Resumo:
The growing technological evolution with the expanding use of Microelectronics associated with Power Electronics in various economic segments, especially the industrial field, has influenced the progressive increase in the presence of sensitive loads, which results in increasingly frequent records of intercurrences related to faults in the Electric Power System. Voltage sags (or voltage dips) stand out as one of the most frequent Short Duration Voltage Variations, representing enormous damage to the production chain and consumers in general. The application of preventive measures both in the planning and in the Electric Power System specification has been shown to be an alternative to minimize or avoid Power Quality Problems and therefore statistical prediction analyses are necessary.
Given this, the present work presents a case study applied to the Basic Power Grid of Bahia (230 and 500 kV bars) using two stochastic approaches in the quantitative and qualitative estimation of the occurrence of voltage sags originated from short circuits on transmission lines: Method of Fault Positions and Monte Carlo Simulation.
As observed by the results, with few simulations the Method of Fault Positions allowed the mapping of the system's vulnerability zone, while the Monte Carlo Simulation technique validated the critical area, making it possible to add randomness to the variables that influence the occurrence of the fault (transmission line, fault position, fault type, and fault impedance), given from known probability distributions. The comparative graphs showed that when considering the fault impedance at random, the cumulative frequencies were between the two curves that represent the minimum (0 $\Omega$) and maximum (15 $\Omega$) extreme values of the number of voltage sags expected annually. In addition, the probability density functions associated with other classes of voltage values for voltage sags indicate a shift to the right (increase in the number of sags) or left (decrease in the number of defects) of the density curves, being noted in an overall, the reduction in sags with increasing fault impedance. However, the study reveals that the reduction of sags will not necessarily imply fewer severities of sags in the Electric Power System since they tend to increase the probability density in classes below 0.5 p.u.
