| Title |
Fault-tree Analysis Based Life-cycle Expectation for Half-bridge Submodule in HVDC |
| Authors |
강필순(Feel-soon Kang) ; 송성근(Sung-Geun Song) |
| DOI |
https://doi.org/10.5370/KIEE.2020.69.1.42 |
| Keywords |
Neural Network; Backpropagation Algorithm; Market Price; Transmission congestion; Electricity market |
| Abstract |
This paper proposes an application of artificial neural networks for analyzing electricity market that has insufficient information for calculating equilibrium. Neural networks are constructed and trained on two representative cases in the electricity market. One is for calculating equilibrium price in perfect competition market and the other is for determining whether the transmission congestion occurs. The neural network uses a multilayer structure and learns with backpropagation algorithms for training. The neural networks trained in the case studies calculate the market price with a high probability and also determines an occurrence of the transmission congestion accurately. |