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The DC transmission, distribution and networking have been applied to medium and low voltage power grids, and have exhibited apparent advantages and favorable application perspective. Different from traditional AC power grids, DC power grids have shown features of low inertia, weak damping and the inclination of oscillation. The intermix of fast switching transients and control dynamics makes the DC grid much more complicated. In addition, the power fluctuation of renewable energy generation and demand-response loads imposes difficulties on the stable and smooth running of the DC grid. However, no comprehensive study has been reported on dynamic and transient patterns and characteristics of the DC power grid. In this paper, through both simulation and theoretical analysis, the transient and dynamic characteristics of medium and low voltage DC power grids are systematically tested, classified and analyzed. Finally, the mechanisms and general conclusions are extracted and refined.

Transient voltage instability always starts from low-voltage load areas and burgeons to high-voltage grids, where the dynamic load is one significant factor. There is an urgent demand for effective and efficient modeling of electrical loads. Thereby, this paper proposes a classification and aggregation approach to model the multi-voltage-level load clusters. Load clusters from online identification are classified and grouped according to their stabilities and transient characteristics. Then, based on the weighted average of induction motor (IM) voltage angles, an approach is proposed to aggregate models of grouped loads sharing similar dynamic features. The proposed approach can aggregate load models from a low voltage level to a higher one layer by layer. Thus, the aggregated model keeps the primary transient characteristics, as well as dramatically reduces the simulation scale and the calculation complexity.

The digital control system delays the system, Considering the control delay and the resonance problem for LCL filter, a undamped control strategy of single-phase LCL type grid connected inverter is proposed. The grid connected current is controlled by network side current feedback. Not only the system unit power factor can be realized, but also no additional sensors are added, so the system control cost is reduced. The feasibility of undamped control is analyzed in detail, and the calculation procedure of controller parameters is given. An experimental platform is built. The correctness and effectiveness of the undamped control strategy are verified on the platform.

In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.