Algoritmo genético para alocação ótima de sensores de corrente para detecção de faltas de alta impedância

Abstract

High impedance faults are defects that occur in electricity transmission and distribution networks. In parallel with the loss of power, this type of fault threatens lives in the area close to the contact, and can cause damage to structures, fatalities and fires, negatively impacting the DEC (Equivalent Duration of Interruption per Consumer Unit) and FEC (Equivalent Frequency of Interruption per Consumer Unit) indices. Several studies aim to develop an efficient platform for detecting this type of disturbance, since traditional detection methods are unable to identify the intrinsic characteristics of this event. At the same time, with the evolution of computational methods, problem solving has gained new tools. Neural networks, evolutionary algorithms, fuzzy logic and other methods, combined with the increase in computing power, favor hardware implementation and, consequently, help in the development of methods for detecting HIFs. This work aims to implement an algorithm for detecting HIFs combined with an algorithm for optimized sensor allocation. The results demonstrate that the detection algorithm need to robustness, since the allocation algorithm depends for that. Overall, the work demonstrates that the allocation algorithm can research a satisfactorily reduction in the number of sensors to optimized response, and the allocation algorithm is an important tool for increasing the effectiveness of HIFs detection methods.