Fault-tree analysis based life-cycle expectation for half-bridge submodule in HVDC

被引：0
作者：
Kang F.-S. [1 ]
Song S.-G. [2 ]
机构：
[1] Dept. of Electronic and Control Engineering, Hanbat National University
[2] Energy Conversion Research Centre, Korea Electronics Technology Institute
来源：
Kang, Feel-Soon (feelsoon@hanbat.ac.kr) | 1600年 / Korean Institute of Electrical Engineers卷 / 69期
关键词：
Backpropagation Algorithm; Electricity market; Market Price; Neural Network; Transmission congestion;
D O I：
10.5370/KIEE.2020.69.1.42
中图分类号：
学科分类号：
摘要：
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. Copyright © The Korean Institute of Electrical Engineers.
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页码：42 / 49
页数：7
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