Power transmission system losses can typically represent from five to ten percent of the total generation, a quantity worth millions of dollars per year. The purpose of loss allocation in the context of pool dispatch is to assign to each individual generation and load the responsibility of paying for part of the system transmission losses. Since the system losses are non-separable, non-linear functions of the real power generation and loads, the allocation of transmission loss is a challenging and contentious issue in a fully deregulated system.

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Documentation: 
[1] Arunachalam Sundaram, "Training Neural Networks for Loss Allocation in Power System", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/9mrd-ez67. Accessed: Sep. 22, 2020.
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doi = {10.21227/9mrd-ez67},
url = {http://dx.doi.org/10.21227/9mrd-ez67},
author = {Arunachalam Sundaram },
publisher = {IEEE Dataport},
title = {Training Neural Networks for Loss Allocation in Power System},
year = {2020} }
TY - DATA
T1 - Training Neural Networks for Loss Allocation in Power System
AU - Arunachalam Sundaram
PY - 2020
PB - IEEE Dataport
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Arunachalam Sundaram. (2020). Training Neural Networks for Loss Allocation in Power System. IEEE Dataport. http://dx.doi.org/10.21227/9mrd-ez67
Arunachalam Sundaram, 2020. Training Neural Networks for Loss Allocation in Power System. Available at: http://dx.doi.org/10.21227/9mrd-ez67.
Arunachalam Sundaram. (2020). "Training Neural Networks for Loss Allocation in Power System." Web.
1. Arunachalam Sundaram. Training Neural Networks for Loss Allocation in Power System [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/9mrd-ez67
Arunachalam Sundaram. "Training Neural Networks for Loss Allocation in Power System." doi: 10.21227/9mrd-ez67