Microgrids are introduced into power grid for managing the high penetration of renewable energy sources(RESs). Based on the resistive characteristics of the microgrid line, this paper proposes an inverter control mode combining the outer power loop controller with anti-droop control and the inner voltage-current dual-loop controller. Meanwhile, a complete small signal model of single inverter including anti-droop control, dual-loop control, filter and branch is established. Then considering the coupling relationship of the output voltage phase angles of each inverter, the small-signal model of the microgrid with multiple parallel inverters is established under the global coordinate system. The static stability analysis of the complete microgrid is carried out by the root locus method. Results show that the anti-droop control is more conducive to the accurate distribution and fast response of the active power output by inverter units than the traditional droop control.

As the scale of the distribution network continues to increase, the importance of distribution network is getting higher and higher. Therefore, it is necessary to achieve fault location and restore it as soon as possible after the fault occurs. This paper proposes a new fault location algorithm for the radial distribution network, which is improved on the basis of traditional matrix algorithm. First, the power failure incidence matrix (PFIM) and power interruption information matrix (PIIM) is constructed based on the topological connection and fault information at each node. The fault location matrix (FLM) is then obtained through PFLM and PIIM to realize the fault location. Second, the accuracy of the proposed algorithm is verified by mathematical derivation. Finally, an 11-node radial distribution network is illustrated to testify the proposed algorithm. Results show that the improved fault location matrix algorithm proposed in this paper can effectively achieve fault location in radial distribution network.

Image jitters occur in the video of the autonomous robot moving on bricks road, which will reduce robot operation precision based on vision. In order to compensate the image jitters, the affine transformation kinematics were established for obtaining the six image motion parameters. The feature point pair detecting method was designed based on Eigen-value of the feature windows gradient matrix, and the motion parameters equation was solved using the least square method and the matching point pairs got based on the optical flow. The condition number of coefficient matrix was proposed to quantificationally analyse the effect of matching errors on parameters solving errors. Kalman filter was adopted to smooth image motion parameters. Computing cases show that more point pairs are beneficial for getting more precise motion parameters. The integrated jitters compensation software was developed with feature points detecting in subwindow. And practical experiments were conducted on two mobile robots. Results show that the compensation costing time is less than frame sample time and Kalman filter is valid for robot vision jitters compensation.

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