This paper proposes a method for extracting the intrinsic parameters of a photovoltaic (PV) generator by using shuffled complex evolution (SCE) technique for a double-diode PV model. The characteristic equation of a double-diode PV presents a nonlinear behavior and the determination of the intrinsic parameters from a I × V experimental curve requires the use of nonlinear optimization methods. To evaluate the accuracy of the SCE technique for extracting the intrinsic PV parameters, a comparison with other well-known methods is presented; in particular, analytic method, Levenberg-Marquardt, genetic algorithms (GA), differential evolution (DE), and particle swarm optimization (PSO) are considered. This comparison is performed by using statistical analysis and by estimating the relative error of parameter values; it has been applied to an unknown PV module and to a known PV cell. The obtained results showed that, compared with other evolutionary methods (GA, DE and PSO), the SCE presents the lowest computational time and requires less iterations/generations to converge. All the results prove that the proposed method is feasible, faster, and presents better results than the conventional ones.

Analysis and control of a dynamic voltage restorer are described. The voltage restorer is based on a four-leg voltage source converter. The three-phase input variables are resolved into the positive, negative and zero-sequence components using a weighted, recursive, least-squares estimator. Identical controllers have been used for each sequence component. A laboratory model of the restorer has been constructed and its performance has been tested by simulation and experiments.

In this paper, we present two modulation schemes for generating unbalanced voltages by means of four-leg voltage-source inverters. The first modulation is an extended scheme of a digital-scalar pulsewidth modulation previously proposed for controlling three-leg inverters. The second one is based on the decomposition of the voltage reference signals into their symmetrical components. The schemes are compared theoretically by simulations and experimental results. As a consequence, we find out a total equivalence between the two modulations despite their different conceptions. The fundamentals of both techniques and a mathematical proof of their equivalence are unfolded. Also, the performances of the techniques with respect to the harmonic distortion and power switching loss are discussed. The results show that the techniques are effective.

This article presents a finite-set model predictive control (FS-MPC) applied to the shunt active power filters (SAPF) based on three-phase inverters connected in parallel sharing the same dc-link. The discrete-time model of the system is used to predict the future value of the grid, circulation, and offset currents. The presence of circulation and offset currents occurs due to the connection of the two inverters in parallel sharing the same dc-link. There are 64 switching state vectors for SAPF and, in order to reduce the burden of calculation, only 30 switching states are chosen and applied, however keeping the advantages of the FS-MPC algorithm. The control strategy ensures the sinusoidal shape of the grid current, high power factor, and circulating and offset currents suppression. The FS-MPC has its performance compared to the pulsewidth modulation (PWM) strategy considering the SAPF with two parallel inverters, the conventional SAPF and the neutral-point-clamped SAPF. These comparisons include harmonic distortion, power semiconductor losses, and analysis of dc-link capacitor losses. As a multilevel topology, the SAPF with two parallel inverters using FS-MPC present competitive efficiency and can be applied with a good performance in industrial and residential applications. Simulation results and a laboratory-scale experimental platform is used for corroborating the proposal.

A repetitive predictive control for grid-connected inverter current control scheme is presented in this paper under voltage harmonic distortion in the stationary reference frame. Predictive control is an approach that uses a receding horizon to achieve the optimal track for the reference. In this approach, the repetitive controller behavior is added to the predictive control to increase its performance under distorted voltage conditions. In addition, to apply the controller in the generation system, controller is designed from the perspectives of the power system. The controller is designed considering the state-space model in the stationary reference frame. The controller performance was verified using a laboratory experimental setup under distorted grid voltage condition. Experimental results confirm that the proposed controller can effectively suppress harmonics under both normal operation and distorted grid voltage conditions, and also satisfy the requirements stipulated in IEEE Std. 1547.2-2008.

A technique for decomposing instantaneous three-phase voltages and currents into sequence components has been described. The technique is based on a recursive weighted least squares procedure. The main advantage of the proposed technique is the use of the same covariance and gain matrices for resolving any number of three-phase variables into their respective sequence components. The proposed technique also estimates the dc offset in the sensed variable, and these are eliminated during the processing. Finally, the proposed technique has been implemented in a digital signal processor (DSP) and has been applied to the open-loop control of a laboratory-scale dynamic voltage restorer.