Steam Turbine models for monitoring purposes

被引：8

作者：

Dettori, S. ^{[1
]}

Colla, V. ^{[1
]}

Salerno, G. ^{[2
]}

Signorini, A. ^{[2
]}

机构：

[1] Scuola Super Sant Anna, TeCIP Inst, PERCRO Lab, Via Alamanni 13D, I-56124 Ghezzano, Italy

[2] Gen Elect Oil & Gas, Via F Matteucci 2, I-50127 Florence, Italy

来源：

8TH INTERNATIONAL CONFERENCE ON APPLIED ENERGY (ICAE2016) | 2017年 / 105卷

关键词：

Steam turbine models; Monitoring; Steam Quality; Neural Networks; Thermodynamic Models; POWER-PLANT; NETWORKS;

D O I：

10.1016/j.egypro.2017.03.351

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The paper proposes two different approaches for steam turbine modelling for on-line monitoring applications, a hybrid-thermodynamic method and a neural network approach. Both models can predict power and other features that cannot be easily measured such as outlet Steam Quality, Pressure and Temperature at drums outlet. Training and validation of both models was carried out by exploiting a dataset created by means the GE sizing design tool. The models were tested by means of real field data of a High Pressure Turbine. (C) 2016 The Authors. Published by Elsevier Ltd.

引用

页码：524 / 529

页数：6

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