This paper summarizes recent progress by the authors in developing two solution frameworks for dual control. The first solution framework considers a class of dual control problems where there exists a parameter uncer...This paper summarizes recent progress by the authors in developing two solution frameworks for dual control. The first solution framework considers a class of dual control problems where there exists a parameter uncertainty in the observation equation of the LQG problem. An analytical active dual control law is derived by a variance minimization approach. The issue of how to determine an optimal degree of active learning is then addressed, thus achieving an optimality for this class of dual control problems. The second solution framework considers a general class of discrete-time LQG problems with unknown parameters in both state and observation equations. The best possible (partial) closed-loop feedback control law is derived by exploring the future nominal posterior probabilities, thus taking into account the effect of future learning when constructing the optimal nominal dual control.展开更多
Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference manage...Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.展开更多
In this paper, we first propose a perturbation procedure for achieving dual feasibility, which starts with any basis without introducing artificial variables. This procedure and the dual simplex method are then incorp...In this paper, we first propose a perturbation procedure for achieving dual feasibility, which starts with any basis without introducing artificial variables. This procedure and the dual simplex method are then incorporated into a general purpose algorithm; then, a modification of it using a perturbation technique is made in order to handle highly degenerate problems efficiently. Some interesting theoretical results are presented. Nmerical results obtained are reported, which are very encouraging though still preliminary.展开更多
Heavy fault currents flow in the event of fault at the loads connected in distribution system. To protect these loads, circuit breakers and relays are required at appropriate places with proper coordination between th...Heavy fault currents flow in the event of fault at the loads connected in distribution system. To protect these loads, circuit breakers and relays are required at appropriate places with proper coordination between them. This research paper focuses on finding optimum relay setting required for minimum time to interrupt power supply to avoid miscoordination in operation of relays and also investigates effect on time multiplier settings (TMS) of directional overcurrent relays in a system with combined overhead lines-underground cables. Linear programming problem (LPP) approach is used for optimization. It is interesting to know the quantitative variations in TMS as the underground cables have different characteristics than overhead lines.展开更多
Calculation of static voltage stability margin(SVSM)of AC/DC power systems with lots of renewable energy sources(RESs)integration requires consideration of uncertain load growth and renewable energy generation output....Calculation of static voltage stability margin(SVSM)of AC/DC power systems with lots of renewable energy sources(RESs)integration requires consideration of uncertain load growth and renewable energy generation output.This paper presents a bi-level optimal power flow(BLOPF)model to identify the worst-case SVSM of an AC/DC power system with line commutation converter-based HVDC and multi-terminal voltage sourced converter-based HVDC transmission lines.Constraints of uncertain load growth’s hypercone model and control mode switching of DC converter stations are considered in the BLOPF model.Moreover,uncertain RES output fluctuations are described as intervals,and two three-level optimal power flow(TLOPF)models are established to identify interval bounds of the system worst-case SVSM.The two TLOPF models are both transformed into max–min bi-level optimization models according to independent characteristics of different uncertain variables.Then,transforming the inner level model into its dual form,max–min BLOPF models are simplified to single-level optimization models for direct solution.Calculation results on the modified IEEE-39 bus AC/DC case and an actual large-scale AC/DC case in China indicate correctness and efficiency of the proposed identification method.展开更多
With the participation of large quantities of renewable energy in power system operations,their volatility and intermittence increases the difficulties and challenges of power system economic scheduling.Considering th...With the participation of large quantities of renewable energy in power system operations,their volatility and intermittence increases the difficulties and challenges of power system economic scheduling.Considering the uncertainty of renewable energy generation,based on the distributionally robust optimization method,a two-stage economic dispatch model is proposed to minimize the total operation costs.In this paper,it is assumed that the fluctuating of renewable power generation follows the unknown probability distribution that is restricted in an ambiguity set,which is established by utilizing the first-order moment information of available historical data.Furthermore,the theory of conditional value-at-risk is introduced to transform the model into a tractable model,which we call robust counterpart formulation.Based on the stochastic dual dynamic programming method,an improved iterative algorithm is proposed to solve the robust counterpart problem.Specifically,the convergence optimum can be obtained by the improved iterative algorithm,which performs a forward pass and backward pass repeatedly in each iterative process.Finally,by comparing with other methods,the results on the modified IEEE 6-bus,118-bus,and 300-bus system show the effectiveness and advantages of the proposed model and method.展开更多
This paper proposes a Lagrangian dual-based polynomial-time approximation algorithm for solving the single-period unit commitment problem,which can be formulated as a mixed-integer quadratic programming problem and pr...This paper proposes a Lagrangian dual-based polynomial-time approximation algorithm for solving the single-period unit commitment problem,which can be formulated as a mixed-integer quadratic programming problem and proven to be NP-hard.Tight theoretical bounds for the absolute errors and relative errors of the approximate solutions generated by the proposed algorithm are provided.Computational results support the effectiveness and efficiency of the proposed algorithm for solving large-scale problems.展开更多
基金the Research Grants Council of Hong Kong, P.R.China under Grant CUHK 4180/03E
文摘This paper summarizes recent progress by the authors in developing two solution frameworks for dual control. The first solution framework considers a class of dual control problems where there exists a parameter uncertainty in the observation equation of the LQG problem. An analytical active dual control law is derived by a variance minimization approach. The issue of how to determine an optimal degree of active learning is then addressed, thus achieving an optimality for this class of dual control problems. The second solution framework considers a general class of discrete-time LQG problems with unknown parameters in both state and observation equations. The best possible (partial) closed-loop feedback control law is derived by exploring the future nominal posterior probabilities, thus taking into account the effect of future learning when constructing the optimal nominal dual control.
基金supported by the National Natural Science Foundation of China (Grant No.61601071)the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No.KJ16004012)+2 种基金the Municipal Natural Science Foundation of Chongqing (Grant No.CSTC2016JCYJA2197)the Seventeenth Open Foundation of State Key Lab of Integrated Services Networks of Xidian University (Grant No.ISN17-01)the Dr. Startup Founds of Chongqing University of Posts and Telecommunications (Grant No.A2016-12)
文摘Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.
文摘In this paper, we first propose a perturbation procedure for achieving dual feasibility, which starts with any basis without introducing artificial variables. This procedure and the dual simplex method are then incorporated into a general purpose algorithm; then, a modification of it using a perturbation technique is made in order to handle highly degenerate problems efficiently. Some interesting theoretical results are presented. Nmerical results obtained are reported, which are very encouraging though still preliminary.
文摘Heavy fault currents flow in the event of fault at the loads connected in distribution system. To protect these loads, circuit breakers and relays are required at appropriate places with proper coordination between them. This research paper focuses on finding optimum relay setting required for minimum time to interrupt power supply to avoid miscoordination in operation of relays and also investigates effect on time multiplier settings (TMS) of directional overcurrent relays in a system with combined overhead lines-underground cables. Linear programming problem (LPP) approach is used for optimization. It is interesting to know the quantitative variations in TMS as the underground cables have different characteristics than overhead lines.
基金supported by the National Natural Science Foundation of China(Grant No.51977080)the Natural Science Foundation of Guangdong Province(Grant No.2022A1515010332)supported by the U.S.National Science Foundation(Grant#2124849).
文摘Calculation of static voltage stability margin(SVSM)of AC/DC power systems with lots of renewable energy sources(RESs)integration requires consideration of uncertain load growth and renewable energy generation output.This paper presents a bi-level optimal power flow(BLOPF)model to identify the worst-case SVSM of an AC/DC power system with line commutation converter-based HVDC and multi-terminal voltage sourced converter-based HVDC transmission lines.Constraints of uncertain load growth’s hypercone model and control mode switching of DC converter stations are considered in the BLOPF model.Moreover,uncertain RES output fluctuations are described as intervals,and two three-level optimal power flow(TLOPF)models are established to identify interval bounds of the system worst-case SVSM.The two TLOPF models are both transformed into max–min bi-level optimization models according to independent characteristics of different uncertain variables.Then,transforming the inner level model into its dual form,max–min BLOPF models are simplified to single-level optimization models for direct solution.Calculation results on the modified IEEE-39 bus AC/DC case and an actual large-scale AC/DC case in China indicate correctness and efficiency of the proposed identification method.
基金supported by the National Natural Science Foundation of China(No.51777126)。
文摘With the participation of large quantities of renewable energy in power system operations,their volatility and intermittence increases the difficulties and challenges of power system economic scheduling.Considering the uncertainty of renewable energy generation,based on the distributionally robust optimization method,a two-stage economic dispatch model is proposed to minimize the total operation costs.In this paper,it is assumed that the fluctuating of renewable power generation follows the unknown probability distribution that is restricted in an ambiguity set,which is established by utilizing the first-order moment information of available historical data.Furthermore,the theory of conditional value-at-risk is introduced to transform the model into a tractable model,which we call robust counterpart formulation.Based on the stochastic dual dynamic programming method,an improved iterative algorithm is proposed to solve the robust counterpart problem.Specifically,the convergence optimum can be obtained by the improved iterative algorithm,which performs a forward pass and backward pass repeatedly in each iterative process.Finally,by comparing with other methods,the results on the modified IEEE 6-bus,118-bus,and 300-bus system show the effectiveness and advantages of the proposed model and method.
基金This work was supported by the National Natural Science Foundation of China(Nos.11771243,12171151,and 11701177)US Army Research Office(No.W911NF-15-1-0223).
文摘This paper proposes a Lagrangian dual-based polynomial-time approximation algorithm for solving the single-period unit commitment problem,which can be formulated as a mixed-integer quadratic programming problem and proven to be NP-hard.Tight theoretical bounds for the absolute errors and relative errors of the approximate solutions generated by the proposed algorithm are provided.Computational results support the effectiveness and efficiency of the proposed algorithm for solving large-scale problems.