Due to the sparsity deployment of nodes, the full connection requirement, and the unpredictable electromagnetic interference on communication caused by high voltage pulse current of Solar Insecticidal Lamps Internet of Things (SIL-IoTs), a Two-Hop Energy Consumption Balanced routing algorithm (THECB) is proposed in this research work. THECB selects next-hop nodes according to 1-hop and 2-hop neighbors’ information. In addition, the greedy forwarding mechanism is expressed in the form of probability; that is, each neighbor node is given a weight between 0 and 1 according to the distance. THECB reduces the data forwarding traffic of nodes whose discharge numbers are relatively higher than those of other nodes so that the unpredictable electromagnetic interference on communication can be weakened. We compare the energy consumption, energy consumption balance, and data forwarding traffic over various discharge numbers, network densities, and transmission radius. The results indicate that THECB achieves better performance than Two-Phase Geographic Greedy Forwarding plus (TPGFPlus), which ignores the requirement of the node-disjoint path.
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<p>The regenerative braking in the tram allows the energy to be returned to the power grid through a power inverter. Since the inverter location between the tram and the power grid is not fixed, resulting in a wide variety of impedance networks at grid coupling points, posing a severe threat to the stable operation of the grid-tied inverter (GTI). By independently changing the loop characteristics of the GTI, the adaptive fuzzy PI controller (AFPIC) can adjust according to different impedance network parameters. It is challenging to fulfill the stability margin requirements of GTI under high network impedance since the PI controller has phase lag characteristics. A correction method of series virtual impedance is proposed, which connects the inductive link in a series configuration with the inverter output impedance, correcting the inverter equivalent output impedance from resistance-capacitance to resistance-inductance and improving the system stability margin. Feedforward control is adopted to improve the system's gain in the low-frequency band. Finally, the specific series impedance parameters are obtained by determining the maximum network impedance and setting the minimum phase margin of 45°. The realization of virtual impedance is simulated by conversion to an equivalent control block diagram, and the effectiveness and feasibility of the proposed method are verified by simulation and a 1 kW experimental prototype.</p>
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