Dynamic behaviour analysis of a heat recovery steam generator during start-up

Kim, T. S.; Lee, D. K.; Ro, Sung Tack

doi:10.1002/(sici)1099-114x(200002)24:2<137::aid-er568>3.0.co;2-0

Cited by 19 publications

(12 citation statements)

References 5 publications

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“…The validity of (A1) to (A3) and (A4) have been tested in [9,10] and [13,14], respectively. Thus, we mainly discuss the assumptions from (A5) to (A7) in the rest of this paper.…”

Section: Physical Assumptionsmentioning

confidence: 99%

“…A.1 Boiler model It is well-known in [9,10] that the dynamic behavior of boiler's pressure is well captured by global mass and energy balances. The global mass balance is given by…”

Section: A Derivation Of Dimensionless Governing Equationsmentioning

confidence: 99%

“…The first one is to derive a lumped-parameter model that captures stability and multiscale properties of steam supply. For internal dynamics in a single boiler or single plant, much work has been reported on lumped-parameter modeling [9,10,11,12], whereas for dynamics of steam flows in pipes, partial differential equations or distributed-parameter models [13,14,15,16] are normally used. Although such models are crucial to plant design, detailed simulation, and commissioning, their simple coupling is too complicated to reveal the system-wide dynamics of interest.…”

Section: Introductionmentioning

confidence: 99%

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A Lumped-Parameter Model of Multiscale Dynamics in Steam Supply Systems

Hoshino

Susuki

Hikihara

2016

Journal of Computational and Nonlinear Dynamics

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This paper focuses on multiscale dynamics occurring in steam supply systems. The dynamics of interest are originally described by a distributed-parameter model for fast steam flows over a pipe network coupled with a lumped-parameter model for slow internal dynamics of boilers. We derive a lumped-parameter model for the dynamics through physically-relevant approximations. The derived model is then analyzed theoretically and numerically in terms of existence of normally hyperbolic invariant manifold in the phase space of the model. The existence of the manifold is a dynamical evidence that the derived model preserves the slow-fast dynamics, and suggests a separation principle of short-term and long-term operations of steam supply systems, which is analogue to electric power systems. We also quantitatively verify the correctness of the derived model by comparison with brute-force simulation of the original model. * Y. Susuki is currently with and also with JST CREST, 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012 Japan 1 In this paper, we newly present the unified description of multiscale dynamics of steam supply systems by proper scaling of governing equations in Sec. 3, derivation of inner-limit of the derived model in Sec. 4, and numerical simulations for phase-space analysis and for verification of the model in Sec. 5, all of which are not reported in [3,4].

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“…The validity of (A1) to (A3) and (A4) have been tested in [9,10] and [13,14], respectively. Thus, we mainly discuss the assumptions from (A5) to (A7) in the rest of this paper.…”

Section: Physical Assumptionsmentioning

confidence: 99%

“…A.1 Boiler model It is well-known in [9,10] that the dynamic behavior of boiler's pressure is well captured by global mass and energy balances. The global mass balance is given by…”

Section: A Derivation Of Dimensionless Governing Equationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Lumped-Parameter Model of Multiscale Dynamics in Steam Supply Systems

Hoshino

Susuki

Hikihara

2016

Journal of Computational and Nonlinear Dynamics

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“…When the integral plant units including gas turbine and HRSG experience dynamic load conditions, more serious is its effect on shortening the service life [7]. In connection with this problem, considerable studies have been carried out to analyze and improve dynamic conditions of start-up process [7][8][9][10][11]. Also, the casing of HRSG can be easy to damage during the start-up.…”

Section: Introductionmentioning

confidence: 99%

Thermal Stress Analysis in Structural Elements of HRSG Casing

Shin¹,

Kim²,

Ahn³

et al. 2012

IJEE

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Heat recovery steam generators (HRSGs) are arranged at the tail end of gas turbines in co mb ined cycle power plants (CCPPs), and are designed to withstand the hot gas environment approaching 600℃. In addition to higher thermal to power efficiency, CCPPs show superior response characteristics compared to those of other conventional steam power plants. For that reason, frequent load changes on the system, which so metimes include daily start and stop (DSS) operation, would impose additional burden on the structural elements. The main objective o f this work is to analy ze the thermal stress conditions as related to the observed failure on the structural elements of HRSG casing, and to find root causes of failure of mechanical integrity. To achieve this goal, field measurements were performed to record temperatures of wall and stiffener of the casing fro m a real plant in operation. To consider the effect of hot gas on the casing, computational fluid dynamic (CFD) analysis of gas flow inside the HRSG with appropriate wall conditions using FLUENT V12. Thermal stress analysis on the thin wall of the casing and stiffeners of HRSG was conducted with the temperature data from the CFD results, using ANSYS Workbench V12. Su mmarizing the computational results, some limited ideas were presented which would be useful to prevent damages.

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“…Under different circumstances, simplified linearized techno-economic models were developed to have a quick but fairly accurate tool to estimate performance and electricity cost [12][13][14][15][16][17]. The extensive modelling displayed in [18][19][20][21] can be used as reference to expand the current mathematical model to allow for transient behaviour evaluation. Large efforts have been made in order to expand these simplified models to incorporate transient behaviour during start-up or brusque load changes [22,23].…”

Section: Introductionmentioning

confidence: 99%