Title :
Real-time closed loop system controlled by an Artificial Neural Network for estimation of the optimal load shedding
Author :
Santos, A.Q. ; Monaro, R.M. ; Coury, Denis ; Oleskovicz, Mario
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Sao Paulo, Sao Carlos, Brazil
fDate :
March 31 2014-April 3 2014
Abstract :
Electrical Power Systems (EPS) are constantly exposed to various disturbances that can significantly affect their operation. Hence, the load shedding philosophy was proposed in order to relieve the overloaded infrastructure in cases of imbalances between generation and demand. However, conventional methods of shedding are slow and inaccurate. In this context, where shedding processes must be optimized, there is a need to pursue new methods and technologies to provide fast and optimized management. Therefore, this paper proposes an Artificial Neural Network (ANN) to estimate the minimum amount of load to be shed in order to recover load-generation balance. The ANN training and testing data were extracted from an EPS simulated using a Real Time Digital Simulator (RTDS). The best ANN topology, selected through cross-validation technique, was able to estimate the load shedding quantity with high precision. The system was then configured to work in a real-time closed loop so that the efficiency of the ANN was tested. The results demonstrate a good generalization over the presented overload situations. As a contribution, this work presents the dynamic of a load shedding scheme controlled by an ANN in real-time closed loop system performed only in one step offering a fast and effective alternative for restoring the frequency close to its nominal value.
Keywords :
closed loop systems; load shedding; neural nets; neurocontrollers; ANN testing; ANN topology; ANN training; EPS; RTDS; artificial neural network; cross-validation technique; electrical power systems; fast management; load shedding philosophy; load shedding quantity; load-generation balance; nominal value; optimal load shedding estimation; optimized management; overload situation; overloaded infrastructure; real time digital simulator; real-time closed loop system; Artificial Neural Networks; Closed Loop; Load Shedding; Real Time Digital Simulator; Real-Time;
Conference_Titel :
Developments in Power System Protection (DPSP 2014), 12th IET International Conference on
Conference_Location :
Copenhagen
Print_ISBN :
978-1-84919-834-9
DOI :
10.1049/cp.2014.0056