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Jiong Shen
Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, PR China

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Journal article
Published: 14 August 2021 in Energy Conversion and Management
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Coal-fired power plants with direct air-cooling condensers (DACC-CFPPs) have been widely used in areas rich in coal but short of water since they can significantly reduce water consumption. Despite its water-saving advantages, direct air-cooling condensers have inherent defects such as environmental and load sensitivity, higher costs and poor cooling performance, which deteriorate the economics and flexibility of the integrated system. For safe, efficient and flexible operation, this paper presents the development of a direct air-cooling condenser dynamic model integrated with a 600 MWe coal-fired power plant to study the interactions between heat and power within the entire DACC-CFPP under various load and ambient conditions. The condenser is modeled in a one-dimensional multi-section manner to reflect the impacts of crosswind and ambient temperature disturbances. A detailed turbine-feedwater heater system model is also developed to link the direct air-cooling condenser and power plant together. Steady-state and dynamic validations under various operating conditions are conducted, which demonstrate the high fidelity of the developed model. Simulation studies are then carried out to investigate the dynamic interactions between boiler-turbine, condenser and environmental conditions. We find that manipulating the fan array speed controls the condenser pressure effectively in terms of environmental disturbance rejection and load ramping. Motivated by this finding, a novel variable condenser pressure operating mode is proposed to coordinate the direct air-cooling condenser and coal-fired power plant operation, which can significantly improve the load tracking performance of the integrated plant.

ACS Style

Mingjuan Zhu; Xiao Wu; Jiong Shen; Kwang Lee. Dynamic modeling, validation and analysis of direct air-cooling condenser with integration to the coal-fired power plant for flexible operation. Energy Conversion and Management 2021, 245, 114601 .

AMA Style

Mingjuan Zhu, Xiao Wu, Jiong Shen, Kwang Lee. Dynamic modeling, validation and analysis of direct air-cooling condenser with integration to the coal-fired power plant for flexible operation. Energy Conversion and Management. 2021; 245 ():114601.

Chicago/Turabian Style

Mingjuan Zhu; Xiao Wu; Jiong Shen; Kwang Lee. 2021. "Dynamic modeling, validation and analysis of direct air-cooling condenser with integration to the coal-fired power plant for flexible operation." Energy Conversion and Management 245, no. : 114601.

Journal article
Published: 13 July 2021 in Energy
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Direct air-cooling is considered as a promising technique in power generation because of its huge water-saving advantages. However, this is accompanied by inherent sensitivity to meteorological and ambient conditions, which is liable to cause frequent detrimental fluctuations in the condenser pressure and unit operation stability/economy. Therefore, a higher requirement has been imposed on the control system to achieve stable and economic operation of direct air-cooling condenser. To this end, a dynamic direct air-cooling condenser pressure model is first established in this paper after taking fully consideration of both condenser dynamics and couplings with adjacent systems. Then, two control methods, namely zone model predictive control and zone economic model predictive control are applied to the established model to realize zone control of the condenser pressure while suppressing control quantity variations resulting from time-varying ambient temperature. Detailed quantitative analysis of the influence of direct air-cooling condenser pressure on the turbine bleed flow and unit economy has been performed after both model steady-state and dynamic verification, and the comparative control simulation results under two typical cases have illustrated that the proposed zone economic model predictive controller provides a flexible way to simultaneously deal with the ambient temperature changes and economic optimization issues.

ACS Style

Yi Zhang; Jinfeng Liu; Tingting Yang; Jianbang Liu; Jiong Shen; Fang Fang. Dynamic modeling and control of direct air-cooling condenser pressure considering couplings with adjacent systems. Energy 2021, 236, 121487 .

AMA Style

Yi Zhang, Jinfeng Liu, Tingting Yang, Jianbang Liu, Jiong Shen, Fang Fang. Dynamic modeling and control of direct air-cooling condenser pressure considering couplings with adjacent systems. Energy. 2021; 236 ():121487.

Chicago/Turabian Style

Yi Zhang; Jinfeng Liu; Tingting Yang; Jianbang Liu; Jiong Shen; Fang Fang. 2021. "Dynamic modeling and control of direct air-cooling condenser pressure considering couplings with adjacent systems." Energy 236, no. : 121487.

Journal article
Published: 18 June 2021 in Energy
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Humidity and voltage are the critical parameters that have a significant influence on the thermal stability and electrical efficiency of the proton exchange membrane fuel cells (PEMFCs). However, the inherent coupling between the two parameters makes the controller design challenging from a system's perspective. Furthermore, frequent load fluctuations during fuel cell operation give rise to considerable fluctuations in voltage and humidity. To mitigate this undesirable variation, the system coupling of voltage and humidity and nonlinearity resulting from varying load are analyzed in this paper, where the coupled dynamics of relative humidity and output voltage are manipulated by the humidifier electrical power and compressor voltage. Based on the analysis, a multi-model predictive control (MMPC) scheme is formulated for the coupled plant dynamics, where the prediction model utilized is developed based on the subspace identification method for local models integrated with fuzzy membership weightings. The MMPC formulation has taken advantage of considering the actuator saturation and the allowable output range as input and output constraints. Simulation results show that the proposed MMPC can improve the tracking performance with a flexible trade-off between the relative humidity and output voltage.

ACS Style

Hao Fu; Jiong Shen; Li Sun; Kwang Y. Lee. In-depth characteristic analysis and wide range optimal operation of fuel cell using multi-model predictive control. Energy 2021, 234, 121226 .

AMA Style

Hao Fu, Jiong Shen, Li Sun, Kwang Y. Lee. In-depth characteristic analysis and wide range optimal operation of fuel cell using multi-model predictive control. Energy. 2021; 234 ():121226.

Chicago/Turabian Style

Hao Fu; Jiong Shen; Li Sun; Kwang Y. Lee. 2021. "In-depth characteristic analysis and wide range optimal operation of fuel cell using multi-model predictive control." Energy 234, no. : 121226.

Research article
Published: 06 April 2021 in Transactions of the Institute of Measurement and Control
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Path following control of underactuated autonomous vessels remains a challenging issue in recent years due to its inherent underactuation and nonlinearities as well as the widely existing disturbances in the marine environment. In order to accommodate all the difficulties simultaneously, a novel extended state Kalman filter, which adopts the idea of extended state observer in estimating and compensating system lumped disturbance and optimizes the filter gain in a real-time fashion using Kalman filter technique, is constructed to estimate system states and disturbances in the presence of model uncertainties and measurement noise. Based on the estimated states and disturbances, an enhanced model predictive controller is proposed to steer the underactuated autonomous vessels along a predefined path at a desired speed after considering system state and input constraints. Simulation results have proved the superiority of extended state Kalman filter over traditional extended state observer and extended Kalman filter under various disturbance and noise scenarios. Moreover, the comparison results with conventional proportion-integration-differentiation controller have demonstrated the feasibility and efficacy of the proposed extended state Kalman filter-based model predictive controller in both set-point tracking and disturbance rejection.

ACS Style

Yi Zhang; Wenchao Xue; Li Sun; Jiong Shen. Extended state Kalman filter-based path following control of underactuated autonomous vessels. Transactions of the Institute of Measurement and Control 2021, 1 .

AMA Style

Yi Zhang, Wenchao Xue, Li Sun, Jiong Shen. Extended state Kalman filter-based path following control of underactuated autonomous vessels. Transactions of the Institute of Measurement and Control. 2021; ():1.

Chicago/Turabian Style

Yi Zhang; Wenchao Xue; Li Sun; Jiong Shen. 2021. "Extended state Kalman filter-based path following control of underactuated autonomous vessels." Transactions of the Institute of Measurement and Control , no. : 1.

Conference paper
Published: 01 March 2021 in IOP Conference Series: Earth and Environmental Science
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Due to the uncertainty of the energy supply and the power demand, the stability and economic performance of the integrated energy system has become a key problem. In this paper, economic model predictive control with augmented model was directly applied to optimize the performance index while responding power demand. Based on the prices of power and hot water, the economic objective function was designed and two modes of operation of heating have been studied which include providing domestic hot water and space heating. The simulation result shows, compared with traditional model predictive control, economic model predictive control could improve economic performance of system by 20% while providing domestic hot water, and showed similar performance while working on space heating.

ACS Style

H L Yang; J Shen; Y H Jin; J L Zhang. Application of Economic Model Predictive Control in Integrated Energy System. IOP Conference Series: Earth and Environmental Science 2021, 701, 012028 .

AMA Style

H L Yang, J Shen, Y H Jin, J L Zhang. Application of Economic Model Predictive Control in Integrated Energy System. IOP Conference Series: Earth and Environmental Science. 2021; 701 (1):012028.

Chicago/Turabian Style

H L Yang; J Shen; Y H Jin; J L Zhang. 2021. "Application of Economic Model Predictive Control in Integrated Energy System." IOP Conference Series: Earth and Environmental Science 701, no. 1: 012028.

Journal article
Published: 23 July 2020 in Energies
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Regulating performance of the main steam temperature (MST) system concerns the economy and safety of the coal-fired power plant (CFPP). This paper develops an offset-free offline robust model predictive control (RMPC) strategy for the MST system of CFPP. Zonotope-type uncertain model is utilized as the prediction model in the proposed RMPC design owing to its features of higher accuracy, compactness of representation and less complexity. An offline RMPC aiming at the system robustness and computational efficiency is then developed to maintain the desired steam temperature in case of wide operating condition change. The proposed RMPC is realized by two stages: in the first stage, the RMPC law set, which is the piecewise affine (PWA) of the MST system state is designed offline; then in the second stage, the explicit control law is selected online according to the current state. To achieve an offset-free tracking performance, a manipulated variable target observer is employed to update the chosen RMPC law. The control simulations using on-site operating data of a 1000 MW ultra-supercritical power plant show that the proposed approach can achieve satisfactory control performance and online computation efficiency even under complicated operating conditions.

ACS Style

Di Wang; Xiao Wu; Jiong Shen. An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant. Energies 2020, 13, 3775 .

AMA Style

Di Wang, Xiao Wu, Jiong Shen. An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant. Energies. 2020; 13 (15):3775.

Chicago/Turabian Style

Di Wang; Xiao Wu; Jiong Shen. 2020. "An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant." Energies 13, no. 15: 3775.

Journal article
Published: 02 June 2020 in Control Engineering Practice
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Bed temperature control, being of great significance for the safety, durability and NOx reduction of circulating fluidized bed (CFB) boiler, is nowadays becoming increasingly challenging due to the participation of CFB boiler in load regulation and the existence of various uncertainties such as the feed fuel quality variation and other unknown disturbances. To this end, this paper develops an engineering-friendly multi-model predictive sliding mode control (MM-PSMC) strategy for bed temperature regulation to attain a better adaption to wide load variation. A second-order plus time-delay (SOPDT) model based predictive sliding mode controller (PSMC) is designed to deal with the time-delay, model parameter uncertainty and external disturbances, and taken as local controller in MM-PSMC. An improved hysteresis switching logic is introduced to select a controller that is most suitable for the current operating condition and avoid system chattering caused by fast and unnecessary switching of controllers among local models. Simulation results on a 220t/h CFB boiler demonstrate the merits of the proposed MM-PSMC strategy over a wide operating range, depicting a promising prospect in industrial applications.

ACS Style

Hongxia Zhu; Jiong Shen; Kwang Y. Lee; Li Sun. Multi-model based predictive sliding mode control for bed temperature regulation in circulating fluidized bed boiler. Control Engineering Practice 2020, 101, 104484 .

AMA Style

Hongxia Zhu, Jiong Shen, Kwang Y. Lee, Li Sun. Multi-model based predictive sliding mode control for bed temperature regulation in circulating fluidized bed boiler. Control Engineering Practice. 2020; 101 ():104484.

Chicago/Turabian Style

Hongxia Zhu; Jiong Shen; Kwang Y. Lee; Li Sun. 2020. "Multi-model based predictive sliding mode control for bed temperature regulation in circulating fluidized bed boiler." Control Engineering Practice 101, no. : 104484.

Journal article
Published: 30 May 2020 in International Journal of Hydrogen Energy
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Humidity of proton exchange membrane fuel cell, a critical underlying variable that affects stack efficiency and durability, is quite challenging to be well controlled due to the measuring difficulty and multiple couplings with other variables. For precise humidity description and control, this paper utilizes the internal water content as the feedback signal, whose dynamic model is developed by taking into account various auxiliary couplings. Based on the mechanistic model, the dynamic responses of the internal water content are exhibited and analyzed by manipulating the external current, air compressor voltage and humidifier electrical power, respectively. It is shown that the internal water content is able to better describe the real humidity environment, in contrast with the conventional method using cathode inlet relative humidity. Furthermore, a combined feed-forward and feedback control structure is proposed to maintain the internal humidity as close to the desired as possible. Simulation results show that the proposed control method is able to maintain the fuel cell operating within the safe and efficient region, and the humidification power consumption can be reduced because of the precise and less conservative description on the internal humidity.

ACS Style

Hao Fu; Jiong Shen; Li Sun; Kwang Y. Lee. Fuel cell humidity modeling and control using cathode internal water content. International Journal of Hydrogen Energy 2020, 46, 9905 -9917.

AMA Style

Hao Fu, Jiong Shen, Li Sun, Kwang Y. Lee. Fuel cell humidity modeling and control using cathode internal water content. International Journal of Hydrogen Energy. 2020; 46 (15):9905-9917.

Chicago/Turabian Style

Hao Fu; Jiong Shen; Li Sun; Kwang Y. Lee. 2020. "Fuel cell humidity modeling and control using cathode internal water content." International Journal of Hydrogen Energy 46, no. 15: 9905-9917.

Articles
Published: 11 March 2020 in International Journal of Systems Science
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Coordinated controllers for coal-fired ultra-supercritical (USC) boiler-turbine power units in the new flexible-operation mode face many challenges, such as faster load-following rate over wider-range operations, nonlinear dynamics with long time delay and multiple disturbances from strong-coupled multivariable processes. Hence, to improve the coordinated controller of the USB power unit, this paper proposes an internal-model robust adaptive control (IM-RAC) approach to handle nonlinearity, multiple variables, unknown uncertainties and long-time delay. The proposed IM-RAC augments an internal model with the framework of an L1 robust adaptive control to predict the time-delay variable. In addition, the proposed IM-RAC uses a dual-feedback adaptive law instead of a single-feedback adaptive law. Based on the proof by contradiction, the stability of the IM-RAC control loop is proved, and stability conditions and performance bounds are derived. Furthermore, an IM-RAC coordinated controller is designed for a 1000 MW coal-fired USC power unit. By simulations, we show that the proposed IM-RAC outperforms an advanced model predictive controller in the presences of fast and wide load-following, long-time delay and uncertainties. With less modelling requirements, the IM-RAC control approach is a promising solution to improve the operational flexibility of USC power units.

ACS Style

Lei Pan; Jiong Shen; Xiao Wu; Sing Kiong Nguang; Chen Chen. Improved internal-model robust adaptive control with its application to coordinated control of USC boiler-turbine power units in flexible operations. International Journal of Systems Science 2020, 51, 669 -686.

AMA Style

Lei Pan, Jiong Shen, Xiao Wu, Sing Kiong Nguang, Chen Chen. Improved internal-model robust adaptive control with its application to coordinated control of USC boiler-turbine power units in flexible operations. International Journal of Systems Science. 2020; 51 (4):669-686.

Chicago/Turabian Style

Lei Pan; Jiong Shen; Xiao Wu; Sing Kiong Nguang; Chen Chen. 2020. "Improved internal-model robust adaptive control with its application to coordinated control of USC boiler-turbine power units in flexible operations." International Journal of Systems Science 51, no. 4: 669-686.

Journal article
Published: 01 February 2020 in Energy
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This paper develops an intelligent predictive controller (IPC) for a large-scale solvent-based post-combustion CO2 capture (PCC) process. An artificial neural network (NN) model is trained to represent the dynamics of the PCC process based on an in-depth behavior investigation of the process under different operating conditions. The resulting NN model can portray the PCC characteristics very well in terms of dynamic trend, response time and steady-state gain. An intelligent predictive controller is thus developed based on the NN model to track the desired CO2 capture level and maintain the given re-boiler temperature, in which the particle swarm optimization (PSO) algorithm is applied to find the best future control sequence for the PCC process. A warm start scheme is proposed in the IPC to improve the quality of initial swarm in the PSO. Dynamic simulations to change CO2 capture level set-point and flue gas flow rate are carried out on the PCC process. The results show that the IPC can adjust CO2 capture level fast and significantly reduce the fluctuations in re-boiler temperature. It is concluded that the proposed IPC is helpful for flexible operation of the solvent-based PCC process.

ACS Style

Xiao Wu; Jiong Shen; Meihong Wang; Kwang Y. Lee. Intelligent predictive control of large-scale solvent-based CO2 capture plant using artificial neural network and particle swarm optimization. Energy 2020, 196, 117070 .

AMA Style

Xiao Wu, Jiong Shen, Meihong Wang, Kwang Y. Lee. Intelligent predictive control of large-scale solvent-based CO2 capture plant using artificial neural network and particle swarm optimization. Energy. 2020; 196 ():117070.

Chicago/Turabian Style

Xiao Wu; Jiong Shen; Meihong Wang; Kwang Y. Lee. 2020. "Intelligent predictive control of large-scale solvent-based CO2 capture plant using artificial neural network and particle swarm optimization." Energy 196, no. : 117070.

Journal article
Published: 01 January 2020 in IFAC-PapersOnLine
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Most stand-alone integrated energy systems (IES) with renewable energy can only meet the demand of electrical load, not both electrical load and thermal load. Those studies on combined heat and power cogeneration systems mainly focus on the optimal scheduling of each source, ignoring the difference in dynamic response between electrical and thermal processes. In fact, the different response speeds of electrical and thermal objects will bring in challenges to control. In order to specify and solve the issue, this paper proposes a detailed mechanism model of a standard IES. A model predictive control (MPC) controller is designed and tuned based on the state-space form of the system. The control simulation results imply the feasibility of the MPC controller in coordinating both electricity and heat.

ACS Style

Yuhui Jin; Junli Zhang; Xiao Wu; Jiong Shen; Kwang Y. Lee. Coordinated Control for Combined Heat and Power Load of an Integrated Energy System. IFAC-PapersOnLine 2020, 53, 13184 -13189.

AMA Style

Yuhui Jin, Junli Zhang, Xiao Wu, Jiong Shen, Kwang Y. Lee. Coordinated Control for Combined Heat and Power Load of an Integrated Energy System. IFAC-PapersOnLine. 2020; 53 (2):13184-13189.

Chicago/Turabian Style

Yuhui Jin; Junli Zhang; Xiao Wu; Jiong Shen; Kwang Y. Lee. 2020. "Coordinated Control for Combined Heat and Power Load of an Integrated Energy System." IFAC-PapersOnLine 53, no. 2: 13184-13189.

Journal article
Published: 01 January 2020 in IFAC-PapersOnLine
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The integrated energy system (IES) plays an important role in the development of clean energy through the complementary advantages of multi energy and the absorption capacity of renewable energy. However, because of the multi energy coupling and the intermittence of renewable energy, the risk of system dynamic instability increases. In order to solve the above issues, this paper considers the influence of the dynamic characteristics of the system from the level of planning and design stage. Based on the solar intensity and load demand curve of typical winter days and considering the daily economic operation of typical days and the dynamic characteristics of the system, an IES capacity configuration optimization model is established, which takes into account the system investment cost and the dynamic characteristics of the system. Then the genetic algorithm with penalty function is used to optimize the solution. Finally, according to the typical winter day data of a certain area in Nanjing, P.R.China, the rationality and validity of the model are verified, and the scientific configuration of an IES capacity considering dynamic performance is realized, which provides ideas and support for the planning and design of an IES later.

ACS Style

Yuxuan Li; Junli Zhang; Xiao Wu; Jiong Shen; Kwang Y. Lee. Capacity Configuration of Integrated Energy System Considering Equipment Inertia. IFAC-PapersOnLine 2020, 53, 13088 -13093.

AMA Style

Yuxuan Li, Junli Zhang, Xiao Wu, Jiong Shen, Kwang Y. Lee. Capacity Configuration of Integrated Energy System Considering Equipment Inertia. IFAC-PapersOnLine. 2020; 53 (2):13088-13093.

Chicago/Turabian Style

Yuxuan Li; Junli Zhang; Xiao Wu; Jiong Shen; Kwang Y. Lee. 2020. "Capacity Configuration of Integrated Energy System Considering Equipment Inertia." IFAC-PapersOnLine 53, no. 2: 13088-13093.

Journal article
Published: 05 November 2019 in Chemical Engineering Research and Design
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In this work, a zone economic model predictive controller is proposed for the operation of a boiler-turbine generating system. The control objective is to optimize the operating economics while satisfying the power generation demand from the grid. First, the considered boiler-turbine system is introduced and the economic performance indices are formulated. Then, a moving horizon estimator (MHE) is designed to provide state estimates for the controller in virtue of its ability in dealing with nonlinearities and constraints. Subsequently, an economic model predictive control (EMPC) design integrated with a zone tracking objective is proposed for the boiler-turbine generating system. Extensive simulations under different scenarios illustrate the effectiveness of the proposed EMPC design compared with the conventional set-point tracking model predictive control.

ACS Style

Yi Zhang; Benjamin Decardi-Nelson; Jianbang Liu; Jiong Shen; Jinfeng Liu. Zone economic model predictive control of a coal-fired boiler-turbine generating system. Chemical Engineering Research and Design 2019, 153, 246 -256.

AMA Style

Yi Zhang, Benjamin Decardi-Nelson, Jianbang Liu, Jiong Shen, Jinfeng Liu. Zone economic model predictive control of a coal-fired boiler-turbine generating system. Chemical Engineering Research and Design. 2019; 153 ():246-256.

Chicago/Turabian Style

Yi Zhang; Benjamin Decardi-Nelson; Jianbang Liu; Jiong Shen; Jinfeng Liu. 2019. "Zone economic model predictive control of a coal-fired boiler-turbine generating system." Chemical Engineering Research and Design 153, no. : 246-256.

Conference paper
Published: 01 November 2019 in 2019 Chinese Automation Congress (CAC)
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The sufficient utilization of the mega data acquired from operative power units is a promising way leading to high efficient, clean and safe operation of power plant. Hereinto, data filtering is a critical link to the data-driven dynamic model identification aiming at optimizing the process control. The machine learning is an advantageous approach for filtering usable data from mega databases for identification due to its effective statistical learning strategy to the field data with noises, disturbances and coupling quantities. Therefore, a data filtering method of combining Gaussian Naive Bayesian classifier and prediction error method (Gaussian NB-PEM) is proposed in this paper. Firstly, variables associated with identification model are selected by analyzing the characteristics of the process. Secondly, the GaussianNB classifier is used for coarse data filtering by calculating the priori probability of each attribute from training sample set and the probability with all possible values of the known categories for testing sample set. Thirdly, the prediction error method is used for further data filtering based on model fitting. By using the filtered closed-loop data, the dynamic characteristics of the superheated steam temperature is modeled and verified by closed-loop control simulation, showing the validity of the Gaussian NB-PEM data filtering method.

ACS Style

Qianchao Wang; Lei Pan; Jiong Shen; Nianci Lu. Power Plant Data Filtering Based on Gaussian Naive Bayesian Classification and Prediction Error Method. 2019 Chinese Automation Congress (CAC) 2019, 1490 -1495.

AMA Style

Qianchao Wang, Lei Pan, Jiong Shen, Nianci Lu. Power Plant Data Filtering Based on Gaussian Naive Bayesian Classification and Prediction Error Method. 2019 Chinese Automation Congress (CAC). 2019; ():1490-1495.

Chicago/Turabian Style

Qianchao Wang; Lei Pan; Jiong Shen; Nianci Lu. 2019. "Power Plant Data Filtering Based on Gaussian Naive Bayesian Classification and Prediction Error Method." 2019 Chinese Automation Congress (CAC) , no. : 1490-1495.

Conference paper
Published: 01 November 2019 in 2019 Chinese Automation Congress (CAC)
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The flue gas desulfurization system is vulnerable to various unknown or unmeasured disturbances. In reality, the type of disturbance is usually unknown or multiple disturbances occur simultaneously in the system. To cope with this issue, this paper proposes the disturbance rejection predictive control strategy based on the new augmented state space model. The new state space model is firstly augmented to reduce the modeling error and be convenient for practical use. To detect the type of disturbance, the disturbance model bank is then established and state estimation is applied to estimate the unknown disturbance model. Furthermore, the method of disturbance model weighting is provided. Finally, the objective function is modified to cope with the continuous effects of the disturbances. Based on the above procedure, a model predictive controller is designed. The validity of the strategy is demonstrated by simulation results.

ACS Style

Hao Jiang; Yiguo Li; Junli Zhang; Jiong Shen. Disturbance Rejection Predictive Control for Flue Gas Desulfurization System. 2019 Chinese Automation Congress (CAC) 2019, 411 -417.

AMA Style

Hao Jiang, Yiguo Li, Junli Zhang, Jiong Shen. Disturbance Rejection Predictive Control for Flue Gas Desulfurization System. 2019 Chinese Automation Congress (CAC). 2019; ():411-417.

Chicago/Turabian Style

Hao Jiang; Yiguo Li; Junli Zhang; Jiong Shen. 2019. "Disturbance Rejection Predictive Control for Flue Gas Desulfurization System." 2019 Chinese Automation Congress (CAC) , no. : 411-417.

Journal article
Published: 25 October 2019 in Applied Energy
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Solvent-based post-combustion CO2 capture (PCC) appears to be the most effective choice to overcome the CO2 emission issue of fossil fuel fired power plants. To make the PCC better suited for power plants, growing interest has been directed to the flexible operation of PCC in the past ten years. The flexible operation requires the PCC system to adapt to the strong flue gas flow rate change and to adjust the carbon capture level rapidly in wide operating range. In-depth study of the dynamic characteristics of the PCC process and developing a suitable control approach are the keys to meet this challenge. This paper provides a critical review for the dynamic research of the solvent–based PCC process including first-principle modelling, data-driven system/process identification and the control design studies, with their main features being listed and discussed. The existent studies have been classified according to the approaches used and their advantages and limitations have been summarized. Potential future research opportunities for the flexible operation of solvent-based PCC are also given in this review.

ACS Style

Xiao Wu; Meihong Wang; Peizhi Liao; Jiong Shen; Yiguo Li. Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation. Applied Energy 2019, 257, 113941 .

AMA Style

Xiao Wu, Meihong Wang, Peizhi Liao, Jiong Shen, Yiguo Li. Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation. Applied Energy. 2019; 257 ():113941.

Chicago/Turabian Style

Xiao Wu; Meihong Wang; Peizhi Liao; Jiong Shen; Yiguo Li. 2019. "Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation." Applied Energy 257, no. : 113941.

Conference paper
Published: 25 October 2019 in IOP Conference Series: Earth and Environmental Science
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Steam turbine thermal system characteristic reconstruction model for multi-parameter joint optimization is proposed in this paper. This paper has two main improvements. First, a steam turbine thermal system characteristic reconstruction model is conducted, which includes turbine, condenser and heater. There are three iterative nested algorithms in this model. In the innermost layer, avariable condition calculation model of condenser is nested, and the exhaust flow and exhaust steam pressure can be calculated. In the outermost layer, the power equation is applied as the iteration ends. In this model, simulation of thermal system of steam turbine three kinds of disturbing factors demand can be realized well and the joint optimization of thermal system of steam turbine flow section and the cold end can be realized. Through calculation and comparison, the model constructed in this paper is proved to have high accuracy, and the calculation process is stable and convergent. At the same time, the joint optimization method involving turbine main steam pressure and exhaust pressure is proposed here. In this method, heat consumption rate is the optimization objective, with steam turbine thermal system characteristic reconstruction model, the optimal main steam condenser and vacuum pressure were obtained. The result of A 600MW condensing unit showed that the method could be synchronized to determine the optimal combination of circulating pump, the best vacuum and sliding pressure curve of main steam under different load and different ambient temperature. Comparison results also showed that the joint optimization solution of main steam pressure and exhaust pressure is superior to optimized solution main steam pressure individually.

ACS Style

S Liu; J Shen; P H Wang. Multi-parameter Joint Optimization Based on Steam Turbine Thermal System Characteristic Reconstruction Model. IOP Conference Series: Earth and Environmental Science 2019, 354, 012068 .

AMA Style

S Liu, J Shen, P H Wang. Multi-parameter Joint Optimization Based on Steam Turbine Thermal System Characteristic Reconstruction Model. IOP Conference Series: Earth and Environmental Science. 2019; 354 (1):012068.

Chicago/Turabian Style

S Liu; J Shen; P H Wang. 2019. "Multi-parameter Joint Optimization Based on Steam Turbine Thermal System Characteristic Reconstruction Model." IOP Conference Series: Earth and Environmental Science 354, no. 1: 012068.

Journal article
Published: 01 October 2019 in Applied Thermal Engineering
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ACS Style

Jianzhong Zhu; Xiao Wu; Jiong Shen. Practical disturbance rejection control for boiler-turbine unit with input constraints. Applied Thermal Engineering 2019, 161, 1 .

AMA Style

Jianzhong Zhu, Xiao Wu, Jiong Shen. Practical disturbance rejection control for boiler-turbine unit with input constraints. Applied Thermal Engineering. 2019; 161 ():1.

Chicago/Turabian Style

Jianzhong Zhu; Xiao Wu; Jiong Shen. 2019. "Practical disturbance rejection control for boiler-turbine unit with input constraints." Applied Thermal Engineering 161, no. : 1.

Journal article
Published: 10 September 2019 in IFAC-PapersOnLine
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Solid oxide fuel cell (SOFC) is of great importance to renewable energy generation system. In practice its output voltage should be held constant and fuel utilization rate should be guaranteed in a reasonable range respectively when the resistance load varies over a large area. In order to overcome the issues in practice, a fuzzy model predictive control with zone tracking for a SOFC power generation system is proposed. The nonlinearity and multivariable coupling are mitigated by fuzzy model and predictive control approaches respectively. The feedforward compensation is adopted to improve with the dynamic response. Zone control is integrated with fuzzy model predictive control for the purposes of satisfying fuel utilization within a desired range. A performance index with a weight function is developed to optimize controlled variables trajectory in the desired range so that the undulations of the controlled variables can be alleviated within the range. The advantages of the proposed method are manifested by simulations.

ACS Style

Long Wu; Xiao Wu; Lei Pan; Jiong Shen; Yiguo Li; Junli Zhang. Fuzzy Model Predictive Control of Solid Oxide Fuel Cell with Zone Tracking. IFAC-PapersOnLine 2019, 52, 210 -215.

AMA Style

Long Wu, Xiao Wu, Lei Pan, Jiong Shen, Yiguo Li, Junli Zhang. Fuzzy Model Predictive Control of Solid Oxide Fuel Cell with Zone Tracking. IFAC-PapersOnLine. 2019; 52 (4):210-215.

Chicago/Turabian Style

Long Wu; Xiao Wu; Lei Pan; Jiong Shen; Yiguo Li; Junli Zhang. 2019. "Fuzzy Model Predictive Control of Solid Oxide Fuel Cell with Zone Tracking." IFAC-PapersOnLine 52, no. 4: 210-215.

Journal article
Published: 10 September 2019 in IFAC-PapersOnLine
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During the scram or load rejection of nuclear power plant, the excess steam of steam generator needs to be dumped to the main condenser through the steam conditioning device to reduce the temperature rising of the primary loop and prevent the steam generator from over-pressure. For study of the dynamics and control strategy of the steam dump system, this paper established a simulation model of nuclear power plant using Gsuite simulation platform, and then studied the dynamical-varying of some important-variables in nuclear power plants during scram. The results indicated that the model built can approximately predict the dynamic changes of important parameters such as the average temperature of the primary loop and the main steam pressure. Therefrom it is concluded that the joint operation of the steam dump system and atmospheric steam dump system can effectively prevent the rising of the temperature of the primary loop and the overpressure of the secondary circuit, and thus it can avoid the opening of the main-steam safety valve.

ACS Style

Nianci Lu; Yanjun Li; Lei Pan; Xiao Wu; Jiong Shen; Zhenxiang Liu; Kwang_Y_ Lee. Study on Dynamics of Steam Dump System in Scram Condition of Nuclear Power Plant. IFAC-PapersOnLine 2019, 52, 360 -365.

AMA Style

Nianci Lu, Yanjun Li, Lei Pan, Xiao Wu, Jiong Shen, Zhenxiang Liu, Kwang_Y_ Lee. Study on Dynamics of Steam Dump System in Scram Condition of Nuclear Power Plant. IFAC-PapersOnLine. 2019; 52 (4):360-365.

Chicago/Turabian Style

Nianci Lu; Yanjun Li; Lei Pan; Xiao Wu; Jiong Shen; Zhenxiang Liu; Kwang_Y_ Lee. 2019. "Study on Dynamics of Steam Dump System in Scram Condition of Nuclear Power Plant." IFAC-PapersOnLine 52, no. 4: 360-365.