy future states in consumers; and the Switch Selection Algorithm, that selects the consumers units to switch based on the future state of energy consumption, the load level margins and the average of the energy future states. Based on the performance results, it was obtained, the efficient reduction of the neutral current and the load average unbalance in the low-voltage grid phases, with load stability robustness about three months, making it an efficient alternative system against load unbalances in the legacy low-voltage grid and the microgrids.
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    Probabilidade de ocorrência de chuvas e sua variação espacial e temporal na bacia hidrográfica do Rio Tapajós
    (Universidade Federal do Pará, 2017-06-30) SANTOS, Vanessa Conceição dos; BLANCO, Claudio José Cavalcante; http://lattes.cnpq.br/8319326553139808
    Studies of the probability of rainfall and its spatial and temporal variation are important in the planning of agricultural activities and water resources engineering. However, statistical analyzes related to rainfall find limitations regarding the size of the available historical series, which are mostly insufficient or have a large number of faults. A good alternative to overcome these limitations is the generation of pluviometric series through the use of stochastic models. In this sense, the objective was to elaborate a methodology to determine the probability of occurrence of dry and rainy days and to estimate daily average rainfall. Thus, the determination of the occurrences was done using first order Markov Chains and two states and, for the quantities, the cumulative probability distributions Gamma and Weibull were used, whose parameters were estimated by both the Maximum Likelihood Method and By the Method of Moments. The developed model was applied to 80 rainfall stations distributed in the Tapajos River Basin (TRB). The results of the probabilities of occurrence of dry and rainy periods defined for the TRB the dry season from May to September and the rainy season from October to April. The elements of the probability transition matrix and the alpha and beta parameters showed variability in relation to time and, in addition, the influence of the geographic position of the rainfall station on the determination of dry and rainy periods in specific localities. The validation of the model was performed using the Kolgomorov-Smirnov adhesion test, which demonstrated that the average daily rainfall can be estimated with good performance through the first order Markov Chain and two states with the Gamma and Weibull distribution to two Parameters. However, the Gama distribution stood out in the estimation of average daily rainfall for most of the months of the year, except for the months of March, July and December, for which the Weibull distribution proved to be efficient.
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