This paper introduces an ant colony routing and wavelength assignment algorithm based on cross-layer design(CL-ACRWA),which can overcome the adverse effects of Doppler wavelength shift on data transmission in optical ...This paper introduces an ant colony routing and wavelength assignment algorithm based on cross-layer design(CL-ACRWA),which can overcome the adverse effects of Doppler wavelength shift on data transmission in optical satellite networks. Firstly, a cross-layer optimization model is built, which considers the Doppler wavelength shift, the transmission delay as well as wavelength-continuity constraint. Then an ant colony algorithm is utilized to solve the cross-layer optimization model, resulting in finding an optimal light path satisfying the above constraints for every connection request. The performance of CL-ACRWA is measured by the communication success probability, the convergence property and the transmission delay. Simulation results show that CL-ACRWA performs well in communication success probability and has good global search ability as well as fast convergence speed. Meanwhile, the transmission delay can meet the basic requirement of real-time transmission of business.展开更多
为应对弃风现象及风电出力的不确定性问题,考虑热网传输延迟特性对应的储能特性,提出一种电热综合能源系统(integrated electricity and district heating system,IEDHS)的鲁棒区间优化调度模型。首先,对热网的物理结构及传输延迟、温...为应对弃风现象及风电出力的不确定性问题,考虑热网传输延迟特性对应的储能特性,提出一种电热综合能源系统(integrated electricity and district heating system,IEDHS)的鲁棒区间优化调度模型。首先,对热网的物理结构及传输延迟、温度损耗特性进行建模,并参与IEDHS优化调度;其次,以区间形式考虑风电的不确定性,使系统在所有风电出力允许区间内,均满足运行约束条件;再次,建立了一种考虑热网传输延迟的IEDHS鲁棒区间优化调度模型,采用对偶理论将原模型进一步转化为单层模型,并调用CPLEX求解器进行求解;最后,通过对PJM-5节点测试系统与6节点热力系统、IEEE-39节点测试系统与12节点热力系统组成的IEDHS进行算例分析,验证了所提模型的有效性。算例结果表明,热网的传输延迟可提高风电利用率,降低系统运行成本,鲁棒区间优化调度结果较常规调度更具可靠性。展开更多
The topological structure of a complex dynamical network plays a vital role in determining the network＇s evolutionary mecha- nisms and functional behaviors, thus recognizing and inferring the network structure is of ...The topological structure of a complex dynamical network plays a vital role in determining the network＇s evolutionary mecha- nisms and functional behaviors, thus recognizing and inferring the network structure is of both theoretical and practical signif- icance. Although various approaches have been proposed to estimate network topologies, many are not well established to the noisy nature of network dynamics and ubiquity of transmission delay among network individuals. This paper focuses on to- pology inference of uncertain complex dynamical networks. An auxiliary network is constructed and an adaptive scheme is proposed to track topological parameters. It is noteworthy that the considered network model is supposed to contain practical stochastic perturbations, and noisy observations are taken as control inputs of the constructed auxiliary network. In particular, the control technique can be further employed to locate hidden sources （or latent variables） in networks. Numerical examples are provided to illustrate the effectiveness of the proposed scheme. In addition, the impact of coupling strength and coupling delay on identification performance is assessed. The proposed scheme provides engineers with a convenient approach to infer topologies of general complex dynamical networks and locate hidden sources, and the detailed performance evaluation can further facilitate practical circuit design.展开更多
基金supported by the National Natural Science Foundation of China(No.61675033,61575026,61675233)National High Technical Research and Development Program of China(No.2015AA015504)
文摘This paper introduces an ant colony routing and wavelength assignment algorithm based on cross-layer design(CL-ACRWA),which can overcome the adverse effects of Doppler wavelength shift on data transmission in optical satellite networks. Firstly, a cross-layer optimization model is built, which considers the Doppler wavelength shift, the transmission delay as well as wavelength-continuity constraint. Then an ant colony algorithm is utilized to solve the cross-layer optimization model, resulting in finding an optimal light path satisfying the above constraints for every connection request. The performance of CL-ACRWA is measured by the communication success probability, the convergence property and the transmission delay. Simulation results show that CL-ACRWA performs well in communication success probability and has good global search ability as well as fast convergence speed. Meanwhile, the transmission delay can meet the basic requirement of real-time transmission of business.
文摘为应对弃风现象及风电出力的不确定性问题,考虑热网传输延迟特性对应的储能特性,提出一种电热综合能源系统(integrated electricity and district heating system,IEDHS)的鲁棒区间优化调度模型。首先,对热网的物理结构及传输延迟、温度损耗特性进行建模,并参与IEDHS优化调度;其次,以区间形式考虑风电的不确定性,使系统在所有风电出力允许区间内,均满足运行约束条件;再次,建立了一种考虑热网传输延迟的IEDHS鲁棒区间优化调度模型,采用对偶理论将原模型进一步转化为单层模型,并调用CPLEX求解器进行求解;最后,通过对PJM-5节点测试系统与6节点热力系统、IEEE-39节点测试系统与12节点热力系统组成的IEDHS进行算例分析,验证了所提模型的有效性。算例结果表明,热网的传输延迟可提高风电利用率,降低系统运行成本,鲁棒区间优化调度结果较常规调度更具可靠性。
基金supported by the National Science and Technology Major Project of China(Grant No.2014ZX10004001-014)the National Natural Science Foundation of China(Grant Nos.61573262,61532020&11472290)the Fundamental Research Funds for the Central Universities(Grant No.2014201020206)
文摘The topological structure of a complex dynamical network plays a vital role in determining the network＇s evolutionary mecha- nisms and functional behaviors, thus recognizing and inferring the network structure is of both theoretical and practical signif- icance. Although various approaches have been proposed to estimate network topologies, many are not well established to the noisy nature of network dynamics and ubiquity of transmission delay among network individuals. This paper focuses on to- pology inference of uncertain complex dynamical networks. An auxiliary network is constructed and an adaptive scheme is proposed to track topological parameters. It is noteworthy that the considered network model is supposed to contain practical stochastic perturbations, and noisy observations are taken as control inputs of the constructed auxiliary network. In particular, the control technique can be further employed to locate hidden sources （or latent variables） in networks. Numerical examples are provided to illustrate the effectiveness of the proposed scheme. In addition, the impact of coupling strength and coupling delay on identification performance is assessed. The proposed scheme provides engineers with a convenient approach to infer topologies of general complex dynamical networks and locate hidden sources, and the detailed performance evaluation can further facilitate practical circuit design.
