e current tracking control strategy determines the compensation performance of shunt active power filter (SAPF). Due to inadequate compensation of the main harmonic by traditional proportional integral (PI) control, a control algorithm based on PI and multi vector resonant (VR) controllers is proposed to control SAPF. e mathematical model of SAPF is built, and basic principle of VR controller is introduced. Under the synchronous reference frame, the proposed control method based on pole zero cancellation is designed, which narrows the order of the control system and improves the system dynamic response and the control accuracy. en the feasibility of the method is demonstrated by analyzing the closed loop frequency characteristics of the system. Finally, the simulation and experimental results are carried out to verify the performance of the proposed method.

This paper presents a new parameterized nonlinear least squares (PNLS) algorithm for unsupervised nonlinear spectral unmixing (UNSU). The PNLS-based algorithms transform the original optimization problem with respect to the endmembers, abundances, and nonlinearity coefficients estimation into separate alternate parameterized nonlinear least squares problems. Owing to the Sigmoid parameterization, the PNLS-based algorithms are able to thoroughly relax the additional nonnegative constraint and the nonnegative constraint in the original optimization problems, which facilitates finding a solution to the optimization problems . Subsequently, we propose to solve the PNLS problems based on the Gauss-Newton method. Compared to the existing nonnegative matrix factorization (NMF)-based algorithms for UNSU, the well-designed PNLS-based algorithms have faster convergence speed and better unmixing accuracy. To verify the performance of the proposed algorithms, the PNLS-based algorithms and other state-of-the-art algorithms are applied to synthetic data generated by the Fan model and the generalized bilinear model (GBM), as well as real hyperspectral data. The results demonstrate the superiority of the PNLS-based algorithms.

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Energy storage charging pile participating in the joint operation of power grid can not only reduce the cost of power grid expansion, but also obtain the benefit of participating in the auxiliary management service of power grid demand side response, so as to reduce operation cost. In this paper, energy storage charging pile is used to participate in the joint operation optimization of grid demand side response, and a model of optimal allocation of container energy storage in distribution network is proposed. Based on operation strategy of Optical storage charging station vehicle, the model aims to maximize investor's income in investment cycle, considering the income of participating in the voltage regulation, the subsidy income of delaying upgrading of distribution network, its investment and operation cost, and considering the constraints of voltage regulation of distribution network, the conversion of access nodes, energy conservation, etc., so as to optimize the number and rated capacity of Optical storage charging station vehicle. Finally, the case study of ieee33 node system is carried out. The results show that optimal configuration model can make investors of optical storage charging station gain profits and improve the economy of optical storage charging station.