PV single-phase grid-connected converter : dc-link voltage sensorless prospective

In this paper, a dc-link voltage sensorless control technique is proposed for single-phase two-stage grid-coupled photovoltaic (PV) converters. Matching conventional control techniques, the proposed scheme assigns the function of PV maximum power point tracking to the chopper stage. However, in the inverter stage, conventional techniques employ two control loops: outer dc-link voltage and inner grid current control loops. Diversely, the proposed technique employs only current control loop and mitigates the voltage control loop, thus eliminating the dc-link high-voltage sensor. Hence, system cost and footprint are reduced, and control complexity is minimized. Furthermore, the removal of the dc-link voltage loop proportional-integral controller enhances system stability and improves its dynamic response during sudden environmental changes. The system simulation is carried out, and an experimental rig is implemented to validate the proposed technique effectiveness. In addition, the proposed technique is compared with the conventional one under varying irradiance conditions at different dc-link voltage levels, illustrating the enhanced capabilities of the proposed technique

Improved performance low-cost incremental conductance PV MPPT technique

Variable-step incremental conductance (Inc.Cond.) technique, for photovoltaic (PV) maximum power point tracking, has merits of good tracking accuracy and fast convergence speed. Yet, it lacks simplicity in its implementation due to the mathematical division computations involved in its algorithm structure. Furthermore, the conventional variable step-size, based on the division of the PV module power change by the PV voltage change, encounters steadystate power oscillations and dynamic problems especially under sudden environmental changes. In this study, an enhancement is introduced to Inc.Cond. algorithm in order to entirely eliminate the division calculations involved in its structure. Hence, algorithm implementation complexity is minimised enabling the utilisation of low-cost microcontrollers to cut down system cost. Moreover, the required real processing time is reduced, thus sampling rate can be improved to fasten system response during sudden changes. Regarding the applied step-size, a modified variable-step size, which depends solely on PV power, is proposed. The latter achieves enhanced transient performance with minimal steady-state power oscillations around the MPP even under partial shading. For proposed technique's validation, simulation work is carried out and an experimental set up is implemented in which ARDUINO Uno board, based on low-cost Atmega328 microcontroller, is employed

High performance single-phase single-stage grid-tied PV current source inverter using cascaded harmonic compensators

In this paper, a single-phase single-stage photovoltaic (PV) grid-tied system is investigated. The conventional Pulse Width Modulated (PWM) voltage source inverter (VSI) is replaced by a PWM current source inverter (CSI) for its voltage boosting capabilities, inherent short-circuit proof and higher reliability features. Modeling, design and analysis of the considered CSI are presented altogether with enhanced proposed control loops aided with a modified PWM technique. DC-link even current harmonics are commonly reflected as low-order odd harmonics in the grid resulting in a poor quality grid current. In order to overcome the latter, a high performance Proportional Resonant Controller, applied in the inverter inner grid current loop, is proposed using cascaded resonant control units tuned at low-order frequencies to eliminate injected grid current harmonics. Hence, with a less-bulky smoothing inductor at the CSI DC-side, grid power quality and system efficiency are simultaneously improved. Simulation and experimental results verify the proposed controller effectiveness

Continuous-input continuous-output current buck-boost DC/DC converters for renewable energy applications : modelling and performance assessment

Stand-alone/grid connected renewable energy systems (RESs) require direct current (DC)/DC converters with continuous-input continuous-output current capabilities as maximum power point tracking (MPPT) converters. The continuous-input current feature minimizes the extracted power ripples while the continuous-output current offers non-pulsating power to the storage batteries/DC-link. CUK, D1 and D2 DC/DC converters are highly competitive candidates for this task especially because they share similar low-component count and functionality. Although these converters are of high resemblance, their performance assessment has not been previously compared. In this paper, a detailed comparison between the previously mentioned converters is carried out as several aspects should be addressed, mainly the converter tracking efficiency, conversion efficiency, inductor loss, system modelling, transient and steady-state performance. First, average model and dynamic analysis of the three converters are derived. Then, D1 and D2 small signal analysis in voltage-fed-mode is originated and compared to that of CUK in order to address the nature of converters' response to small system changes. Finally, the effect of converters’ inductance variation on their performance is studied using rigorous simulation and experimental implementation under varying operating conditions. The assessment finally revels that D1 converter achieves the best overall efficiency with minimal inductor value

A PMSG Wind Energy System Featuring Low-Voltage Ride-through via Mode-Shift Control

Low-voltage ride-through (LVRT) and grid support capability are becoming a necessity for grid-tied renewable energy sources to guarantee utility availability, quality and reliability. In this paper, a swap control scheme is proposed for grid-tied permanent magnet synchronous generator (PMSG) MW-level wind turbines. This scheme shifts system operation from maximum power point tracking (MPPT) mode to LVRT mode, during utility voltage sags. In this mode, the rectifier-boost machine-side converter overtakes DC-link voltage regulation independently of the grid-side converter. The latter attains grid synchronization by controlling active power injection into the grid to agree with grid current limits while supporting reactive power injection according to the sag depth. Thus grid code requirements are met and power converters safety is guaranteed. Moreover, the proposed approach uses the turbine-generator rotor inertia to store surplus energy during grid voltage dips; thus, there is no need for extra hardware storage devices. This proposed solution is applied on a converter topology featuring a minimal number of active switches, compared to the popular back-to-back converter topology. This adds to system compatibility, reducing its size, cost and switching losses. Simulation and experimental results are presented to validate the proposed approach during normal and LVRT operation.</jats:p

A PMSG Wind Energy System Featuring Low-Voltage Ride-through via Mode-Shift Control

Low-voltage ride-through (LVRT) and grid support capability are becoming a necessity for grid-tied renewable energy sources to guarantee utility availability, quality and reliability. In this paper, a swap control scheme is proposed for grid-tied permanent magnet synchronous generator (PMSG) MW-level wind turbines. This scheme shifts system operation from maximum power point tracking (MPPT) mode to LVRT mode, during utility voltage sags. In this mode, the rectifier-boost machine-side converter overtakes DC-link voltage regulation independently of the grid-side converter. The latter attains grid synchronization by controlling active power injection into the grid to agree with grid current limits while supporting reactive power injection according to the sag depth. Thus grid code requirements are met and power converters safety is guaranteed. Moreover, the proposed approach uses the turbine-generator rotor inertia to store surplus energy during grid voltage dips; thus, there is no need for extra hardware storage devices. This proposed solution is applied on a converter topology featuring a minimal number of active switches, compared to the popular back-to-back converter topology. This adds to system compatibility, reducing its size, cost and switching losses. Simulation and experimental results are presented to validate the proposed approach during normal and LVRT operation

Bi-Functional Non-Superconducting Saturated-Core Inductor for Single-Stage Grid-Tied PV Systems: Filter and Fault Current Limiter

Single-stage grid-interfaced PV topologies have challenges with high grid fault currents, despite being more efficient, simpler to implement, and less expensive than two-stage ones. In such systems, a single inverter is required to perform all grid-interface tasks. i.e., maximum power point tracking (MPPT), DC voltage stabilization, and grid current control. This necessitates a hardware-based fault current limitation solution rather than a software-based one to avoid adding to the inverter&rsquo;s control complexity and to mitigate the implications of PV system tripping. Therefore, in this study, a dual-functional non-superconducting saturated-core inductor-based (SCI) reactor is proposed to be applied at the output of a single-stage PV inverter. It involves two operation modes: a grid pre-fault mode where it filters the line current, hence minimizing its THD, and a grid-fault mode where it acts as a fault current limiter (FCL). Controlling the DC saturation current flowing into its control winding terminals alters the core magnetization of the SCI to vary its impedance between a low value during normal utility operation and a maximal value during faults. Consequently, the system is protected against inverter failures or unnecessary circuit-breaker tripping, which preserves service continuity and reduces system losses. Moreover, compared to existing FCLs, the proposed topology is an appealing candidate in terms of cost, size, reliability, and harmonic filtering ability. The bi-functionality and usefulness of the proposed reactor are confirmed using simulation and experimental results

A lightweight deep learning framework for transformer fault diagnosis in smart grids using multiple scale CNN features

Abstract Scheduled maintenance and condition monitoring of power transformers in smart grids is mandatory to reduce their downtimes and maintain economic benefits. However, to minimize energy losses during inspection, non-invasive fault diagnosis techniques such as thermogram imaging can enable continuous monitoring of transformer health with minimal out-of-service time. Deep learning (DL) has proven to be a fast and efficient intelligent diagnostic tool. In this paper, a DL-based thermography method is proposed called Trans-Light for transformers’ interturn faults detection and short-circuit severity identification. Trans-light extracts deep features from two deep layers of a convolutional neural network (CNN) rather than depending on one layer, thus obtaining more intricate patterns. Moreover, a Dual-tree Complex Wavelet Transform method is adopted which offers two enhancements. First, it acquires time–frequency knowledge besides the already obtained spatial information and second, it reduces the huge deep features dimensionality. Trans-light combines extracted deep features, then a feature selection process is applied to further reduce features’ size, thus decreasing computation burden and reducing classification and training time. To validate the proposed scheme’s diagnosis performance and robustness, different combinations of two CNN models, two feature selection methods, and six classifiers were tested, applying the proposed Trans-light framework, under noise-free and noise-existing conditions. Experimental results indicated that the combination of the LDA classifier, applied with the ResNet-18 CNN model and trained with merged deep features undergoing the chi-square (χ2) selection approach, attained superior performance under noise-free conditions. Compared to its counterparts in previous work, this configuration outperforms their performance since it uses the fewest features’ number yet maintains 100% classification accuracy. Besides, it attained robust performance under two different noise natures again with minimal features’ dimension, thus minimizing computational load and implementation complexity