Seghir Benhalima

This paper presents the experimental implementation of a LMS‐Adaline‐based ANFIS controller of an improved power‐quality photovoltaic (PV) generating system connected to the grid. The proposed system applies an adaptive neuro‐fuzzy inference system (ANFIS) to control the DC–DC boost converter integrated with PV to achieve the maximum power point tracking (MPPT) operating condition. For power‐quality improvement at the point of common coupling (PCC), Adaline (adaptive linear element)‐based control algorithm is used to estimate the reference grid currents. To achieve high performance with fast dynamic response during transition and to regulate constant the DC and the AC voltages without saturation phenomena, ANFIS controller is employed. The real‐time benchmark realised in the laboratory, to implement the setup, uses a dSPACE controller. To demonstrate the performance of the proposed configuration, the system is first simulated offline under numerous critical scenarios. The experimental results are then presented to validate the concept.

This paper proposes a sliding mode control (SMC) method for an onshore voltage-source-converter (VSC) used in a high-voltage-direct-current (HVDC) transmission system. The onshore VSC-HVDC station is based on a two-level voltage converter topology that is used to interconnect an offshore wind farm (OWF) with the ac main grid via two dc cables. The OWF is composed of ten variable speed wind turbines based on permanent magnet synchronous generators (VSWT/PMSGs). The VSWT/PMSGs are connected in parallel to a common dc-bus. The ac main grid receives the required active power from the OWF through a transformer, 12-pulse diode rectifiers, boost converters, two dc cables and a VSC-HVDC station. The boost converters are used to operate at speeds for maximum power extraction from the VSWT. SMC is used to ensure a stable operation of the VSC-HVDC station during dc fault, as well as to avoid controller saturation, a behavior that is usually seen when using linear controllers. The effectiveness of the proposed control method on system operation under dc fault is demonstrated by simulations carried out using Matlab/Simulink. In addition, a scaled-down laboratory prototype of the system is built and tested to validate the performance of the proposed control scheme.

In this paper enhanced control strategies for standalone microgrids based on solar photovoltaic systems (SVPAs) and diesel engine driven fixed speed synchronous generators, are presented. Single-phase d-q theory-based sliding mode controller for voltage source converter voltage source converter (VSC) is employed to mitigate harmonics, balance diesel generator (DG) current, and to inject the generated power by SVPA into local grid. To achieve fast dynamic response with zero steady-state error during transition, sliding mode controller for inner control loop is employed. To achieve maximum power point tracking (MPPT) from SVPA without using any MPPT method, a DC-DC buck boost converter supported by battery storage system is controlled using a new control strategy based on sliding mode control with boundary layer. In addition, modeling and detailed stability analysis are performed. The performance of the developed control strategies, are validate by simulation using MATLAB/Simulink and in real-time using hardware prototype.