A Hybrid Unit Commitment Approach Incorporating Modified Priority List with Charged System Search Methods

This paper presents a new hybrid approach that combines Modified Priority List (MPL) with Charged System Search (CSS), termed MPL-CSS, to solve one of the most crucial power system’s operational optimization problems, known as unit commitment (UC) scheduling. The UC scheduling problem is a mixed-integer nonlinear problem, highly-dimensional and extremely constrained. Existing meta-heuristic UC solution methods have the problems of stopping at a local optimum and slow convergence when applied to large-scale, heavily-constrained UC applications. In the first step of the proposed method, initial hourly optimum solutions of UC are obtained by Modified Priority List (MPL);however, the obtained UC solution may still be possible to be further improved. Therefore, in the second step, the CSS is utilized to achieve higher quality solutions. The UC is formulated as mixed integer linear programming to ensure the tractability of the results. The proposed method is successfully applied to a popular test system up to 100 units generators for both 24-hr and 168-hr system. Computational results show that both solution cost and execution time are superior to those of published methods.

Comparison of electronic structure between monolayer silicenes on Ag(111)

√√The electronic structures of monolayer silicenes(4 × 4 and■ ×■R13.9o) grown on Ag(111) surface are studied by scanning tunneling spectroscopy(STS) and density functional theory(DFT) calculations. While both phases have similar electronic structures around the Fermi level, significant differences are observed in the higher energy unoccupied states.The DFT calculations show that the contributions of Si 3pz orbitals to the unoccupied states are different because of their different buckled configurations.

Active Queue Management within Large-Scale Wired Networks

Signal transmission control protocol sources with the objective of managing queue utilization and delay is actually a feedback control problem in active queue management (AQM) core routers. This paper extends AQM control design for single network systems to large-scale wired network systems with time delays at each communication channel. A system model consisted of several local networks is first constructed. The stability condition guaranteeing overall stability is subsequently derived using Lyapunov stability theory. The results developed have been successfully verified on a network simulator.

MAC Throughput Improvement Using Adaptive Contention Window

HomePlug AV (HPAV) is a standard developed by HomePlug Powerline Alliance (HPA) for power line communication. In HomePlug AV, it uses a technology named Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) to reduce collision happened in network. However, when network nodes increase, the contention window number may not be wide enough. It will cause collision probability to increase. In this paper, we introduce a new idea of adaptive contention window which will produce suitable contention window under actual network environment. Our method only requires the information of CSMA/CA parameters. It means that one doesn’t need to correct the original CSMA/CA procedure but substitutes old parameters by the new ones. Simulation experiments conducted in the network simulator NS3 show that compared with HomePlug AV, our method promotes throughput significantly when the node number increases.

Robust estimation of stochastic gene-network systems

Gene networks in biological systems are highly complicated because of their nonlinear and stochastic features. Network dynamics typically involve crosstalk mechanism and they may suffer from corruption due to intrinsic and extrinsic stochastic molecular noises. Filtering noises in gene networks using biological techniques accompanied with a systematic strategy is thus an attractive topic. However, most states of biological systems are not directly accessible. In practice, these immeasurable states can only be predicted based on the measurement output. In the lab experiment, green fluorescent protein (GFP) is commonly adopted as the reporter protein since it is able to reflect intensity of the gene expression. On this basis, this study considers a nonlinear stochastic model to describe the stochastic gene networks and shows that robust state estimation using Kalman filtering techniques is possible. Stability of the robust estimation scheme is analyzed based on the Ito’s theorem and Lyapunov stability theory. Numerical examples in silico are illustrated to confirm performance of the proposed design.