DocumentCode :
1955186
Title :
ANN based Z-bus loss allocation for pool dispatch in deregulated power system
Author :
Arunachalam, S. ; Babu, M. Ramesh ; Mohanadasse, K. ; Ramamoorthy, S.
Author_Institution :
St. Joseph´´s Coll. of Eng., Chennai
fYear :
0
fDate :
0-0 0
Abstract :
This paper presents a procedure for ANN based Z-bus loss allocation for pool dispatch in a deregulated power system. The procedure is based on the network Z-bus matrix; although all required computations exploit the sparse Y-bus matrix. One innovative feature of ANN based Z-bus loss allocation is that, it exploits the full set of network equations and does not require any simplifying assumptions. ANN based Z-bus loss allocation is based on a solved load flow and is easily understood and implemented. Most independent system variables can be used as inputs to the neural network which in turn makes the Z-bus loss allocation process responsive to practical situations. Training and testing of this network have been done with the help of a five bus test system. Numerical examples on ANN based Z-bus loss allocation using a feed forward back propagation algorithm has been provided. A trained ANN for loss allocation requires only operational data to calculate the loss allocation at any instant
Keywords :
backpropagation; electricity supply industry deregulation; feedforward neural nets; impedance matrix; load flow; losses; power generation dispatch; power system analysis computing; sparse matrices; transmission networks; ANN; Z-bus loss allocation; deregulated power system; feed forward back propagation algorithm; impedance-admittance matrix; load flow; network Z-bus matrix; neural network; pool dispatch; sparse Y-bus matrix; training; transmission loss; Artificial neural networks; Computer networks; Equations; Feeds; Load flow; Neural networks; Power systems; Propagation losses; Sparse matrices; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power India Conference, 2006 IEEE
Conference_Location :
New Delhi
Print_ISBN :
0-7803-9525-5
Type :
conf
DOI :
10.1109/POWERI.2006.1632578
Filename :
1632578
Link To Document :
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