Neural expert system for loading of overhead lines

被引：0

作者：

Negnevitsky, M ^{[1
]}

Le, TL ^{[1
]}

机构：

[1] Univ Tasmania, Dept Elect Engn & Comp Sci, Hobart, Tas 7001, Australia

来源：

PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2 | 1998年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes an intelligent neural expert system for loading overhead power transmission lines. The system is used to evaluate the:thermal rating and temperature rise of power transmission lines. An artificial neural network (ANN) was trained for the prediction of hourly or instantaneous values of the irradiance dependent on astronomic and meteor-climatic conditions. The developed intelligent system can be used to assist operators in loading power transmission lines in different operating and weather conditions.

引用

页码：797 / 800

页数：4

共 50 条

[41] RECOLLECTIONS OF OVERHEAD LINES
BOYSE, CO
ELECTRONICS AND POWER, 1969, 15 (FEB): : 72 - &
[42] Aluminium for overhead lines
不详
ZEITSCHRIFT DES VEREINES DEUTSCHER INGENIEURE, 1922, 66 : 260 - 260
[43] Lightning Performance Analysis of Overhead Subtransmission Lines in Power System
Phayomhom, A.
Kulwongwit, W.
Rugthaicharoencheep, N.
2014 INTERNATIONAL CONFERENCE ON LIGHTNING PROTECTION (ICLP), 2014, : 2024 - 2027
[44] HANDBOOKS FOR OVERHEAD LINES
CORDOVA, AH
EPRI JOURNAL, 1983, 8 (04): : 26 - 27
[45] Statistical evaluation of lightning overvoltages on overhead distribution lines using neural networks
Martinez, JA
González-Molina, F
2001 IEEE POWER ENGINEERING SOCIETY WINTER MEETING, CONFERENCE PROCEEDINGS, VOLS 1-3, 2001, : 1133 - 1138
[46] Statistical evaluation of lightning overvoltages on overhead distribution lines using neural networks
Martinez, JA
Gonzalez-Molina, F
IEEE TRANSACTIONS ON POWER DELIVERY, 2005, 20 (03) : 2219 - 2226
[47] Probabilistic prediction for the ampacity of overhead lines using Quantile Regression Neural Network
Jin, Xu
Cai, Fudong
Wang, Mengxia
Sun, Yang
Zhou, Shengyuan
2020 INTERNATIONAL CONFERENCE ON ENERGY, ENVIRONMENT AND BIOENGINEERING (ICEEB 2020), 2020, 185
[48] Curative measures identification in congestion management exploiting temporary admissible thermal loading of overhead lines
Kollenda, Katharina
Schrief, Alexander
Biele, Charlotte
Lindner, Martin
Sundorf, Niklas
Hoffrichter, Andre
Roehder, Andreas
Moser, Albert
Rehtanz, Christian
IET GENERATION TRANSMISSION & DISTRIBUTION, 2022, 16 (16) : 3171 - 3183
[49] Variational concepts for arcs and lines in an expert system environment
1784, Publ by Pergamon Press Inc, Tarrytown, NY, USA
[50] Memory and neural network based expert system
Shin, CK
Park, SC
DATA MINING AND KNOWLEDGE DISCOVERY: THEORY, TOOLS, AND TECHNOLOGY, 1999, 3695 : 83 - 91

← 1 2 3 4 5 →