Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms i.e. Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters i.e. buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.

Efficient method for wind velocity estimation and power-extraction maximization using a fourth-order Luenberger observer in a wind-energy-conversion system

This paper proposes an advanced method for estimating numerous parameters in a wind-energy-conversion system with high precision,especially in a transient state,including the rotation speed and mechanical torque of the turbine as well as wind velocity.The suggested approach is designed into two parts.First,a fourth-order Luenberger observer is proposed to take into account the significant fluctuations of the mechanical torque that can be caused by wind gusts.This observer provides an accurate estimate of speed and mechanical torque in all weather conditions and especially when the wind is gusting.At the same time,the wind velocity is calculated using the Luenberger observer outputs and a model of the mechanical power generated by the turbine.Second,these estimated parameters are exploited as input in a maximum-power-point tracking(MPPT)algorithm using the tip-speed ratio(TSR)to improve the sensorless strategy control.Simulation results were performed using MATLAB®/Simulink®for both wind gust and real wind profiles.We have verified that for wind gusts with jumps ranging from 3 to 7 m/s,the new observer manages to better follow the rotation speed and the torque of the turbine compared to a usual observer.In addition,we demonstrated that by applying the proposed estimator in the improved TSR-MPPT strategy,it is possible to extract 3.3%more energy compared to traditional approaches.