Case series, Level IV.

The new energy promoting community has recently witnessed a surge of developments in photovoltaic power generation technologies. To fulfill the grid code requirement of photovoltaic inverter under low-voltage ride-through (LVRT) condition, by utilizing the asymmetry feature of grid voltage, this paper aims to control both restraining negative sequence current and reactive power fluctuation on grid side to maintain balanced output of inverter. Two mathematical inverter models of grid-connected inverter containing LCL grid-side filter under both symmetrical and asymmetric grid are proposed. PR controller method is put forward based on inverter model under asymmetric grid. To ensure the stable operation of the inverter, grid voltage feedforward method is introduced to restrain current shock at the moment of voltage drop. Stable grid-connected operation and LVRT ability at grid drop have been achieved via a combination of rapid positive and negative sequence component extraction of accurate grid voltage synchronizing signals. Simulation and experimental results have verified the superior effectiveness of our proposed control strategy.

Electronic synapses with both long-term and short-term plasticity are considered as significant components for constructing brain-inspired computing systems. Research progress on electrical synapses have proved that memristors possess huge similarities with biological synapses. Nevertheless, an effective mean of manipulating the biological properties of memristors is still unclear. In this letter, we propose a memristor and reveal that the compliance current of electroforming plays an active role in tuning short-term and long-term plasticity of the memristors. The results may provide a useful guideline for manipulating memristor as electronic synapses in the hardware implementation of artificial neural networks.

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Motivated by the complex production management with difficulties in error-prone assembly system and inaccurate supply chain inventory, this paper designs a novel manufacturing execution system (MES) architecture for intelligent monitoring based on wireless sensor network (WSN). The technical perspective includes analysis on the proposed manufacturing resource mutual inductance method under active sensing network, appreciation technology of multisource information, and dynamic optimization technology for manufacturing execution processes. From business perspective, this paper elaborates the impact of RFID investment on complex product by establishing a three-stage supply chain model that involves two suppliers carrying out Stackelberg games (manufacturer and retailer). The optimal cost threshold values of technology investment are examined for both the centralized and the decentralized scenarios utilizing quantitative modeling methods. By analyzing and comparing the optimal profit with or without investment on WSN, this paper establishes a supply chain coordination and boosting model. The results of this paper have contributed significantly for one to make decision on whether RFID should be adopted among its members in supply chain. The system performance and model extension are verified via numerical analyses.