126 research outputs found

    Towards Dilated Placement of Dynamic NoC Cores

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    Instead of mapping application task graphs in a compact manner onto reconfigurable devices using a network-on-chip for interconnecting application cores, we propose dilating the mappings as much as the available latencies on critical connections allow. In a dilated mapping, the unused resources between an application\u27s configured components can be used to provide additional flexibility when the configuration needs to change. We motivate the reasons for dilating application task graphs targeted at reconfigurable devices; derive a simulated annealing approach to dilating the placement of such graphs; and present preliminary results of applying the algorithm to synthetic test cases. The method appears to result in successful and meaningful graph dilation and could be further tuned to satisfy desired power constraints

    Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems

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    © 2017 IEEE. This brief proposes a new convex model predictive control (MPC) strategy for dynamic optimal power flow between battery energy storage (ES) systems distributed in an ac microgrid. The proposed control strategy uses a new problem formulation, based on a linear d-q reference frame voltage-current model and linearized power flow approximations. This allows the optimal power flows to be solved as a convex optimization problem, for which fast and robust solvers exist. The proposed method does not assume that real and reactive power flows are decoupled, allowing line losses, voltage constraints, and converter current constraints to be addressed. In addition, nonlinear variations in the charge and discharge efficiencies of lithium ion batteries are analyzed and included in the control strategy. Real-time digital simulations were carried out for an islanded microgrid based on the IEEE 13 bus prototypical feeder, with distributed battery ES systems and intermittent photovoltaic generation. It is shown that the proposed control strategy approaches the performance of a strategy based on nonconvex optimization, while reducing the required computation time by a factor of 1000, making it suitable for a real-time MPC implementation
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