This paper focuses on sensor fault detection and isolation (FDI) for electrical systems. A new, easy and fast FDI algorithm is proposed, keeping system performances unchanged under certain faulty sensor conditions when reconfigurations are available. The proposed FDI algorithm is derived from a parity space approach and is based on temporal redundancies. It is insensitive to parameter variations since no model knowledge is required. Also, it is available for a large class of electrical systems such as single- or three-phase power converters, dc or ac electrical drives, etc. Moreover, the residual threshold used for FDI is accurately defined and is suitable for the whole operating range. Simulations results are presented to illustrate the good functionality of theoretical developments. Numerous experimental results are also shown to validate the effectiveness of the proposed FDI algorithm and to highlight its advantages for the control of electrical systems.

In this article, the dynamic responses of wind turbine systems are analytically and numerically investigated. For this purpose, analytic differential equations of motion of wind turbine components subjected to vibration (the blades, the nacelle, and the tower) are solved. This allows determining their dynamic characteristics, mode shapes, and natural frequencies. Two models of two three-dimensional (3D) micro-turbine that are created by the finite element method are set up using the new version of the academic finite element analysis software ANSYS. The first wind turbine is a standard micro three-bladed turbine and the second one is a micro six-bladed Rutland 504. Their natural frequencies and mode shapes are identified based on the modal analysis principle to check the validity of designed models. Dynamic behaviors at several operating conditions of wind turbines are established. Then, spectrum graphs of the structures along x-, y- and z-axis are analyzed.

The installed energy production capacity of wind turbines is growing intensely on a global scale, making the reliability of wind turbine subsystems of greater significance. However, many faults like Inter-Turn Short-Circuit (ITSC) may affect the turbine generator and quickly lead to a decline in supplied power quality. In this framework, this paper proposes a Sliding Mode Observer (SMO)-based Fault Tolerant Control (FTC) scheme for Induction Generator (IG)-based variable-speed grid-connected wind turbines. First, the dynamic models of the wind turbine subsystems were developed. The control schemes were elaborated based on the Maximum Power Point Tracking (MPPT) method and Indirect Rotor Flux Oriented Control (IRFOC) method. The grid control was also established by regulating the active and reactive powers. The performance of the wind turbine system and the stability of injected power to the grid were hence analyzed under both healthy and faulty conditions. The robust developed SMO-based Fault Detection and Isolation (FDI) scheme was proved to be fast and efficient for ITSC detection and localization.Afterwards, SMO were involved in scheming the FTC technique. Accordingly, simulation results assert the efficacy of the proposed ITSC FTC method for variable-speed wind turbines with faulty IG in protecting the subsystems from damage and ensuring continuous connection of the wind turbine to the grid during ITSC faults, hence maintaining power quality.