电力体制改革的不断推进和分布式能源渗透率的不断提高给电力市场与配网运行带来新的机遇与挑战。在此背景下,提出了面向虚拟电厂(virtual power plant,VPP)能量管理的点对点(peer-to-peer,P2P)市场交易机制与模型。首先,在日前阶段针对...电力体制改革的不断推进和分布式能源渗透率的不断提高给电力市场与配网运行带来新的机遇与挑战。在此背景下,提出了面向虚拟电厂(virtual power plant,VPP)能量管理的点对点(peer-to-peer,P2P)市场交易机制与模型。首先,在日前阶段针对VPP内部的产消者拥有的分布式资源进行量化建模并根据交易流向进行解耦;然后,基于次梯度法搭建了日前的产消者P2P交易框架,以集群产消者个体收益最大为目标,并通过交互有限的信息,把原问题分解为多个子问题进行迭代求解,实现虚拟电厂内产消者之间的P2P电能交易。所提机制与模型可以有效缓解VPP承担的计算压力,保护用户信息隐私。针对在实时阶段中VPP可能出现的电能偏差,基于VCG(vickrey-clarke-groves)规则提出多边竞价交易机制消除偏差,既能保证实时运行的安全时限,又能实现系统的帕累托改进,降低了交易方信息暴露风险。最后结合算例验证了所提机制与模型的有效性和优越性。展开更多
Backlash-like hysteresis is one of the nonsmooth and multi-valued nonlinearities usually existing in mechanical systems. The traditional identification method is quite difficult to be used to model the systems involve...Backlash-like hysteresis is one of the nonsmooth and multi-valued nonlinearities usually existing in mechanical systems. The traditional identification method is quite difficult to be used to model the systems involved with such complex nonlinearities. In this paper, a nonsmooth recursive identification algorithm for the systems with backlash-like hysteresis is proposed. In this method, the concept of Clarke subgradient is introduced to approximate the gradients at nonsmooth points and the so-called bundle method is used to obtain the optimization search direction in nonsmooth cases. Then, a recursive algorithm based on the idea of bundle method is developed for parameter estimation. After that, the convergence analysis of the algorithm is investigated. Finally, simulation results to validate the proposed method on a simulated mechanical transmission system are presented.展开更多
In this paper,we investigate pseudomonotone and Lipschitz continuous variational inequalities in real Hilbert spaces.For solving this problem,we propose a new method that combines the advantages of the subgradient ext...In this paper,we investigate pseudomonotone and Lipschitz continuous variational inequalities in real Hilbert spaces.For solving this problem,we propose a new method that combines the advantages of the subgradient extragradient method and the projection contraction method.Some very recent papers have considered different inertial algorithms which allowed the inertial factor is chosen in[0;1].The purpose of this work is to continue working in this direction,we propose another inertial subgradient extragradient method that the inertial factor can be chosen in a special case to be 1.Under suitable mild conditions,we establish the weak convergence of the proposed algorithm.Moreover,linear convergence is obtained under strong pseudomonotonicity and Lipschitz continuity assumptions.Finally,some numerical illustrations are given to confirm the theoretical analysis.展开更多
Multi-dimensional nonlinear knapsack problem is a bounded nonlinear integer programming problem that maximizes a separable nondecreasing function subject to multiple separable nondecreasing constraints. This problem i...Multi-dimensional nonlinear knapsack problem is a bounded nonlinear integer programming problem that maximizes a separable nondecreasing function subject to multiple separable nondecreasing constraints. This problem is often encountered in resource allocation, industrial planning and computer network. In this paper, a new convergent Lagrangian dual method was proposed for solving this problem. Cutting plane method was used to solve the dual problem and to compute the Lagrangian bounds of the primal problem. In order to eliminate the duality gap and thus to guarantee the convergence of the algorithm, domain cut technique was employed to remove certain integer boxes and partition the revised domain to a union of integer boxes. Extensive computational results show that the proposed method is efficient for solving large-scale multi-dimensional nonlinear knapsack problems. Our numerical results also indicate that the cutting plane method significantly outperforms the subgradient method as a dual search procedure.展开更多
A kind of nondecreasing subgradient algorithm with appropriate stopping rule has been proposed for nonsmooth constrained minimization problem. The dual theory is invoked in dealing with the stopping rule and general g...A kind of nondecreasing subgradient algorithm with appropriate stopping rule has been proposed for nonsmooth constrained minimization problem. The dual theory is invoked in dealing with the stopping rule and general global minimiizing algorithm is employed as a subroutine of the algorithm. The method is expected to tackle a large class of nonsmooth constrained minimization problem.展开更多
The minimization problem of time delays in networked control system （NCS） is concered, which is a hot area of such research field. First, some analysis and comments on time-delayed NCS model listed in previous work ...The minimization problem of time delays in networked control system （NCS） is concered, which is a hot area of such research field. First, some analysis and comments on time-delayed NCS model listed in previous work are given. Then, time delay minimization problem based on average behavior of network queuing delay is presented. Under fixed routing scheme and certain optimization performance indexes, the delay minimization problem is translated into convex optimization problem. And the solution of the delay minimization problems is attained through optimized allocation of flow rates among network links.展开更多
A new method in digital hearing aids to adaptively localize the speech source in noise and reverberant environment is proposed. Based on the room reverberant model and the multichannel adaptive eigenvalue decompositi...A new method in digital hearing aids to adaptively localize the speech source in noise and reverberant environment is proposed. Based on the room reverberant model and the multichannel adaptive eigenvalue decomposition （MCAED） algorithm, the proposed method can iteratively estimate impulse response coefficients between the speech source and microphones by the adaptive subgradient projection method. Then, it acquires the time delays of microphone pairs, and calculates the source position by the geometric method. Compared with the traditional normal least mean square （NLMS） algorithm, the adaptive subgradient projection method achieves faster and more accurate convergence in a low signal-to-noise ratio （SNR） environment. Simulations for glasses digital hearing aids with four-component square array demonstrate the robust performance of the proposed method.展开更多
Many approaches inquiring into variational inequality problems have been put forward,among which subgradient extragradient method is of great significance.A novel algorithm is presented in this article for resolving q...Many approaches inquiring into variational inequality problems have been put forward,among which subgradient extragradient method is of great significance.A novel algorithm is presented in this article for resolving quasi-nonexpansive fixed point problem and pseudomonotone variational inequality problem in a real Hilbert interspace.In order to decrease the execution time and quicken the velocity of convergence,the proposed algorithm adopts an inertial technology.Moreover,the algorithm is by virtue of a non-monotonic step size rule to acquire strong convergence theorem without estimating the value of Lipschitz constant.Finally,numerical results on some problems authenticate that the algorithm has preferable efficiency than other algorithms.展开更多
Many approaches have been put forward to resolve the variational inequality problem. The subgradient extragradient method is one of the most effective. This paper proposes a modified subgradient extragradient method a...Many approaches have been put forward to resolve the variational inequality problem. The subgradient extragradient method is one of the most effective. This paper proposes a modified subgradient extragradient method about classical variational inequality in a real Hilbert interspace. By analyzing the operator’s partial message, the proposed method designs a non-monotonic step length strategy which requires no line search and is independent of the value of Lipschitz constant, and is extended to solve the problem of pseudomonotone variational inequality. Meanwhile, the method requires merely one map value and a projective transformation to the practicable set at every iteration. In addition, without knowing the Lipschitz constant for interrelated mapping, weak convergence is given and R-linear convergence rate is established concerning algorithm. Several numerical results further illustrate that the method is superior to other algorithms.展开更多
文摘可交易能源系统基于市场运行机制可以充分发挥产消者的资源灵活性,并保障电力系统的安全,经济运行。针对含光伏(photovoltaic,PV)出力、储能装置(energy storage system,ESS)、电动汽车(electric vehicle,EV)以及空调(heating ventilating and air conditioning,HVAC)资源的多个产消者组成的智能园区为研究对象,首先对产消者资源灵活性进行整合与量化并根据交易流向进行解耦。其次,为确保园区交互平台中参与用户的信息安全,实现园区内电能共享、就地消纳,提出了基于次梯度法的成本最小化算法及其分布式凸优化运行框架。优化子问题可以通过有限的信息交互迭代收敛于全局最优解,实现产消者之间的P2P(peer-to-peer)电能交易,最后通过算例验证了所提模型的有效性。
文摘电力体制改革的不断推进和分布式能源渗透率的不断提高给电力市场与配网运行带来新的机遇与挑战。在此背景下,提出了面向虚拟电厂(virtual power plant,VPP)能量管理的点对点(peer-to-peer,P2P)市场交易机制与模型。首先,在日前阶段针对VPP内部的产消者拥有的分布式资源进行量化建模并根据交易流向进行解耦;然后,基于次梯度法搭建了日前的产消者P2P交易框架,以集群产消者个体收益最大为目标,并通过交互有限的信息,把原问题分解为多个子问题进行迭代求解,实现虚拟电厂内产消者之间的P2P电能交易。所提机制与模型可以有效缓解VPP承担的计算压力,保护用户信息隐私。针对在实时阶段中VPP可能出现的电能偏差,基于VCG(vickrey-clarke-groves)规则提出多边竞价交易机制消除偏差,既能保证实时运行的安全时限,又能实现系统的帕累托改进,降低了交易方信息暴露风险。最后结合算例验证了所提机制与模型的有效性和优越性。
基金supported by the National Natural Science Foundation of China (Nos. 61203108, 60971004, 61171088)the projects of the Science and Technology Commission of Shanghai (Nos. 09220503000, 10JC1412200, 09ZR1423400)the projects of Shanghai Education Commission(Nos. 11YZ92, 13YZ056)
文摘Backlash-like hysteresis is one of the nonsmooth and multi-valued nonlinearities usually existing in mechanical systems. The traditional identification method is quite difficult to be used to model the systems involved with such complex nonlinearities. In this paper, a nonsmooth recursive identification algorithm for the systems with backlash-like hysteresis is proposed. In this method, the concept of Clarke subgradient is introduced to approximate the gradients at nonsmooth points and the so-called bundle method is used to obtain the optimization search direction in nonsmooth cases. Then, a recursive algorithm based on the idea of bundle method is developed for parameter estimation. After that, the convergence analysis of the algorithm is investigated. Finally, simulation results to validate the proposed method on a simulated mechanical transmission system are presented.
基金funded by the University of Science,Vietnam National University,Hanoi under project number TN.21.01。
文摘In this paper,we investigate pseudomonotone and Lipschitz continuous variational inequalities in real Hilbert spaces.For solving this problem,we propose a new method that combines the advantages of the subgradient extragradient method and the projection contraction method.Some very recent papers have considered different inertial algorithms which allowed the inertial factor is chosen in[0;1].The purpose of this work is to continue working in this direction,we propose another inertial subgradient extragradient method that the inertial factor can be chosen in a special case to be 1.Under suitable mild conditions,we establish the weak convergence of the proposed algorithm.Moreover,linear convergence is obtained under strong pseudomonotonicity and Lipschitz continuity assumptions.Finally,some numerical illustrations are given to confirm the theoretical analysis.
文摘Multi-dimensional nonlinear knapsack problem is a bounded nonlinear integer programming problem that maximizes a separable nondecreasing function subject to multiple separable nondecreasing constraints. This problem is often encountered in resource allocation, industrial planning and computer network. In this paper, a new convergent Lagrangian dual method was proposed for solving this problem. Cutting plane method was used to solve the dual problem and to compute the Lagrangian bounds of the primal problem. In order to eliminate the duality gap and thus to guarantee the convergence of the algorithm, domain cut technique was employed to remove certain integer boxes and partition the revised domain to a union of integer boxes. Extensive computational results show that the proposed method is efficient for solving large-scale multi-dimensional nonlinear knapsack problems. Our numerical results also indicate that the cutting plane method significantly outperforms the subgradient method as a dual search procedure.
文摘A kind of nondecreasing subgradient algorithm with appropriate stopping rule has been proposed for nonsmooth constrained minimization problem. The dual theory is invoked in dealing with the stopping rule and general global minimiizing algorithm is employed as a subroutine of the algorithm. The method is expected to tackle a large class of nonsmooth constrained minimization problem.
基金This project was supported by the National Natural Science Foundation of China (60274014) Specialized Research Fund forthe Doctoral Programof Higher Education (20020487006) China Education Ministry’s Key Laboratory Foundation for Intelli-gent Manufacture Technology (I mstsu-2002 -03) .
文摘The minimization problem of time delays in networked control system （NCS） is concered, which is a hot area of such research field. First, some analysis and comments on time-delayed NCS model listed in previous work are given. Then, time delay minimization problem based on average behavior of network queuing delay is presented. Under fixed routing scheme and certain optimization performance indexes, the delay minimization problem is translated into convex optimization problem. And the solution of the delay minimization problems is attained through optimized allocation of flow rates among network links.
基金Supported by the National Natural Science Foundation of China (60872073)~~
文摘A new method in digital hearing aids to adaptively localize the speech source in noise and reverberant environment is proposed. Based on the room reverberant model and the multichannel adaptive eigenvalue decomposition （MCAED） algorithm, the proposed method can iteratively estimate impulse response coefficients between the speech source and microphones by the adaptive subgradient projection method. Then, it acquires the time delays of microphone pairs, and calculates the source position by the geometric method. Compared with the traditional normal least mean square （NLMS） algorithm, the adaptive subgradient projection method achieves faster and more accurate convergence in a low signal-to-noise ratio （SNR） environment. Simulations for glasses digital hearing aids with four-component square array demonstrate the robust performance of the proposed method.
文摘Many approaches inquiring into variational inequality problems have been put forward,among which subgradient extragradient method is of great significance.A novel algorithm is presented in this article for resolving quasi-nonexpansive fixed point problem and pseudomonotone variational inequality problem in a real Hilbert interspace.In order to decrease the execution time and quicken the velocity of convergence,the proposed algorithm adopts an inertial technology.Moreover,the algorithm is by virtue of a non-monotonic step size rule to acquire strong convergence theorem without estimating the value of Lipschitz constant.Finally,numerical results on some problems authenticate that the algorithm has preferable efficiency than other algorithms.
文摘Many approaches have been put forward to resolve the variational inequality problem. The subgradient extragradient method is one of the most effective. This paper proposes a modified subgradient extragradient method about classical variational inequality in a real Hilbert interspace. By analyzing the operator’s partial message, the proposed method designs a non-monotonic step length strategy which requires no line search and is independent of the value of Lipschitz constant, and is extended to solve the problem of pseudomonotone variational inequality. Meanwhile, the method requires merely one map value and a projective transformation to the practicable set at every iteration. In addition, without knowing the Lipschitz constant for interrelated mapping, weak convergence is given and R-linear convergence rate is established concerning algorithm. Several numerical results further illustrate that the method is superior to other algorithms.
