http://dspace.univ-setif.dz:8888/jspui/bitstream/123456789/2999/1/Article_BELAOUT_Mai_2018.pdf

Multiclass adaptive neuro-fuzzy classifier and feature selection techniques for photovoltaic array fault detection and classification

The environmentally clean nature of solar photovoltaic (PV) technology causes PV power generation to be embraced by all countries across the globe. Consequently, installation and utilization of PV power systems have seen much growth in recent years. Although PV arrays of such systems are robust, they are not immune to faults. To guarantee reliable power supply, economic returns, and safety of both humans and equipment, highly accurate fault detection, diagnosis, and interruption devices are required. In this paper, an overview of four major PV array faults and their causes are presented. Specifically, ground fault, line-line fault, arc fault, and hot spot fault have been covered. Next, conventional and advanced fault detection and diagnosis (FDD) techniques for managing these faults are reviewed. Moreover, a single evaluation metric has been proposed and utilized to evaluate the performances of the advanced FDD techniques. Finally, based on the papers reviewed, PV array fault management future trends and possible recommendations have been outlined.

/pdf/review-and-performance-evaluation-of-photovoltaic-array-1okizxvri8.pdf

Review and Performance Evaluation of Photovoltaic Array Fault Detection and Diagnosis Techniques

A comprehensive review of improving power quality using active power filters

This paper presents a dual voltage source inverter (DVSI) scheme to enhance the power quality and reliability of the microgrid system. The proposed scheme is comprised of two inverters, which enables the microgrid to exchange power generated by the distributed energy resources (DERs) and also to compensate the local unbalanced and nonlinear load. The con- trol algorithms are developed based on instantaneous symmetrical component theory (ISCT) to operate DVSI in grid sharing and grid injecting modes. The proposed scheme has increased relia- bility, lower bandwidth requirement of the main inverter, lower cost due to reduction in ﬁlter size, and better utilization of micro- grid power while using reduced dc-link voltage rating for the main inverter. These features make the DVSI scheme a promising option for microgrid supplying sensitive loads. The topology and control algorithm are validated through extensive simulation and experimental results.

A Grid-Connected Dual Voltage Source Inverter with Power Quality Improvement Features

A real-time nonlinear model predictive control using a self-feedback recurrent fuzzy neural network (SFRFNN) estimator for an active power filter is developed to improve the performance of harmonic compensation. First, an SFRFNN with a recurrent structure and fuzzy rules is proposed as a prediction model for nonlinear systems. The SFRFNN merges the advantages of the fuzzy system and the recurrent neural network with a self-feedback structure, which can significantly improve the dynamic performance. Second, the optimization method based on gradient descent is employed to solve the optimal control problem. In addition, the convergence of the proposed SFRFNN and the stability of RT-NMPC are guaranteed using Lyapunov stability theory. Finally, the hardware experiment demonstrated that the proposed method has better performance in both steady and dynamic states compared with existing methods and RT-NMPC using a radial basis function neural network. 

Real-Time Nonlinear Model Predictive Control of Active Power Filter Using Self-Feedback Recurrent Fuzzy Neural Network Estimator

Pack U-Cell (PUC) multi-level inverter is an attractive topology which widely investigated in the past few years for renewable energy conversion systems. This study introduces a modified five-level packed Unit-cell converter (MPUC5) for single-phase double stage grid-tied photovoltaic (PV) system with unity power factor. The proposed system operates as a single-phase active power filter able to compensate reactive power generated by non-linear loads connected to the point of common coupling, feeds the non-linear load by the generated PV power, and injects the extra power into the grid. The MPUC5 inverter has a special topology with two DC-link capacitors and six switches. One DC-link of the inverter is connected to the PV arrays through DC/DC Cuk converter to draw the maximum power. Therefore, finite-control-set model predictive control (FCS-MPC) for such configuration appears as a promising alternative for this inverter to work properly. Where the proposed FCS-MPC algorithm is designed to ensure a high grid current quality, taking into consideration the issue of the capacitor voltages balancing and the switching frequency minimisation. Both simulation results and experimental validation through real-time hardware in the loop system prove the validity and feasibility of the proposed control scheme, regarding PV power management and quality enhancement.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2019.0028

Energy management and power quality enhancement in grid-tied single-phase PV system using modified PUC converter

This work offers a simple and efficient model predictive voltage control strategy with a two-step prediction for improved output voltage control of single-phase inverter used for stand-alone renewable energy systems. The single-phase inverter with output LC filter is used to provide a sinusoidal output voltage, regardless of the arbitrary consumer load profiles. The suggested control algorithm uses the discrete-time model of the inverter and LC filter for two-step prediction of the output voltage for each possible switching state. Then, the control algorithm selects the switching state which minimizes the error between the output voltage and its reference without using any inner controllers or modulators. An accurate extrapolation methodology with reduced computational burden is used to predict the dynamic changes in the output voltage reference. The switching frequency reduction is also attained by considering a simple constraint in the suggested algorithm. Simulation results are presented to verify the feasibility and excellent performance of the suggested controller under linear and nonlinear load conditions, compared to a conventional voltage control strategy based on PI regulators and PWM. Furthermore, experimental tests using a dSPACE system with DS1104 controller have been done to confirm the simulations results.

Model predictive voltage control of a single-phase inverter with output LC filter for stand-alone renewable energy systems

Model predictive control for single phase active power filter using modified packed U-cell (MPUC5) converter

This paper focuses on the control of large-scale grid-connected photovoltaic system. The proposed system is composed of two conversion stages: the first stage contains four PV arrays, each one connected to an individual DC/DC converter (boost converter), while the second stage is a five-level neutral point clamped (NPC) inverter tied to the grid. Each DC-link capacitor input of the NPC inverter is connected to the output of the DC/DC boost converter. In order to enhance the energy harvesting capability of the proposed system, different controllers based on finite-set model predictive control (FS-MPC) are developed and presented. A fast voltage-oriented maximum power point tracking performed by FS-MP current controller (FS-MPCC) is investigated and applied for each boost converter to maximize the produced power from each PV array. Furthermore, a FS-MPC algorithm is proposed to control the centralized five-level NPC inverter. The purposes of the developed controllers are: track the MPP rapidly and accurately under sudden irradiation changes, ensure the balance of the four DC-link capacitor voltages whatever the difference between the extracted powers from each PV system unit, inject the reactive power demanded by the grid operator and also minimize the switching frequency of the five-level NPC inverter. The results obtained through MATLAB/Simulink and Simpower toolbox packages prove that the proposed control scheme provides better performance in comparison with conventional control scheme. Moreover, a high grid current quality and perfect DC-link capacitor voltages balancing are ensured under contrast of extract powers from each PV system.

A Predictive Control Scheme for Large-Scale Grid-Connected PV System Using High-Level NPC Inverter

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power systems based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid current synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage controller based on ISMC theory is proposed to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage-oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid current synchronization. Numerical simulations are performed in a MATLAB/SimulinkTM (R2009b, MathWorks, Natick, MA, USA) environment to evaluate the proposed control strategy. In comparison with conventional control schemes, the developed control strategy provides an accurate maximum power point (MPP) tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under varying irradiation conditions. Moreover, the transfer of the extracted power into the grid is achieved with high quality.

Abdeslem Sahli

Papers

Energy management and power quality enhancement in grid-tied single-phase PV system using modified PUC converter

Model predictive voltage control of a single-phase inverter with output LC filter for stand-alone renewable energy systems

Model predictive control for single phase active power filter using modified packed U-cell (MPUC5) converter

A Predictive Control Scheme for Large-Scale Grid-Connected PV System Using High-Level NPC Inverter

A Robust Control of Two-Stage Grid-Tied PV Systems Employing Integral Sliding Mode Theory