Data-Driven Virtual Inertia Control Method of Doubly Fed Wind Turbine

This paper presents a data-driven virtual inertia control method for doubly fed induction generator (DFIG)-based wind turbine to provide inertia support in the presence of frequency events. The Markov parameters of the system are first obtained by monitoring the grid frequency and system operation state. Then, a data-driven state observer is developed to evaluate the state vector of the optimal controller. Furthermore, the optimal controller of the inertia emulation system is developed through the closed solution of the differential Riccati equation. Moreover, a differential Riccati equation with self-correction capability is developed to enhance the anti-noise ability to reject noise interference in frequency measurement process. Finally, the simulation verification was performed in Matlab/Simulink to validate the effectiveness of the proposed control strategy. Simulation results showed that the proposed virtual inertia controller can adaptively tune control parameters online to provide transient inertia supports for the power grid by releasing the kinetic energy, so as to improve the robustness and anti-interference ability of the control system of the wind power system.

Sensitivity of the Solution to Nonsymmetric Differential Matrix Riccati Equation

Nonsymmetric differential matrix Riccati equations arise in many problems related to science and engineering. This work is focusing on the sensitivity of the solution to perturbations in the matrix coefficients and the initial condition. Two approaches of nonlocal perturbation analysis of the symmetric differential Riccati equation are extended to the nonsymmetric case. Applying the techniques of Fréchet derivatives, Lyapunov majorants and fixed-point principle, two perturbation bounds are derived: the first one is based on the integral form of the solution and the second one considers the equivalent solution to the initial value problem of the associated differential system. The first bound is derived for the nonsymmetric differential Riccati equation in its general form. The perturbation bound based on the sensitivity analysis of the associated linear differential system is formulated for the low-dimensional approximate solution to the large-scale nonsymmetric differential Riccati equation. The two bounds exploit the existing sensitivity estimates for the matrix exponential and are alternative.

Optimal Control of PMSG Based Wind Energy Conversion System using State-Dependent DRE

Generation of electricity from wind is becoming more economical and popular with improved system design with modern control techniques. To capture energy from the inherently variable wind source and converting it into good quality electricity need to use advanced techniques in equipment and control . Since all the subsystems involved in the generation of electricity from wind are highly nonlinear, optimal control using linear models and linear techniques will not be effective. This paper presents a closed loop optimal control for a PMSG based wind energy conversion system using State Dependent Differential Riccati Equation. A suboptimal control is obtained for the non-linear system through differential Riccati equation, which is solved by converting in to linear Lyapunov equation by change of variables in the finite-horizon. The effectiveness of the technique is verified by simulating on MATLAB platform.