This paper investigates a multi-period mean-variance portfolio selection with regime switching and uncertain exit time. The returns of assets all depend on the states of the stochastic market which are assumed to foll...This paper investigates a multi-period mean-variance portfolio selection with regime switching and uncertain exit time. The returns of assets all depend on the states of the stochastic market which are assumed to follow a discrete-time Markov chain. The authors derive the optimal strategy and the efficient frontier of the model in closed-form. Some results in the existing literature are obtained as special cases of our results.展开更多
In the computational process of very fast transient over-voltage （VFTO）, it is essen-tial to find an accurate model for a gas insulated substation. The arcing model of the disconnector is particularly important. The...In the computational process of very fast transient over-voltage （VFTO）, it is essen-tial to find an accurate model for a gas insulated substation. The arcing model of the disconnector is particularly important. The general arcing model is not able to give a good description of the arc development process. In this paper, based on the physical process of arcing and existing arc models （the exponential time-varying resistance model and the segmental arcing models）, a dy- namic arcing model is proposed, which is divided into two stages before and after the zero crossing. The dynamic arcing model combines hyperbola time-varying resistance and the Mayr model to describe the dynamic process of arcing. The present paper creates an arc model blockset upon the Matlab/Simulink software platform. Moreover for a specific 1100 kV station, VFTO is simulated in detail based on different arcing models. It is demonstrated that the dynamic arcing model can describe the physical arc process precisely and is useful for improving the accuracy of VFTO simulations.展开更多
The increasing integration of photovoltaic generators(PVGs) and the uneven economic development in different regions may cause the unbalanced spatial-temporal distribution of load demands in an urban distribution netw...The increasing integration of photovoltaic generators(PVGs) and the uneven economic development in different regions may cause the unbalanced spatial-temporal distribution of load demands in an urban distribution network(UDN). This may lead to undesired consequences, including PVG curtailment, load shedding, and equipment inefficiency, etc. Global dynamic reconfiguration provides a promising method to solve those challenges. However, the power flow transfer capabilities for different kinds of switches are diverse, and the willingness of distribution system operators(DSOs) to select them is also different. In this paper, we formulate a multi-objective dynamic reconfiguration optimization model suitable for multi-level switching modes to minimize the operation cost, load imbalance, and the PVG curtailment. The multi-level switching includes feeder-level switching, transformer-level switching, and substation-level switching. A novel load balancing index is devised to quantify the global load balancing degree at different levels. Then, a stochastic programming model based on selected scenarios is established to address the uncertainties of PVGs and loads. Afterward, the fuzzy c-means(FCMs) clustering is applied to divide the time periods of reconfiguration. Furthermore, the modified binary particle swarm optimization(BPSO)and Cplex solver are combined to solve the proposed mixed-integer second-order cone programming(MISOCP) model. Numerical results based on the 148-node and 297-node systems are obtained to validate the effectiveness of the proposed method.展开更多
This paper is concerned with the scaled formation control problem for multi-agent systems(MASs)over fixed and switching topologies.First,a modified resilient dynamic event-triggered(DET)mechanism involving an auxiliar...This paper is concerned with the scaled formation control problem for multi-agent systems(MASs)over fixed and switching topologies.First,a modified resilient dynamic event-triggered(DET)mechanism involving an auxiliary dynamic variable(ADV)based on sampled data is proposed.In the proposed DET mechanism,a random variable obeying the Bernoulli distribution is introduced to express the idle and busy situations of communication networks.Meanwhile,the operation of absolute value is introduced into the triggering condition to effectively reduce the formation error.Second,a scaled formation control protocol with the proposed resilient DET mechanism is designed over fixed and switching topologies.The scaled formation error system is modeled as a time-varying delay system.Then,several sufficient stability criteria are derived by constructing appropriate Lyapunov-Krasovskii functionals(LKFs).A co-design algorithm based on the sparrow search algorithm(SSA)is presented to design the control gains and triggering parameters jointly.Finally,numerical simulations of multiple unmanned aerial vehicles(UAVs)are presented to validate the designed control method.展开更多
基金This research is supported by the National Science Foundation for Distinguished Young Scholars under Grant No. 70825002, the National Natural Science Foundation of China under Grant No. 70518001, and the National Basic Research Program of China 973 Program, under Grant No. 2007CB814902.
文摘This paper investigates a multi-period mean-variance portfolio selection with regime switching and uncertain exit time. The returns of assets all depend on the states of the stochastic market which are assumed to follow a discrete-time Markov chain. The authors derive the optimal strategy and the efficient frontier of the model in closed-form. Some results in the existing literature are obtained as special cases of our results.
基金supported by Special Research Fund for Doctoral Program of Education Ministry of China (No. 20092102110001)Natural Science Foundation of Liaoning Province of China (No. 201102169)National Natural Science Foundation of China (No. 51277123)
文摘In the computational process of very fast transient over-voltage （VFTO）, it is essen-tial to find an accurate model for a gas insulated substation. The arcing model of the disconnector is particularly important. The general arcing model is not able to give a good description of the arc development process. In this paper, based on the physical process of arcing and existing arc models （the exponential time-varying resistance model and the segmental arcing models）, a dy- namic arcing model is proposed, which is divided into two stages before and after the zero crossing. The dynamic arcing model combines hyperbola time-varying resistance and the Mayr model to describe the dynamic process of arcing. The present paper creates an arc model blockset upon the Matlab/Simulink software platform. Moreover for a specific 1100 kV station, VFTO is simulated in detail based on different arcing models. It is demonstrated that the dynamic arcing model can describe the physical arc process precisely and is useful for improving the accuracy of VFTO simulations.
基金supported by the National Key R&D Program of China (No.2019YFE0123600)National Natural Science Foundation of China (No.52077146)Young Elite Scientists Sponsorship Program by CSEE (No.CESS-YESS-2019027)。
文摘The increasing integration of photovoltaic generators(PVGs) and the uneven economic development in different regions may cause the unbalanced spatial-temporal distribution of load demands in an urban distribution network(UDN). This may lead to undesired consequences, including PVG curtailment, load shedding, and equipment inefficiency, etc. Global dynamic reconfiguration provides a promising method to solve those challenges. However, the power flow transfer capabilities for different kinds of switches are diverse, and the willingness of distribution system operators(DSOs) to select them is also different. In this paper, we formulate a multi-objective dynamic reconfiguration optimization model suitable for multi-level switching modes to minimize the operation cost, load imbalance, and the PVG curtailment. The multi-level switching includes feeder-level switching, transformer-level switching, and substation-level switching. A novel load balancing index is devised to quantify the global load balancing degree at different levels. Then, a stochastic programming model based on selected scenarios is established to address the uncertainties of PVGs and loads. Afterward, the fuzzy c-means(FCMs) clustering is applied to divide the time periods of reconfiguration. Furthermore, the modified binary particle swarm optimization(BPSO)and Cplex solver are combined to solve the proposed mixed-integer second-order cone programming(MISOCP) model. Numerical results based on the 148-node and 297-node systems are obtained to validate the effectiveness of the proposed method.
基金Project supported by the National Natural Science Foundation of China(Nos.62103097 and 61803081)the Shanghai Rising-Star Program(No.21QA1400100)the Natural Science Foundation of Shanghai,China(No.20ZR1400800)。
文摘This paper is concerned with the scaled formation control problem for multi-agent systems(MASs)over fixed and switching topologies.First,a modified resilient dynamic event-triggered(DET)mechanism involving an auxiliary dynamic variable(ADV)based on sampled data is proposed.In the proposed DET mechanism,a random variable obeying the Bernoulli distribution is introduced to express the idle and busy situations of communication networks.Meanwhile,the operation of absolute value is introduced into the triggering condition to effectively reduce the formation error.Second,a scaled formation control protocol with the proposed resilient DET mechanism is designed over fixed and switching topologies.The scaled formation error system is modeled as a time-varying delay system.Then,several sufficient stability criteria are derived by constructing appropriate Lyapunov-Krasovskii functionals(LKFs).A co-design algorithm based on the sparrow search algorithm(SSA)is presented to design the control gains and triggering parameters jointly.Finally,numerical simulations of multiple unmanned aerial vehicles(UAVs)are presented to validate the designed control method.
