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The high penetration of renewable energy sources makes the two-by-one combined cycle gas-turbine (2 × 1 CCGT) with high operational flexibility (OPFL) become the mainstream of deep peak-load units. However, the thermos-exchanger water level (TEWL) often exceeds the limit and causes unit trip during flexible operations. For this reason, this paper proposes a flexible operational TEWL control strategy. First, by modeling and analyzing the thermodynamics of the thermal-supply system of 2 × 1 CCGT unit, the exhaust steam pressure of intermediate pressure cylinder (IPEP) is chosen as an upstream controlled variable with mathematical-model derived setpoint to stabilize the TEWL; Secondly, considering the heat storage utilization of heating network, the heating-network circulating water flow is selected as the manipulated variable of IPEP control, then forming a pilot IPEP control loop cooperating with the existing TEWL control loop to stabilize the TEWL. Several control algorithms are designed and compared to determine the most effective one for the IPEP pilot-TEWL control. The results show that the maximal deviation of TEWL can be reduced to 7 mm and the OPFL indexes can be significantly improved, i.e. the average power ramp rate is 6.74 MW/min, and the power capacity is 69.55 MW from 158 MW steam turbine.
Nianci Lu; Lei Pan; Zhenxiang Liu; Yajun Song; Paiyou Si. Flexible operation control strategy for thermos-exchanger water level of two-by-one combined cycle gas turbine based on heat network storage utilization. Energy 2021, 232, 121077 .
AMA StyleNianci Lu, Lei Pan, Zhenxiang Liu, Yajun Song, Paiyou Si. Flexible operation control strategy for thermos-exchanger water level of two-by-one combined cycle gas turbine based on heat network storage utilization. Energy. 2021; 232 ():121077.
Chicago/Turabian StyleNianci Lu; Lei Pan; Zhenxiang Liu; Yajun Song; Paiyou Si. 2021. "Flexible operation control strategy for thermos-exchanger water level of two-by-one combined cycle gas turbine based on heat network storage utilization." Energy 232, no. : 121077.
The two-by-one (2 × 1) combined-cycle gas turbine (CCGT) unit with condensation-extraction-backpressure (C-E-B) steam turbine has become the major means of peak regulation in China because of its flexible operating mode. However, mode switching of the unit often causes drastic fluctuation of the water level of heating network thermos-exchanger and jeopardizes unit safety. In order to study the suppression mechanism of the water level fluctuation in the transient mode of switching, first a dynamic mathematical model of the thermal-supply system of the C-E-B steam turbine is developed based on a mixed approach of theory and identification. Then field data is used to verify model accuracy. Through step response analysis on the heat-supply system, the relationship between the extraction flow to the thermos-exchanger and its water level is identified along with the major influential factors. On the heat-demand system, the circulating water flow through heating network influences the heat transfer of thermos-exchanger, the exhaust steam pressure of turbine, the extraction flow and the water level in sequel. Combining the factors from the two systems arrives at the conclusion that the circulating water flow stabilizes the water level during mode switching process and provides theoretical basis for water-level controller design.
Nianci Lu; Lei Pan; Zhenxiang Liu; Kwang Y. Lee; Yajun Song; Paiyou Si. Dynamic modeling of thermal-supply system for two-by-one combined-cycle gas and steam turbine unit. Fuel Processing Technology 2020, 209, 106549 .
AMA StyleNianci Lu, Lei Pan, Zhenxiang Liu, Kwang Y. Lee, Yajun Song, Paiyou Si. Dynamic modeling of thermal-supply system for two-by-one combined-cycle gas and steam turbine unit. Fuel Processing Technology. 2020; 209 ():106549.
Chicago/Turabian StyleNianci Lu; Lei Pan; Zhenxiang Liu; Kwang Y. Lee; Yajun Song; Paiyou Si. 2020. "Dynamic modeling of thermal-supply system for two-by-one combined-cycle gas and steam turbine unit." Fuel Processing Technology 209, no. : 106549.
Boiler forced draft systems play a critical role in maintaining power plant safety and efficiency. However, their control is notoriously intractable in terms of modelling difficulty, multiple disturbances and severe noise. To this end, this paper develops a data-driven paradigm by combining some popular data analytics methods in both modelling and control. First, singular value decomposition (SVD) is utilized for data classification, which further cooperates with back propagation (BP) neural network to de-noise the measurements. Second, prediction error method (PEM) is used to analyze the historical data and identify the dynamic model, whose responses agree well with the actual plant data. Third, by estimating the lumped disturbances via the real-time data, active disturbance rejection control (ADRC) is employed to control the forced draft system, whose stability is analyzed in the frequency domain. Simulation results demonstrate the efficiency and superiority of the proposed method over proportional-integral-differential (PID) controller and model predictive controller, depicting a promising prospect in the future industry practice.
Qianchao Wang; Hongcan Xu; Lei Pan; Li Sun. Active Disturbance Rejection Control of Boiler Forced Draft System: A Data-Driven Practice. Sustainability 2020, 12, 4171 .
AMA StyleQianchao Wang, Hongcan Xu, Lei Pan, Li Sun. Active Disturbance Rejection Control of Boiler Forced Draft System: A Data-Driven Practice. Sustainability. 2020; 12 (10):4171.
Chicago/Turabian StyleQianchao Wang; Hongcan Xu; Lei Pan; Li Sun. 2020. "Active Disturbance Rejection Control of Boiler Forced Draft System: A Data-Driven Practice." Sustainability 12, no. 10: 4171.
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.
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 StyleLei 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 StyleLei 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.
Superheated steam temperature is one of the most important process variables for controlling the steam quality of thermal power units. In order to improve the accuracy of superheated steam temperature and the stability of valves for desuperheating water, this paper proposed a novel control strategy called united long short-term memory (LSTM) and model predictive control (MPC), which is weighted by particle swarm optimization. First, a deeply learnt inverse model is made to express the potential nonlinear dynamic characteristics of data and to predict the future valve opening in short-term. Secondly, model predictive control is used to control the secondary superheated steam temperature. Thirdly, the two predicted valve opening are weighted by particle swarm optimization. The combined deep learning inverse model control and MPC can make up the deficiencies of each other, i.e., over fitting of deep learning inverse model and linearity of MPC. The simulation experiments proved the advantage of LSTM-MPC in comparison with traditional PID and single MPC control.
Qianchao Wang; Lei Pan; Kwang Y Lee. Improving Superheated Steam Temperature Control Using United Long Short Term Memory and MPC. IFAC-PapersOnLine 2020, 53, 13345 -13350.
AMA StyleQianchao Wang, Lei Pan, Kwang Y Lee. Improving Superheated Steam Temperature Control Using United Long Short Term Memory and MPC. IFAC-PapersOnLine. 2020; 53 (2):13345-13350.
Chicago/Turabian StyleQianchao Wang; Lei Pan; Kwang Y Lee. 2020. "Improving Superheated Steam Temperature Control Using United Long Short Term Memory and MPC." IFAC-PapersOnLine 53, no. 2: 13345-13350.
For solving the problems of closed-loop optimization on controller parameters of multiple-controller single-output thermal engineering system, this paper proposes a recurrent optimization method that is based on the particle swarm computing and closed-loop simulation (PSO-RCO). It consists of a set of closed-loop identification, simulation, and optimization functions that are organized in a recurrent working flow. The working flow makes one controller tuned at a time whilst others keep their values. It ends after several rounds of overall optimizations. Such a recurrently alternative tuning can greatly speed up the convergence of controller parameters to reasonable values. Verifications on practical data from a superheated steam temperature control system show that the optimized control system performance is greatly improved by reasonable controller parameters and practicable control action. With the advantage of not interfering system operation and the potential supporting on big data identification method, the PSO-RCO is a promising method for control system optimization.
Xingjian Liu; Lei Pan. A PSO-Based Recurrent Closed-Loop Optimization Method for Multiple Controller Single-Output Thermal Engineering Systems. Processes 2019, 7, 784 .
AMA StyleXingjian Liu, Lei Pan. A PSO-Based Recurrent Closed-Loop Optimization Method for Multiple Controller Single-Output Thermal Engineering Systems. Processes. 2019; 7 (11):784.
Chicago/Turabian StyleXingjian Liu; Lei Pan. 2019. "A PSO-Based Recurrent Closed-Loop Optimization Method for Multiple Controller Single-Output Thermal Engineering Systems." Processes 7, no. 11: 784.
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.
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 StyleLong 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 StyleLong 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.
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.
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 StyleNianci 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 StyleNianci 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.
The super-critical thermal power plants are undertaking more and more responsibilities for the balance of the power grid intermittency of the renewable energies. However, the frequent wide-range load regulation may deteriorate the operational efficiency of the power plant. To this end, a hierarchical control structure with two layers is proposed in this paper. An economic model predictive controller using a locally linearized model of the plant (LEMPC) is employed in the upper layer to realize an optimal load tracking. A L1 adaptive controller in the lower layer forces the plant to track the optimal trajectory by estimating and compensating the lumped uncertainty between the real plant and the linear model. The tracking performance is theoretically proved to reach the desired transient process. The proposed hierarchical control architecture is validated through simulations on a simplified 1000MW super-critical boiler-turbine unit model with comparison to the other two conventional real-time optimization control approaches. The results show that the proposed L1-LEMPC control system produces better load tracking performance than the other two conventional control strategies with higher operational economy efficiency. Moreover, under the environment of severe external disturbance and parameter perturbation, the proposed control system still maintains satisfactory performance.
Siwei Han; Jiong Shen; Lei Pan; Li Sun; Chengyu Cao. A L1-LEMPC hierarchical control structure for economic load-tracking of super-critical power plants. ISA Transactions 2019, 96, 415 -428.
AMA StyleSiwei Han, Jiong Shen, Lei Pan, Li Sun, Chengyu Cao. A L1-LEMPC hierarchical control structure for economic load-tracking of super-critical power plants. ISA Transactions. 2019; 96 ():415-428.
Chicago/Turabian StyleSiwei Han; Jiong Shen; Lei Pan; Li Sun; Chengyu Cao. 2019. "A L1-LEMPC hierarchical control structure for economic load-tracking of super-critical power plants." ISA Transactions 96, no. : 415-428.
Water pump control, prevalent in various industrial plants, such as wastewater treatment and steam generator facilities, plays a significant role in maintaining economic efficiency and stable plant operation. Due to its slow dynamics, strong nonlinearity, and various disturbances, it is also widely studied as a typical benchmark problem in process control. The current control strategies can be categorized into two aspects: one branch resorts to model-based design and the other to data-driven design. To merge the merits and overcome the deficiencies of each paradigm, this paper proposes a hybrid data-driven and model-assisted control strategy, namely modified active disturbance rejection control (MADRC). The model information regarding water dynamics is incorporated into an extended state observer (ESO), which is used to estimate and mitigate the limitations of slow dynamics, strong nonlinearity, and various disturbances by analyzing the real-time data. The tuning formula is given in terms of the desired closed-loop performance. It is shown that MADRC is able to produce a satisfactory control performance while maintaining a low sensitivity to the measurement noise under general parametric setting conditions. The simulation results verify the clear superiority of MADRC over the proportional-integral (PI) controller and the conventional ADRC, and the results also evidence its noise reduction effects. The experimental results agree well with the simulation results based on a water tank setup. The proposed MADRC approach is able to improve the control performance while reducing the actuator fluctuation. The results presented in this paper offer a promising methodology for the water control loops widely used in the water industry.
Guanru Li; Lei Pan; Qingsong Hua; Li Sun; Kwang Y. Lee. Water Pump Control: A Hybrid Data-Driven and Model-Assisted Active Disturbance Rejection Approach. Water 2019, 11, 1066 .
AMA StyleGuanru Li, Lei Pan, Qingsong Hua, Li Sun, Kwang Y. Lee. Water Pump Control: A Hybrid Data-Driven and Model-Assisted Active Disturbance Rejection Approach. Water. 2019; 11 (5):1066.
Chicago/Turabian StyleGuanru Li; Lei Pan; Qingsong Hua; Li Sun; Kwang Y. Lee. 2019. "Water Pump Control: A Hybrid Data-Driven and Model-Assisted Active Disturbance Rejection Approach." Water 11, no. 5: 1066.
Proton Exchange Membrane Fuel Cell (PEMFC) is promising in distributed generation owing to its load reliability in complementing intermittent renewable energy sources. However, the existing PEMFC operational researches, usually developed based on the constant current (CC) mode, is not compatible with the grid-connected applications, which instead requires the PEMFC to operate under the constant net power (CP) mode. Some novel difficulties are revealed in association with the couplings caused by the CP operation. An iterative algorithm is developed to decouple the computational interactions so that the steady-state variables can be derived. The efficiency analysis gives the static references of the oxygen excess ratio (OER), which is, however, revealed as contradicting with the voltage requirement of the inverter. Thus, it results in the optimal OER reference modified. In dynamic operation, a peculiar initial inverse response of the OER is exhibited under the CP mode, which requires more cautious controller design than that under the CC mode. Moreover, a power profile governor is designed to prevent the stack voltage from decreasing below the lower bound during transient. Finally, the simulation demonstrates the feasibility and capability of the proposed method in compensating for the renewable intermittency, laying a foundation for the future work on the grid-connected PEMFC.
Li Sun; Yuhui Jin; Lei Pan; Jiong Shen; Kwang Y. Lee. Efficiency analysis and control of a grid-connected PEM fuel cell in distributed generation. Energy Conversion and Management 2019, 195, 587 -596.
AMA StyleLi Sun, Yuhui Jin, Lei Pan, Jiong Shen, Kwang Y. Lee. Efficiency analysis and control of a grid-connected PEM fuel cell in distributed generation. Energy Conversion and Management. 2019; 195 ():587-596.
Chicago/Turabian StyleLi Sun; Yuhui Jin; Lei Pan; Jiong Shen; Kwang Y. Lee. 2019. "Efficiency analysis and control of a grid-connected PEM fuel cell in distributed generation." Energy Conversion and Management 195, no. : 587-596.
The distributed energy system is an energy supply method built around the end users, which can achieve energy sustainability and reduce emissions compared to traditional centralized energy systems. The micro gas turbine (MGT)-based combined cooling and power (CCP) system has received renewed attention as an important distributed energy system technology due to its substantial energy savings and reduced emission levels. The task of the MGT-CCP system is to quickly adapt to changes in various renewable energy sources to maintain the balance in energy supply and demand in a distributed energy system. Therefore, it is imperative to improve the load tracking capability of the MGT-CCP system with advanced control technologies toward achieving this goal. However, the difficulty of controlling the MGT-CCP system is that the MGT responds very fast while CCP responds very slowly. To this end, the dynamic characteristics and nonlinear distribution of the MGT and CCP processes are analyzed, and a coordinated predictive control strategy is proposed by utilizing the generalized predictive control for the MGT system and the Hammerstein generalized predictive control for the CCP system. The coordinated predictive control of generalized predictive control and Hammerstein generalized predictive control was implemented in an 80 kW MGT-CCP simulator to verify the effectiveness of the proposed method. The simulation results show that compared with PID and MPC, the proposed control method not only can greatly improve simultaneous cooling and power load-following capability, but also has the best control effect when accessing with renewable energy.
Chen Chen; Jiangfan Lin; Lei Pan; Kwang Y. Lee; Li Sun. Improving Simultaneous Cooling and Power Load-Following Capability for MGT-CCP Using Coordinated Predictive Controls. Energies 2019, 12, 1180 .
AMA StyleChen Chen, Jiangfan Lin, Lei Pan, Kwang Y. Lee, Li Sun. Improving Simultaneous Cooling and Power Load-Following Capability for MGT-CCP Using Coordinated Predictive Controls. Energies. 2019; 12 (6):1180.
Chicago/Turabian StyleChen Chen; Jiangfan Lin; Lei Pan; Kwang Y. Lee; Li Sun. 2019. "Improving Simultaneous Cooling and Power Load-Following Capability for MGT-CCP Using Coordinated Predictive Controls." Energies 12, no. 6: 1180.
The control of an ultra-supercritical (USC) boiler–turbine power plant is critical in maintaining the safety of the sustainable power grid. However, it is challenging due to the internal nonlinearity, hard manipulation constraints, and widespread uncertainties. To this end, a fuzzy extended state observer (FESO)-based stable fuzzy predictive control (SFPC) approach is developed in this paper. First, the control difficulties of the USC boiler–turbine unit are analyzed. Then, based on a Takagi–Sugeno (T–S) fuzzy model, a new FESO is developed for nonlinear systems to achieve a more precise observation performance. The gain of FESO is determined by solving a series of linear matrix inequalities, while guaranteeing the stability of FESO. Then, by combining the proposed FESO with the SFPC, an integrated FESO–SFPC algorithm is devised. The disturbance rejection ability of the FESO–SFPC algorithm is analyzed theoretically. Simulation results on a 1000 MW USC boiler–turbine power plant model further validate the effectiveness of the proposed method.
Chen Chen; Lei Pan; Shanjian Liu; Li Sun; Kwang Y. Lee. A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control. Sustainability 2018, 10, 4824 .
AMA StyleChen Chen, Lei Pan, Shanjian Liu, Li Sun, Kwang Y. Lee. A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control. Sustainability. 2018; 10 (12):4824.
Chicago/Turabian StyleChen Chen; Lei Pan; Shanjian Liu; Li Sun; Kwang Y. Lee. 2018. "A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control." Sustainability 10, no. 12: 4824.
It is extremely challenging to control ultra-supercritical boiler–turbine unit on account of its nonlinearity, coupling among multi-variables, hard input constraints, and unknown disturbances. An offset-free output-feedback stable model predictive control (MPC) (OFOF-SMPC) for nonlinear constrained ultra-supercritical boiler-turbine units is investigated. It is shown that the OFOF-SMPC is composed of a disturbance and state observer, a steady-state target calculator as well as a stable MPC, which can remove unknown disturbances from output channels and ensure the stability of the closed-loop system with input constraints. Simulation results demonstrate the effectiveness of the proposed algorithm.
Chen Chen; Lei Pan; Jiong Shen; Kwang Y. Lee; Fan Zhang; Li Sun; Xiao Wu; Junli Zhang; Wenchao Xue. Control of Nonlinear Constrained Ultra-Supercritical Boiler–Turbine Units Using Offset-Free Output-Feedback Stable MPC. IFAC-PapersOnLine 2018, 51, 155 -160.
AMA StyleChen Chen, Lei Pan, Jiong Shen, Kwang Y. Lee, Fan Zhang, Li Sun, Xiao Wu, Junli Zhang, Wenchao Xue. Control of Nonlinear Constrained Ultra-Supercritical Boiler–Turbine Units Using Offset-Free Output-Feedback Stable MPC. IFAC-PapersOnLine. 2018; 51 (28):155-160.
Chicago/Turabian StyleChen Chen; Lei Pan; Jiong Shen; Kwang Y. Lee; Fan Zhang; Li Sun; Xiao Wu; Junli Zhang; Wenchao Xue. 2018. "Control of Nonlinear Constrained Ultra-Supercritical Boiler–Turbine Units Using Offset-Free Output-Feedback Stable MPC." IFAC-PapersOnLine 51, no. 28: 155-160.
As the problem of three-phase unbalance in distribution network with distributed generations (DG) is prominent, a multi-objective dynamic reconfiguration method for three-phase balance is proposed to make reconfiguration more reasonable and effective. Based on three-phase power flow calculation and reconfiguration process analysis of distribution networks with DGs, a new reconfiguration model with comprehensive optimization objectives of minimizing three-phase unbalance factor and number of switching times is established. A network connectivity discrimination method based on the algebraic connectivity of graph theory is adopted to quickly remove infeasible solutions, and a new multi-objective molecular differential evolution (MOMDE) algorithm is designed to improve optimization depth and avoid prematurity in the optimization process, which is based on the principle of closer molecules with greater inter-molecular repulsion. The multi-objective optimal dynamic reconfiguration of a modified IEEE 34-bus test feeder with DGs is carried out and the simulation results demonstrate the effectiveness and superiority of the proposed method.
Chunhua Peng; Lu Xu; Xun Gong; Huijuan Sun; Lei Pan. Molecular Evolution Based Dynamic Reconfiguration of Distribution Networks With DGs Considering Three-Phase Balance and Switching Times. IEEE Transactions on Industrial Informatics 2018, 15, 1866 -1876.
AMA StyleChunhua Peng, Lu Xu, Xun Gong, Huijuan Sun, Lei Pan. Molecular Evolution Based Dynamic Reconfiguration of Distribution Networks With DGs Considering Three-Phase Balance and Switching Times. IEEE Transactions on Industrial Informatics. 2018; 15 (4):1866-1876.
Chicago/Turabian StyleChunhua Peng; Lu Xu; Xun Gong; Huijuan Sun; Lei Pan. 2018. "Molecular Evolution Based Dynamic Reconfiguration of Distribution Networks With DGs Considering Three-Phase Balance and Switching Times." IEEE Transactions on Industrial Informatics 15, no. 4: 1866-1876.
Siwei Han; Jiang Shen; Lei Pan; Li Sun. Voltage and Fuel Utilization Control for Solid Oxide Fuel Cells with Combined L1 Adaptive – Predictive Control Strategy. 2018 Annual American Control Conference (ACC) 2018, 1 .
AMA StyleSiwei Han, Jiang Shen, Lei Pan, Li Sun. Voltage and Fuel Utilization Control for Solid Oxide Fuel Cells with Combined L1 Adaptive – Predictive Control Strategy. 2018 Annual American Control Conference (ACC). 2018; ():1.
Chicago/Turabian StyleSiwei Han; Jiang Shen; Lei Pan; Li Sun. 2018. "Voltage and Fuel Utilization Control for Solid Oxide Fuel Cells with Combined L1 Adaptive – Predictive Control Strategy." 2018 Annual American Control Conference (ACC) , no. : 1.
An optimal load-tracking operation strategy for a grid-connected tubular solid oxide fuel cell (SOFC) is studied based on the steady-state analysis of the system thermodynamics and electrochemistry. Control of the SOFC is achieved by a two-level hierarchical control system. In the upper level, optimal setpoints of output voltage and the current corresponding to unit load demand is obtained through a nonlinear optimization by minimizing the SOFC’s internal power waste. In the lower level, a combined L1-MPC control strategy is designed to achieve fast set point tracking under system nonlinearities, while maintaining a constant fuel utilization factor. To prevent fuel starvation during the transient state resulting from the output power surging, a fuel flow constraint is imposed on the MPC with direct electron balance calculation. The proposed control schemes are testified on the grid-connected SOFC model.
Siwei Han; Li Sun; Jiong Shen; Lei Pan; Kwang Y. Lee. Optimal Load-Tracking Operation of Grid-Connected Solid Oxide Fuel Cells through Set Point Scheduling and Combined L1-MPC Control. Energies 2018, 11, 801 .
AMA StyleSiwei Han, Li Sun, Jiong Shen, Lei Pan, Kwang Y. Lee. Optimal Load-Tracking Operation of Grid-Connected Solid Oxide Fuel Cells through Set Point Scheduling and Combined L1-MPC Control. Energies. 2018; 11 (4):801.
Chicago/Turabian StyleSiwei Han; Li Sun; Jiong Shen; Lei Pan; Kwang Y. Lee. 2018. "Optimal Load-Tracking Operation of Grid-Connected Solid Oxide Fuel Cells through Set Point Scheduling and Combined L1-MPC Control." Energies 11, no. 4: 801.
It is difficult to control the output voltage of the Solid Oxide Fuel Cells (SOFCs) because of the system nonlinearity, load disturbance and various constraints on the actuators and the fuel utilization rate. To overcome these difficulties, this paper proposed a multiple model predictive control scheme. The nonlinearity is addressed by using multiple models that are linearized at different operating conditions. The disturbance is accommodated by directly sending the load current information to the optimizer. And the constraints are naturally handled by formulating a constrained optimization problem. The simulation results show the effectiveness of the proposed strategy.
Lei Pan; Yali Xue; Li Sun; Nghai Li; Zhenlong Wu. Multiple Model Predictive Control for Solid Oxide Fuel Cells. Volume 1: 37th Computers and Information in Engineering Conference 2017, 1 .
AMA StyleLei Pan, Yali Xue, Li Sun, Nghai Li, Zhenlong Wu. Multiple Model Predictive Control for Solid Oxide Fuel Cells. Volume 1: 37th Computers and Information in Engineering Conference. 2017; ():1.
Chicago/Turabian StyleLei Pan; Yali Xue; Li Sun; Nghai Li; Zhenlong Wu. 2017. "Multiple Model Predictive Control for Solid Oxide Fuel Cells." Volume 1: 37th Computers and Information in Engineering Conference , no. : 1.
Zhenlong Wu; Yali Xue; Lei Pan; Nghai Li; Ting He; Li Sun; Yuxin Yang. Active disturbance rejection control based simplified decoupling for two-input-two-output processes. 2017 36th Chinese Control Conference (CCC) 2017, 399 -404.
AMA StyleZhenlong Wu, Yali Xue, Lei Pan, Nghai Li, Ting He, Li Sun, Yuxin Yang. Active disturbance rejection control based simplified decoupling for two-input-two-output processes. 2017 36th Chinese Control Conference (CCC). 2017; ():399-404.
Chicago/Turabian StyleZhenlong Wu; Yali Xue; Lei Pan; Nghai Li; Ting He; Li Sun; Yuxin Yang. 2017. "Active disturbance rejection control based simplified decoupling for two-input-two-output processes." 2017 36th Chinese Control Conference (CCC) , no. : 399-404.
Uncertain operating conditions, along with the load demand for a wider and faster response, bring new challenges to the nonlinear boiler–turbine unit control. In order to achieve safe and efficient operations, this paper proposes a novel L1 adaptive state feedback controller for the multivariable nonlinear boiler–turbine systems with unknown uncertainties. This L1 adaptive control approach can achieve arbitrarily close tracking of the reference signal while ensuring closed-loop stability in the presence of strong nonlinearities, internal un-modeled dynamics, time-varying unknown parameters and uncertain dead time within its time-delay margins. In this study, a boiler–turbine unit simulation model is first built in order to verify the algorithm; then the L1 adaptive control approach is presented followed by its main results and proof; only based on one group of the equilibrium working point data, the L1 adaptive controller is designed for the overall working range of the boiler–turbine unit. For a more reliable evaluation on the L1 adaptive controller, the offset-free input-to-state stable fuzzy model predictive controller (OFISS-MPC) – which has all-sided performances – is briefly introduced and functions as a reference for our results. Finally, the L1 adaptive controller is tested in a series of challenging simulation scenarios and then compared with the OFISS-MPC controller. The results validate the expected performances of the L1 adaptive controller for the boiler–turbine unit with unknown uncertainties.
Lei Pan; Jie Luo; Chengyu Cao; Jiong Shen. L1 adaptive control for improving load-following capability of nonlinear boiler–turbine units in the presence of unknown uncertainties. Simulation Modelling Practice and Theory 2015, 57, 26 -44.
AMA StyleLei Pan, Jie Luo, Chengyu Cao, Jiong Shen. L1 adaptive control for improving load-following capability of nonlinear boiler–turbine units in the presence of unknown uncertainties. Simulation Modelling Practice and Theory. 2015; 57 ():26-44.
Chicago/Turabian StyleLei Pan; Jie Luo; Chengyu Cao; Jiong Shen. 2015. "L1 adaptive control for improving load-following capability of nonlinear boiler–turbine units in the presence of unknown uncertainties." Simulation Modelling Practice and Theory 57, no. : 26-44.