Abstract:The large-scale penetration of wind power might lead to degradation of the power system stability due to its inherent feature of randomness. Hence, proper control designs which can effectively handle various uncertainties become very crucial. This paper designs a novel robust passive control (RPC) scheme of a doubly-fed induction generator (DFIG) for power system stability enhancement. The combinatorial effect of generator nonlinearities and parameter uncertainties, unmodelled dynamics, wind speed randomness, is aggregated into a perturbation, which is rapidly estimated by a nonlinear extended state observer (ESO) in real-time. Then, the perturbation estimate is fully compensated by a robust passive controller to realize a globally consistent control performance, in which the energy of the closed-loop system is carefully reshaped through output feedback passification, such that a considerable system damping can be injected to improve the transient responses of DFIG in various operation conditions of power systems. Six case studies are carried out while simulation results verify that RPC can rapidly stabilize the disturbed DFIG system much faster with less overshoot, as well as supress power oscillations more effectively compared to that of linear proportional-integral-derivative (PID) control and nonlinear feedback linearization control (FLC).

With the improvement of the permeability of wind and photovoltaic (PV) energy, it has become one of the key problems to maintain the small-signal stability of the power system. Therefore, this paper analyzes the small-signal stability in a power system integrated with wind and solar energy. First, a mathematical model for small-signal stability analysis of power systems including the wind farm and PV station is established. And the characteristic roots of the New England power system integrated with wind energy and PV energy are obtained to study their small-signal stability. In addition, the validity of the theory is verified by the voltage drop of different nodes, which proves that power system integrated with wind-solar renewable energy participating in the frequency regulation can restore the system to the rated frequency in the shortest time and, at the same time, can enhance the robustness of each unit.

Large-scale renewable energy sources connected to the grid bring new problems and challenges to the automatic generation control (AGC) of the power system. In order to improve the dynamic response performance of AGC, a biobjective of complementary control (BOCC) with high-participation of energy storage resources (ESRs) is established, with the minimization of total power deviation and the minimization of regulation mileage payment. To address this problem, the strength Pareto evolutionary algorithm is employed to quickly acquire a high-quality Pareto front for BOCC. Based on the entropy weight method (EWM), grey target decision-making theory is designed to choose a compromise dispatch scheme that takes both of the operating economy and power quality into account. At last, an extended two-area load frequency control (LFC) model with seven AGC units is taken to verify the effectiveness and the performance of the proposed method.

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In this paper, a study on frequency adaptability of permanent magnet synchronous generator (PMSG) is carried out, the influence mechanism of the frequency changes on PMSG is revealed. It is proposed that setting the converter protection setting value and PLL parameters reasonably can ensure that the grid frequency change has little effect on the PMSG. The simulation of frequency adaptability of PMSG is realized on Matlab/Simulink, and the simulation results verify the correctness of the conclusion.