Title :
Hybrid Support System for Decision Making Based on MLP-ANN, IED and SCADA for Disturbances Analysis of Electrical Power Distribution Transformers
Author :
Nina, D.L.F. ; da Fonseca Neto, Joao V. ; Ferreira, E.F.M. ; Miranda dos Santos, Alcione
Author_Institution :
Grad. Program in Electr. Eng.-PPGEE, Univ. Fed. do Maranhao, Sao Luis, Brazil
Abstract :
The operation and maintenance of the power system require attention, precise diagnostics on failure and agility on system recovery. In addition, each operation needs to be carefully planned and executed, once errors can be fatal. To improve the operation and maintenance tasks, in this article is presented the proposal of a support system for decision making units based on artificial neural network (ANN), intelligent electronic devices (IED), supervisory control and data acquisition (SCADA) system for disturbances analysis of electrical power distribution transformers. The intelligent system is hybrid in the sense that it performs on-line tasks in real time for data acquisition systems via IED and off-line tasks are performed for analysis of disturbances in electrical power distribution transformers. The hybrid decision making support system (HDMSS) has built a MLP-ANN engine for classifying patterns and providing support for decisions. The MLP-ANN engine is evaluated for fault detection in distribution transformer of electrical power substation. The proposed method was evaluated using real data collected directly from IED, such as: digital relays. The on-line simulations results show the effectiveness and the feasibility of the proposed system based on artificial neural network.
Keywords :
SCADA systems; decision making; decision support systems; electrical maintenance; multilayer perceptrons; power distribution planning; power engineering computing; power system faults; power system simulation; power transformers; relays; substations; HDMSS; IED; MLP-ANN; MLP-ANN engine; SCADA; decision making units; digital relays; disturbance analysis; electrical power distribution transformers; electrical power substation; fault detection; hybrid decision making support system; intelligent electronic devices; intelligent system; off-line tasks; on-line simulation results; power system failure; power system maintenance; power system operation; precise diagnostics; supervisory control and data acquisition system; system recovery; Artificial neural networks; Decision making; Neurons; Power transformers; Substations; Training; Vectors; Substations Automation; Faults; Electrical Distribution Power Systems; Artificial Neural Network; Decision Making Systems; SCADA System; Electronic Intelligent Devices;
Conference_Titel :
Computer Modelling and Simulation (UKSim), 2013 UKSim 15th International Conference on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4673-6421-8
DOI :
10.1109/UKSim.2013.147