Proceedings Article10.1109/APEC.2006.1620775
Predicting load harmonics in three phase systems using neural networks
J. Mazumdar,R.G. Harley,Frank Lambert,Ganesh K. Venayagamoorthy +3 more
- 19 Mar 2006
- pp 1738-1744
TL;DR: In this paper, an artificial neural network (ANN) based method was proposed to measure the actual harmonic current injected into a power system network by three phase nonlinear loads without disconnecting any loads from the network.
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Abstract: This paper proposes a artificial neural network (ANN) based method for the problem of measuring the actual harmonic current injected into a power system network by three phase nonlinear loads without disconnecting any loads from the network. The ANN directly estimates or identifies the nonlinear admittance (or impedance) of the load by using the measured values of voltage and current waveforms. The output of this ANN is a waveform of the current that the load would have injected into the network if the load had been supplied from a sinusoidal voltage source and is therefore a direct measure of load harmonics.
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Citations
•Dissertation
System and method for determining harmonic contributions from nonlinear loads in power systems
Joy Mazumdar
- 13 Nov 2006
23
A Brief Review on Advances of Harmonic State Estimation Techniques in Power Systems
U. Arumugam,Mohd Faris Abdullah +1 more
TL;DR: The author outlines the role of artificial intelligence (AI) in the field and the process overview of neural network and also a hybrid algorithm which combines particle swarm optimization (PSO) and gradient descent (GD) to train the weights of Neural network (NN).
Adaptive Neuro-Fuzzy System for Current Prediction in Electric Arc Furnaces
Manuela Panoiu,Loredana Ghiormez,Caius Panoiu +2 more
- 24 Jul 2014
TL;DR: An adaptive neuro-fuzzy system which is used in the current prediction through the electric arc from an electric arc furnace and performance is presented in this paper based on its architecture and training parameters.
10
Application of neural method of voltage estimation to evaluation of influence of nonlinear loads on electric energy quality
Marek Gala
- 06 Nov 2009
TL;DR: In this article, a neural method of estimation of instantaneous voltage at a considered node of electric power system feeding nonlinear loads is presented, where simulations conducted using MATLAB/SIMULINK as well as results of measurements obtained for a real power network.
5
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TL;DR: In this article, the authors proposed a new method to determine whether the utility or the customer side has more contribution to the harmonic currents measured at the point of common coupling, inspired by the observation that the direction of harmonic reactive power, instead of active power, is a more reliable indicator on the location of dominant harmonic sources.
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