The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previ...The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.展开更多
This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for...This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.展开更多
A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which m...A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which made it possible to obtain good dynamic and control performances just through mechanism optimization.Based on the idea of design for control(DFC),a novel kind of multi-objective optimization model was proposed.There were three optimization objectives:the index of inertia,the index describing the dynamic coupling effects and the global condition number.Other indexes to characterize the designing requirements such as the velocity of end-effector,the workspace size,and the first mode natural frequency were regarded as the constraints.The cross-section area and length of the linkages were chosen as the design variables.NSGA-II algorithm was introduced to solve this complex multi-objective optimization problem.Additional criteria from engineering experience were incorporated into the selecting of final parameters among the obtained Pareto solution sets.Finally,experiments were performed to validate the linear dynamic structure and control performances of the optimized mechanisms.A new expression for measuring the dynamic coupling degree with clear physical meaning was proposed.The results show that the optimized mechanism has an approximate decoupled dynamics structure,and each active joint can be regarded as a linear SISO system.The control performances of the linear and nonlinear controllers were also compared.It can be concluded that the optimized mechanism can achieve good control performance only using a linear controller.展开更多
[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infra...[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.展开更多
A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization （IMOCO） and its extension improved multi-objective robust c...A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization （IMOCO） and its extension improved multi-objective robust collaborative （IMORCO）. In this work, the proposed IMORCO approach combined the IMOCO method, the worst possible point （WPP） constraint cuts and the Genetic algorithm NSGA-II type as an optimizer in order to solve the robust optimization problem of multi-physics of microstructures with uncertainties. The optimization problem is hierarchically decomposed into two levels： a microstructure level, and a disciplines levels, For validation purposes, two examples were selected： a numerical example, and an engineering example of capacitive micro machined ultrasonic transducers （CMUT） type. The obtained results are compared with those obtained from robust non-distributed and distributed optimization approach, non-distributed multi-objective robust optimization （NDMORO） and multi-objective collaborative robust optimization （McRO）, respectively. Results obtained from the application of the IMOCO approach to an optimization problem of a CMUT cell have reduced the CPU time by 44% ensuring a Pareto front close to the reference non-distributed multi-objective optimization （NDMO） approach （mahalanobis distance, D2M =0.9503 and overall spread, So=0.2309）. In addition, the consideration of robustness in IMORCO approach applied to a CMUT cell of optimization problem under interval uncertainty has reduced the CPU time by 23% keeping a robust Pareto front overlaps with that obtained by the robust NDMORO approach （D2M =10.3869 and So=0.0537）.展开更多
A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A s...A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including LPP.For damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was proposed.The performance of the suggested controller was tested using a 16-machine 5-area network.The results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating conditions.The method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing LPP.Simulation results demonstrate that the model presented can be used in designing of essential controllers for LPP.展开更多
The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for...The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.展开更多
为抑制因无功缺额过多引发的多馈入直流后续多次换相失败,提出利用低压限流控制(voltage dependent current order limiter,VDCOL)减少逆变器无功消耗,协同静止无功发生器(static var generator,SVG)补偿无功的抑制思路。首先,计及系统...为抑制因无功缺额过多引发的多馈入直流后续多次换相失败,提出利用低压限流控制(voltage dependent current order limiter,VDCOL)减少逆变器无功消耗,协同静止无功发生器(static var generator,SVG)补偿无功的抑制思路。首先,计及系统电压-无功特性,建立直流电流、SVG无功输出与换相电压的耦合数学模型,推导得到SVG与VDCOL共同作用抑制换相失败存在参数可行域;进而,考虑换相失败恢复过程,提出二者协同时多馈入后续换相失败的临界电压指标,指导优化过程;然后,综合所提指标及系统有功传输、无功补偿力度设置奖励函数,并利用深度确定性策略梯度算法自适应求解最优参数组合。最后,仿真验证了所提策略能够有效抑制多直流输电系统的后续换相失败。展开更多
随着新型电力系统的发展,利用智能终端处理愈发复杂的配电网保护控制任务时,对资源供给与需求的平衡要求越来越高。因此,文中提出一种考虑资源弹性配置的配电网保护控制终端(protect and control intelligent terminal,PCIT)协同任务优...随着新型电力系统的发展,利用智能终端处理愈发复杂的配电网保护控制任务时,对资源供给与需求的平衡要求越来越高。因此,文中提出一种考虑资源弹性配置的配电网保护控制终端(protect and control intelligent terminal,PCIT)协同任务优化分配方法。首先,阐述多终端协同的技术架构,并建立基于容器的PCIT的弹性资源模型、任务处理模型。其次,提出双层模型用于优化保护控制任务在终端间的协同分配、资源的弹性调度,并利用隐枚举法对该模型进行求解,从而充分发挥任务处理时资源的灵活性,提升任务处理性能。最后,算例验证了文中所提方法的可行性与先进性,各智能终端计算资源的占用率降低约28.85%,任务平均处理延时减少约4.12%。展开更多
基金Project(62073342)supported by the National Natural Science Foundation of ChinaProject(2014 AA 041803)supported by the Hi-tech Research and Development Program of China。
文摘The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.
文摘This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.
基金Project(2009AA04Z216) supported in part by the National High Technology Research and Development Program of ChinaProject(2009ZX04013-011) supported by the National Science and Technology Major Program of ChinaProject(20092302120068) supported by the Doctoral Program of Higher Education of China
文摘A design and optimization approach of dynamic and control performance for a two-DOF planar manipulator was proposed.After the kinematic and dynamic analysis,several advantages of the mechanism were illustrated,which made it possible to obtain good dynamic and control performances just through mechanism optimization.Based on the idea of design for control(DFC),a novel kind of multi-objective optimization model was proposed.There were three optimization objectives:the index of inertia,the index describing the dynamic coupling effects and the global condition number.Other indexes to characterize the designing requirements such as the velocity of end-effector,the workspace size,and the first mode natural frequency were regarded as the constraints.The cross-section area and length of the linkages were chosen as the design variables.NSGA-II algorithm was introduced to solve this complex multi-objective optimization problem.Additional criteria from engineering experience were incorporated into the selecting of final parameters among the obtained Pareto solution sets.Finally,experiments were performed to validate the linear dynamic structure and control performances of the optimized mechanisms.A new expression for measuring the dynamic coupling degree with clear physical meaning was proposed.The results show that the optimized mechanism has an approximate decoupled dynamics structure,and each active joint can be regarded as a linear SISO system.The control performances of the linear and nonlinear controllers were also compared.It can be concluded that the optimized mechanism can achieve good control performance only using a linear controller.
文摘[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.
文摘A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization （IMOCO） and its extension improved multi-objective robust collaborative （IMORCO）. In this work, the proposed IMORCO approach combined the IMOCO method, the worst possible point （WPP） constraint cuts and the Genetic algorithm NSGA-II type as an optimizer in order to solve the robust optimization problem of multi-physics of microstructures with uncertainties. The optimization problem is hierarchically decomposed into two levels： a microstructure level, and a disciplines levels, For validation purposes, two examples were selected： a numerical example, and an engineering example of capacitive micro machined ultrasonic transducers （CMUT） type. The obtained results are compared with those obtained from robust non-distributed and distributed optimization approach, non-distributed multi-objective robust optimization （NDMORO） and multi-objective collaborative robust optimization （McRO）, respectively. Results obtained from the application of the IMOCO approach to an optimization problem of a CMUT cell have reduced the CPU time by 44% ensuring a Pareto front close to the reference non-distributed multi-objective optimization （NDMO） approach （mahalanobis distance, D2M =0.9503 and overall spread, So=0.2309）. In addition, the consideration of robustness in IMORCO approach applied to a CMUT cell of optimization problem under interval uncertainty has reduced the CPU time by 23% keeping a robust Pareto front overlaps with that obtained by the robust NDMORO approach （D2M =10.3869 and So=0.0537）.
文摘A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including LPP.For damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was proposed.The performance of the suggested controller was tested using a 16-machine 5-area network.The results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating conditions.The method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing LPP.Simulation results demonstrate that the model presented can be used in designing of essential controllers for LPP.
文摘The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.
文摘为抑制因无功缺额过多引发的多馈入直流后续多次换相失败,提出利用低压限流控制(voltage dependent current order limiter,VDCOL)减少逆变器无功消耗,协同静止无功发生器(static var generator,SVG)补偿无功的抑制思路。首先,计及系统电压-无功特性,建立直流电流、SVG无功输出与换相电压的耦合数学模型,推导得到SVG与VDCOL共同作用抑制换相失败存在参数可行域;进而,考虑换相失败恢复过程,提出二者协同时多馈入后续换相失败的临界电压指标,指导优化过程;然后,综合所提指标及系统有功传输、无功补偿力度设置奖励函数,并利用深度确定性策略梯度算法自适应求解最优参数组合。最后,仿真验证了所提策略能够有效抑制多直流输电系统的后续换相失败。
文摘随着新型电力系统的发展,利用智能终端处理愈发复杂的配电网保护控制任务时,对资源供给与需求的平衡要求越来越高。因此,文中提出一种考虑资源弹性配置的配电网保护控制终端(protect and control intelligent terminal,PCIT)协同任务优化分配方法。首先,阐述多终端协同的技术架构,并建立基于容器的PCIT的弹性资源模型、任务处理模型。其次,提出双层模型用于优化保护控制任务在终端间的协同分配、资源的弹性调度,并利用隐枚举法对该模型进行求解,从而充分发挥任务处理时资源的灵活性,提升任务处理性能。最后,算例验证了文中所提方法的可行性与先进性,各智能终端计算资源的占用率降低约28.85%,任务平均处理延时减少约4.12%。
