Generalized Predictive Control for superheated steam temperature regulation in a supercritical coal-fired power plant

Draganescu, Mihai; Guo, Shen; Wojcik, Jacek D.; Wang, Jihong; Liu, Xiangjie; Hou, Guolian; Xue, Yali; Gao, Qirui

doi:10.17775/cseejpes.2015.00009

Cited by 29 publications

(9 citation statements)

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“…In [16], a state-space MPC method is applied to the control of the core power in a pressurised water reactor. Additional applications of MPC to thermal power plant processes can be found in [36][37][38] for coal-fired power plants, [19,20] for gas-fired power plants, and in [17] for nuclear power plants.…”

Section: Review Of Mpc Applications In Power Plantsmentioning

confidence: 99%

Application of an adaptive model predictive control algorithm on the Pelton turbine governor control

Beus

Pandžić

2020

IET Renewable Power Generation

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Traditionally, hydro turbine governor applications mainly rely on classical proportional-integral-derivative controllers. A classical controller can perform optimally only at the operating point chosen during the controller design. Since hydro power plants are highly non-linear systems alternative control approaches based on adaptive parameters are needed. Historically, due to the limited computation capabilities of microprocessors and programmable logic controllers (PLCs) used in hydro turbine governors, adaptive control schemes were not frequently applied. However, the latest generation of microprocessors and PLCs facilitate the application of adaptive control scheme based on predictive control algorithm for plants with faster dynamic behaviour. In that regard, this study introduces an adaptive controller based on model predictive control (MPC) algorithm developed and applied to a non-linear simulation model of a laboratory hydro power plant. The applied MPC algorithm is based on a linear prediction model whose parameters are identified offline for different operating points across the plant's operating range. The adaptive control scheme updates the prediction model parameters depending on the current operating point. Furthermore, the predictive control algorithm applied in this study is set up as a quadratic programming (QP) optimisation problem that is solved online using a QP solver in a form of Hildreth's algorithm.

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Section: Review Of Mpc Applications In Power Plantsmentioning

confidence: 99%

Application of an adaptive model predictive control algorithm on the Pelton turbine governor control

Beus

Pandžić

2020

IET Renewable Power Generation

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“…The simulation results have been verified by the real operational plant data. More detailed descriptions of the fluid network models can be found in previous publications by the authors' group [17,18].…”

Section: Description Of a Supercritical Power Plant And Simulation Plmentioning

confidence: 99%

Flexible Operation of Supercritical Power Plant via Integration of Thermal Energy Storage

Li¹,

Zhang²,

Wang³

2019

Power Plants in the Industry

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This chapter presents the recent research on various strategies for power plant flexible operations to meet the requirements of load balance. The aim of this study is to investigate whether it is feasible to integrate the thermal energy storage (TES) with the thermal power plant steam-water cycle. Optional thermal charge and discharge locations in the cycle have been proposed and compared. Dynamic modeling and simulations have been carried out to demonstrate the capability of TES integration in supporting the flexible operation of the power plant. The simulation software named SimuEngine is adopted, and a 600 MW supercritical coal-fired power plant model is implemented onto the software platform. Three TES charging strategies and two TES discharging strategies are proposed and verified via the simulation platform. The simulation results show that it is feasible to extract steam from steam turbines to charge the TES and to discharge the stored thermal energy back to the power generation processes. The improved capability of the plant flexible operation is further studied in supporting the responses to the grid load demand changes. The results demonstrated that the TES integration has led to much faster and more flexible responses to the load demand changes.

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“…The temperature of this intermediate steam responds faster to changes in the BFW spray flow rate in comparison to the main steam temperature, which lags due to the thermal and volumetric holdup of the finishing SH. In Configuration 2, the intermediate steam temperature controller manipulates the BFW injection flow rate to Attemperator 2 as shown in Figure 9 [30]. The PID controller that is used for the main steam temperature control generates the set point for the intermediate steam temperature controller.…”

Section: Configurationmentioning

confidence: 99%

Development of a Dynamic Model and Control System for Load-Following Studies of Supercritical Pulverized Coal Power Plants

et al. 2018

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Traditional energy production plants are increasingly forced to cycle their load and operate under low-load conditions in response to growth in intermittent renewable generation. A plant-wide dynamic model of a supercritical pulverized coal (SCPC) power plant has been developed in the Aspen Plus Dynamics® (APD) software environment and the impact of advanced control strategies on the transient responses of the key variables to load-following operation and disturbances can be studied. Models of various key unit operations, such as the steam turbine, are developed in Aspen Custom Modeler® (ACM) and integrated in the APD environment. A coordinated control system (CCS) is developed above the regulatory control layer. Three control configurations are evaluated for the control of the main steam; the reheat steam temperature is also controlled. For studying servo control performance of the CCS, the load is decreased from 100% to 40% at a ramp rate of 3% load per min. The impact of a disturbance due to a change in the coal feed composition is also studied. The CCS is found to yield satisfactory performance for both servo control and disturbance rejection.

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Generalized Predictive Control for superheated steam temperature regulation in a supercritical coal-fired power plant

Cited by 29 publications

References 0 publications

Application of an adaptive model predictive control algorithm on the Pelton turbine governor control

Application of an adaptive model predictive control algorithm on the Pelton turbine governor control

Flexible Operation of Supercritical Power Plant via Integration of Thermal Energy Storage

Development of a Dynamic Model and Control System for Load-Following Studies of Supercritical Pulverized Coal Power Plants

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