Aissa Chouder

Global MPPT Scheme for Photovoltaic String Inverters Based on Restricted Voltage Window Search Algorithm

String inverter photovoltaic (PV) systems with bypass diodes require improved global maximum power point tracking (GMPPT) algorithms to effectively reach the absolute maximum power operating point. Several GMPPT algorithms have been proposed to deal with this problem, but most of them require scanning wide voltage ranges of the PV array from nearly zero voltage to open-circuit voltage that increases the scanning time and, in turn, causes energy loss. This paper presents a novel GMPPT method which significantly restricts the voltage window search range and tracks the global power peak rapidly in all shading conditions. Simulation tests and experimental comparisons with another GMPPT algorithm are presented to highlight the features of the presented approach.

Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

An artificial bee colony based MPPT under partially shaded conditions is proposed.Photovoltaic systems are considered.A co-simulation methodology combining Simulink and Pspice has been adopted.Excellent efficiency and tracking performance compared to the PSO-based MPPT.The effectiveness of the proposed method has been confirmed experimentally. Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink? and Cadence/Pspice?, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.

Analysis Model of Mismatch Power Losses in PV Systems

A novel procedure to extract and analyze the power losses, mainly due to mismatch effects, in a photovoltaic (PV) system is presented. The developed model allows the extraction of the main PV module and PV array parameters from I-V characteristics, as well as in dynamic behavior under real conditions of work. The method allows a good estimation of the mismatch effect on the total PV system power losses.

Shading effects in characteristic parameters of PV modules

Main characteristic parameters of a PV module present substantial variations in case of partial shading, resulting in important reductions of the output power. A commercial PV module formed by 36 solar cells in series has been tested varying the shadow rate of one of its cells and changes in most important characteristic parameters have been analyzed. Using parameter extraction techniques we have obtained the evolution of series and shunt resistance of the PV module in function of shadow rate.

Parameters extraction of photovoltaic module for long-term prediction using artifical bee colony optimization

In this paper, a heuristic optimization approach based on Artificial Bee Colony (ABC) algorithm is applied to the extraction of the five electrical parameters of a photovoltaic (PV) module. The proposed approach has several interesting features such as no prior knowledge of the physical system and its convergence is not dependent on the initial conditions. The extracted parameters have been tested against several static IV characteristics of different PV modules from different manufacturers. In order to assess the effectiveness of the extracted parameters, a dynamic model based maximum power point has been used and compared to real measurements data of a grid connected system located in the Centre de Developpement des Energies Renouvelables (CDER) in Algiers. In addition, comparison of the proposed ABC algorithm with some well-known heuristic algorithms such as, Particle Swarm Optimization (PSO) and Differential Evolution (DE), has given better results in terms of local minimum avoidance and accuracy.

Prediction-based Deadbeat Control for Grid-connected Inverter with L-filter and LCL-filter

Abstract—In this article, an improved deadbeat control algorithm suitable for digital signal processor-based circuit implementation is proposed. The control algorithm allows the derivation of a nearly sine wave output current with a fixed switching frequency of a current-controlled voltage source inverter. Two low-pass output filters configurations are considered in this study: a simple inductance filter and an LCL-filter. By taking advantage of prior knowledge of the state variables’ shape, the improved deadbeat control algorithm is based on a simple prediction model to derive the expected duty cycle needed to switch on and off the power switches. The control study of the grid-connected inverter with L and LCL output filters has been considered using a co-simulation approach with (Powersim Inc., Rockville, Maryland, USA) and MATLAB software (The MathWorks, Natick, Massachusetts, USA). The obtained results show the improvement of both shape quality and tracking accuracy of the output current quantified by low ripple content and a nearly unity power factor.

Efficient fault detection and diagnosis procedure for photovoltaic systems

This paper proposes a simple method to detect and diagnose short circuits and open circuits faults in photovoltaic (PV) systems based on the evaluation of three coefficients. The proposed method consists fundamentally on two steps: an offline step based on a simulated model and an online step in which a comparison of the real measured coefficients against those obtained in the offline step is performed. The simulated model of the PV array has been validated using a real experimental data of a daily profile from a 3 kWp grid connected system installed at Algiers. The effectiveness of the proposed method has been evaluated based on PSIM™/Matlab™ Co-simulation approach of four operating cases: healthy operating case, one short circuit module in a string operating case, five short circuits modules in a string operating case, and finally a completely disconnected string operating case. Simulation results have demonstrated the ability of the proposed method to detect and diagnose short circuits and open circuits faulty operation under any meteorological conditions.

Behavioral data of thin-film single junction amorphous silicon (a-Si) photovoltaic modules under outdoor long term exposure

Four years׳ behavioral data of thin-film single junction amorphous silicon (a-Si) photovoltaic (PV) modules installed in a relatively dry and sunny inland site with a Continental-Mediterranean climate (in the city of Jaén, Spain) are presented in this article. The shared data contributes to clarify how the Light Induced Degradation (LID) impacts the output power generated by the PV array, especially in the first days of exposure under outdoor conditions. Furthermore, a valuable methodology is provided in this data article permitting the assessment of the degradation rate and the stabilization period of the PV modules. Further discussions and interpretations concerning the data shared in this article can be found in the research paper “Characterization of degradation and evaluation of model parameters of amorphous silicon photovoltaic modules under outdoor long term exposure” (Kichou et al., 2016) [1].