Improved internal-model robust adaptive control with its application to coordinated control of USC boiler-turbine power units in flexible operations

Pan, Lei; Shen, Jiong; Wu, Xiao; Nguang, Sing Kiong; Chen, Chen

doi:10.1080/00207721.2020.1737267

Cited by 12 publications

(3 citation statements)

References 24 publications

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“…The same parameter optimization method as LSTM was adopted for the BPNN, and the learning rate, the number of hidden layers and the hidden nodes were carefully optimized. It was finally determined that the BPNN has a structure of [29,20] with a learning rate of 0.01. A radial basis function (RBF) kernel was selected as the kernel function in the SVM model.…”

Section: Comparison With Different Modelling Methodsmentioning

confidence: 99%

“…Based on the dynamic model, researchers have conducted extensive research to improve the regulation of steam temperatures using dynamic matrix control [25], neuro-PID control [26], fuzzy model predictive control [27], and predictive feedforward control [28]. Due to the strong ability to address problems of multiple variables, large inertia and time delay in control processes, model predictive control (MPC) has been considered to be one of the most promising approaches to control boiler-turbine units [29]. Wu et al [27] developed a stable fuzzy model predictive controller (SFMPC) to solve the SST control problem in a power plant.…”

Section: Introductionmentioning

confidence: 99%

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Modelling and regulation of steam temperatures of a 1000‐MW double‐reheat boiler with long short‐term memory

Zhu,

Tan,

et al. 2023

IET Control Theory & Appl

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With the increase in the proportion of new energy power generation in grids, there is an urgent need for the flexible operation of coal‐fired power plants. However, as the most efficient commercial coal‐fired power generation technology, the flexibility of double‐reheat ultra‐supercritical units is limited due to the steam temperature fluctuation in transient processes. To inhibit the steam temperature fluctuations, a data‐driven method, called long short‐term memory (LSTM) was introduced to model the dynamics of the steam temperatures of a 1000‐MW double‐reheat coal‐fired boiler. Moreover, an advanced controller was proposed by combining the LSTM‐based dynamic model and the model predictive control architecture. The results demonstrate that the LSTM model can be used to capture the time delay, multivariable coupling and non‐linear dynamics of the steam temperatures and the proposed controller exhibits excellent performance in steam temperature regulation. The superheated steam temperature fluctuation decreases from 15.4 to 9.8°C, the primary reheat temperature fluctuation decreases from 34.6 to 8.3°C, and the secondary reheat temperature fluctuation decreases from 41.4 to 8.8°C. The proposed method has good potential to stabilize steam temperatures during transient processes of wide‐range load cycling, and finally improves the flexibility of the double‐reheat ultra‐supercritical unit.

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Section: Comparison With Different Modelling Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling and regulation of steam temperatures of a 1000‐MW double‐reheat boiler with long short‐term memory

Zhu,

Tan,

et al. 2023

IET Control Theory & Appl

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“…Niu et al 16 established a simplified dynamic model for a once‐through boiler‐turbine unit at low load operating conditions. Pan et al 17 introduced an internal‐model robust adaptive control (IM‐RAC) approach and designed an IM‐RAC coordinated controller for a 1000 MW supercritical coal‐fired unit to improve the operational flexibility of the unit. Wang et al 18 presented a modified water‐to‐fuel ratio (WFR) control strategy based on the thermal storage temperature difference and tested it on an established coal‐fired power plant model.…”

Section: Introductionmentioning

confidence: 99%

A novel thermal power unit with feedwater pump turbine driven by thermal energy storage system: System construction and performance evaluation

Cao

Zhang

Zhao

et al. 2022

Intl J of Energy Research

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Summary The rapid development of renewable energy power generation brings the strong demand of load regulation capacity for the coal‐fired thermal power unit. This paper presents a novel approach to improving its operational flexibility with a feedwater pump turbine driven by a thermal energy storage (TES) system. The purpose of this study is to investigate the feasibility of the proposed system and evaluate its system performance. During energy charging process, some steam is extracted from hot reheat pipe to heat the TES system and reduce the power generation. During energy discharging process, the feedwater pump turbine is driven by the steam generated from the stored heat instead of extracting from the main turbine. Performance evaluation was conducted based on a model of a 660 MW supercritical thermal power unit. The results show that a low TES outlet steam temperature during the charging process should be employed and extracting water from the pipe between condenser and No. 8 heater during the discharging process should be adopted. The peak regulation range can be expanded from (198‐660 MW) to (188.41‐685.15 MW) without charging the boiler load rate. Hence, the proposed novel system is demonstrated to be an effective way for flexibility improvement of thermal power unit.

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Introduction

Chen

Cheng

2022

Reconstruction and Intelligent Control for Power Plant

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Improved internal-model robust adaptive control with its application to coordinated control of USC boiler-turbine power units in flexible operations

Cited by 12 publications

References 24 publications

Modelling and regulation of steam temperatures of a 1000‐MW double‐reheat boiler with long short‐term memory

Modelling and regulation of steam temperatures of a 1000‐MW double‐reheat boiler with long short‐term memory

A novel thermal power unit with feedwater pump turbine driven by thermal energy storage system: System construction and performance evaluation

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