This paper presents a method of Traveling Wave Fault location based on the improved Hilbert-Huang Transform. First, Intrinsic Mode Functions (IMF) of traveling waves are extracted by Ensemble Empirical Mode Decomposition (EEMD). Then Hilbert Transform is applied to calculate the corresponding instantaneous frequency of the highest frequency component (IMF1), the instantaneous frequency and corresponding time-frequency graph are obtained. Second, the arrival time and speed can be detected by the first instantaneous frequency's mutational point. Finally, the improved two-terminal traveling wave fault location principle is used to calculate the fault distance. Relevant simulation results are performed to verify the correctness of the method by EMTDC software.

Battery energy storage devices (ESDs) have become more and more commonplace to maintain the stability of islanded power systems. Considering the limitation in inverter capacity and the requirement of flexibility in the ESD, the droop control was implemented in paralleled ESDs for higher capacity and autonomous operation. Under the conventional droop control, state-of-charge (SoC) errors between paralleled ESDs is inevitable in the discharging operation. Thus, some ESDs cease operation earlier than expected. This paper proposes an adaptive accelerating parameter to improve the performance of the SoC error eliminating droop controller under the constraints of a microgrid. The SoC of a battery ESD is employed in the active power droop coefficient, which could eliminate the SoC error during the discharging process. In addition, to expedite the process of SoC error elimination, an adaptive accelerating parameter is dedicated to weaken the adverse effect of the constraints due to the requirement of the system running. Moreover, the stability and feasibility of the proposed control strategy are confirmed by small-signal analysis. The effectiveness of the control scheme is validated by simulation and experiment results.

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