ANFIS Approach for Locating Faults in Underground Cables
نویسنده
چکیده
This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location. Keywords—ANFIS, Fault location, Underground Cable, Wavelet Transform.
منابع مشابه
Prediction of Incipient Faults in Underground Power Cables Utilizing S-Transform and Support Vector Regression
Incipient faults usually emerge from partial discharges which eventually cause insulation degradation between two insulated cable cores. Early detection of incipient faults is of particular importance because insulation defects caused by incipient faults may lead to permanent faults in underground distribution networks. This paper presents a novel approach using S-transform and support vector r...
متن کاملAdaptive neuro-fuzzy inference system based faulty sensor monitoring of indoor air quality in a subway station
−A new faulty sensor monitoring method based on an adaptive neuro-fuzzy inference system (ANFIS) is proposed to improve the monitoring performance of indoor air quality (IAQ) in subway stations. To enhance network performance, a data preprocessing step for detecting outliers and treating missing data is implemented before building the monitoring models. A squared prediction error (SPE) monitori...
متن کاملComparison of Intelligent Methods for Thermal Assessment of Power Cables under Geometrical Parameter Variations
In this paper, the thermal field of underground power cable is solved using two intelligent techniques which are newly introduced for thermal assessment of power cables. A backpropagation neural network (BPNN) and an adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the cable temperature under geometrical parameter variations. The effect of cable spacing and cable b...
متن کاملCalculating Intermediate Faults in Underground Cables
Short-circuit calculations are extremely important in the application and setting of protective relays and the analysis of power system operations. This paper illustrates the calculation of fault currents and voltages during intermediate faults in underground cables, taking into consideration the cable sheath bonding and grounding method. The compensated ground loop impedance for faults along t...
متن کاملAdaptive Neuro-Fuzzy Inference System for Thermal Field Evaluation of Underground Cable System
The influence of thermal circuit parameters on a buried underground cable is investigated using an ANFIS (adaptive neuro-fuzzy inference system). Finite element solution of the heat conduction equation is used, combined with artificial intelligence methods. The cable temperature depends on several parameters, such as the ambient temperature, the currents flowing through the conductor and the re...
متن کامل