Mamadou Lamine Doumbia

Hybrid renewable energy systems (HRES) now sit at the centre of efforts to decarbonize electricity supply. The literature describing them has grown faster than anyone has organized it. Work on storage integration, optimization, artificial intelligence (AI) and digital energy management has accumulated largely in parallel, and existing reviews tend to treat each strand on its own. This paper takes on that fragmentation through a structured, bibliometrically grounded synthesis instead of new experimental work. What it offers is a maturity–momentum framework that places every research theme on two axes at once: accumulated citation influence and current publication growth. The position a theme occupies separates settled knowledge from frontiers that are busy but still empirically thin. The framework was applied to a corpus of 18,420 Scopus-indexed documents published between 2000 and 2024, retrieved through eight pre-specified TITLE-ABS-KEY queries and screened against documented eligibility criteria. From that corpus, 150 studies were read in full and synthesized thematically. The corpus spans 1840 source journals and 142 countries, carries 312,640 citations, yields a field-level h-index of 214, and grew at a compound annual rate of 18.3% between 2015 and 2024. One relationship runs through the whole analysis: citation maturity and publication momentum move in opposite directions. Early HRES design and pumped hydro storage record the highest citation intensity, at 48.2 and 42.1 citations per document, while their output decelerates. AI-driven operation and future-oriented themes grow fastest, with AI-related output rising roughly 65-fold between 2010 and 2024, yet they rest on comparatively thin citation foundations. Reported minimum levelized cost of energy across successive families of optimization methods fell from USD 0.091 kWh⁻¹ in 2019 to USD 0.037 kWh⁻¹ in 2024, and the reductions arrived in steps that coincide with changes in the method family, not with incremental algorithmic refinement. Eight gaps persist: large-scale experimental validation, multi-energy interoperability, uncertainty-aware optimization, cybersecurity of AI-enabled control, Digital Twin standardization, explainable AI, lifecycle sustainability assessment, and integrated electricity–hydrogen market design. Taken together, they indicate that the weakest point in the field is no longer algorithmic capability. It is the shortage of long-horizon field evidence against which simulated gains can be tested.

This work proposes a real-time wind power estimation approach for a direct-current (DC) wind energy conversion system based on an artificial neural network (ANN). The proposed ANN uses the Levenberg–Marquardt (LM) algorithm and is trained using experimental data collected from a LabVolt wind energy test bench. The objective is to accurately estimate the instantaneous electrical power generated from the measured wind speed under different operating conditions. The proposed methodology comprises experimental data acquisition, ANN training, algorithm comparison, and model validation. The training performance of the LM algorithm was compared with that of the Resilient Backpropagation algorithm using the same dataset and network architecture. The results demonstrate that the LM algorithm provides superior convergence and prediction accuracy for the considered dataset. The selected ANN model achieved an MSE of 0.240601, an RMSE of 0.490511, an MAE of 0.207092, and a coefficient of determination of (R² = 0.999964). These results demonstrate an excellent agreement between the measured and predicted power values. The proposed ANN-based approach provides an accurate and computationally efficient solution for real-time wind power estimation and shows strong potential for integration into intelligent energy management systems and digital twin frameworks for wind energy conversion systems.

This work proposes a real-time estimation approach for the power produced by a direct current wind power system, based on an artificial neural network (ANN). The latter uses the Levenberg–Marquardt training algorithm. The model is trained using experimental data from a LabVolt wind test bench and can predict instantaneous power from measured operating variables, taking into account load variations and simulated wind conditions. The methodology includes the collection of experimental data, training of the neural network, and validation of the model under different operating conditions. The ANN model demonstrated excellent predictive performance. For current prediction, the MSE, RMSE, MAE, and R² values were 2.8271e−5, 0.0053, 0.0031, and 1.0000, respectively. For power forecasting, the corresponding values were 0.16245, 0.4030, 0.1885, and 1.0000, respectively, indicating near-perfect agreement between the forecast data and the measured data.

Given the decline in fossil energy reserves and the need for less pollution, achieving carbon zero is challenging in major industrial sectors. However, the emergence of large-scale hydrogen production systems powered by renewable energy sources offers an achievable option for carbon neutrality in specific applications. When combined with energy storage systems, static power converters are crucial in these production systems. This paper offers a comprehensive review of various power converter topologies, focusing on AC– and DC–bus architectures that interface battery storage units, electrolyzers, and fuel cells. The evaluation of DC/AC, AC/DC, and DC/DC converter topologies, considering cost, energy efficiency, control complexity, power level suitability, and power quality, represents a significant advancement in the field. Furthermore, the subsequent exploration of battery aging behavioral modeling, characterization methods, and real-time parameter estimation of the battery’s equivalent electrical circuit model enhances our understanding of these systems. Large-scale hydrogen production systems most often use an AC–bus architecture. However, DC–bus configuration offers advantages over AC–bus architecture, including high efficiency, simpler energy management, and lower system costs. In addition, MVDC or HVDC DC/DC converters, including isolated and non-isolated designs based on multiple cascaded DABs and MMC-type topologies, have also been studied to adapt the DC–bus to loads. Finally, this work summarizes several battery energy storage projects in the European Union, specifically supporting the large-scale integration of renewable energy sources. It also provides recommendations, discussion results, and future research perspectives from this study.

This paper proposes the expressions for the motor airgap torque harmonics induced by a cascaded H-bridge inverter operating with failed cells. These variable frequency drive systems (VFDs), are widely used in oil and gas applications, where a torsional vibration evaluation is a critical challenge for field engineers. This paper proposes mathematical expressions that are crucial for an accurate torsional analysis during the design stage of VFDs, as required by international standards such as API 617, API 672, etc. By accurately reconstructing the electromagnetic torque from the stator voltages and currents in the (αβ0) reference frame, the obtained expressions enable the precise prediction of the exact locations of torque harmonics induced by the inverter under various real-world operating conditions, without the need for installed torque sensors. The neutral-shifted and peak-reduction fault-tolerant control techniques are commonly adopted under faulty operation of these VFDs. However, their effects on the pulsating torques harmonics in machine air-gap remain uncovered. This paper fulfils this gap by conducting a detailed evaluation of spectral characteristics of these fault-tolerant methods. The theoretical analyses are supported by MATLAB/Simulink 2024 based offline simulation and Typhoon based virtual real-time simulation results performed on a (4.16 kV and 7 MW) vector-controlled induction motor fed by a 7-level cascaded H-bridge inverter. According to the theoretical analyses- and simulation results, the Neutral-shifted and Peak-reduction approaches rebalance the motor input line-to-line voltages in the event of an inverter’s failed cells but, in contrast to the normal mode the carrier, all the triplen harmonics are no longer suppressed in the differential voltage and current spectra due to inequal magnitudes in the phase voltages. These additional current harmonics induce extra airgap torque components that can excite the lowly damped eigenmodes of the mechanical shaft found in the oil and gas applications and shut down the power conversion system due torsional vibrations.

A cascaded H-bridge multilevel converter topology is the ultimate solution for energy conversion in various industrial applications due to its exceptional features, such as high modularity and fault-tolerant capability. However, two circumstances can lead to unbalanced operation of the inverter, potentially causing a decrease in its reliability and survivability: unequal DC voltage sources and faulty cells. In recent decades, scientists and engineers have conducted intensive research and meaningful studies to propose control solutions capable of maintaining the stable and continuous operation of the inverter under these operational concerns. Typically, each challenge is addressed separately using a distinct compensation control scheme in the existing literature. The paper aims to offer a comprehensive review of the existing compensation control schemes appropriate for CHBMIs operating under unbalanced conditions. It overviews the most popular control schemes and summarizes their usefulness in such scenarios. The theoretical foundations of each control scheme are presented and discussed, including their operating principles, implementation schemes, advantages, and disadvantages. The paper concludes with suggested future trends that require further research for CHBMIs’ continued growth and adoption in various industrial applications.

To achieve a more ecologically friendly energy transition by the year 2050 under the European “green” accord, hydrogen has recently gained significant scientific interest due to its efficiency as an energy carrier. This paper focuses on large-scale hydrogen production systems based on marine renewable-energy-based wind turbines and tidal turbines. The paper reviews the different technologies of hydrogen production using water electrolyzers, energy storage unit base hydrogen vectors, and fuel cells (FC). The focus is on large-scale hydrogen production systems using marine renewable energies. This study compares electrolyzers, energy storage units, and FC technologies, with the main factors considered being cost, sustainability, and efficiency. Furthermore, a review of aging models of electrolyzers and FCs based on electrical circuit models is drawn from the literature and presented, including characterization methods of the model components and the parameters extraction methods, using a dynamic current profile. In addition, industrial projects for producing hydrogen from renewable energies that have already been completed or are now in progress are examined. The paper is concluded through a summary of recent hydrogen production and energy storage advances, as well as some applications. Perspectives on enhancing the sustainability and efficiency of hydrogen production systems are also proposed and discussed. This paper provides a review of behavioral aging models of electrolyzers and FCs when integrated into hydrogen production systems, as this is crucial for their successful deployment in an ever-changing energy context. We also review the EU’s potential for renewable energy analysis. In summary, this study provides valuable information for research and industry stakeholders aiming to promote a sustainable and environmentally friendly energy transition.

This paper proposed a simplified modeling approach for a power quality (PQ) assessment of Electric Submersible Pumps (ESP) systems supplied by the two-level, the neutral-point-clamped three-level, and the cascaded H-bridge (CHB) multilevel inverter VFD topologies. The VFD switching function models and their analytical expressions are proposed to understand how they can create high-frequency components that might excite the resonance mode in a transmission cable or a rotating shaft system. Voltage, current, and motor airgap torque harmonics induced by each VFD topology in a balanced operation mode are derived and correlated to the PWM carrier and motor operating frequencies. The motor airgap harmonics are calculated based on Concordia’s transformation of voltages and currents in αβ-plan. These harmonic components are represented in the form of Campbell diagrams. An analysis of harmonics under unbalanced conditions was also conducted in a CHB VFD topology-powered ESP system with failed and bypassed cells. The investigated modulation technique is a neutral-shift PWM method that enables the system to operate balanced line-line voltages even if the line-neutral voltages are unbalanced. The effects of modifying the electrical spectrum using the neutral-shift PWM method on electrical and mechanical spectra are analyzed. The results of the Matlab/Simulink-based simulation show that the proposed full ESP system model is highly accurate in both normal and failure modes. The results are consistent with theoretical predictions and are graphically shown in the time and frequency domains for easy analysis. Hybrid experimental–numerical results on a reduced-scale laboratory setup are also discussed to confirm the correctness of the suggested developments.

Power generation from Renewable Energy Sources (RESs) is unpredictable due to climate or weather changes. Therefore, more control strategies are required to maintain the proper power supply in the entire microgrid. This paper presents a simulation scheme utilizing a solar system instanced by Photovoltaic (PV) panels coupled to the grid, loads, and an energy storage device. At first, modeling the PV panels cell and their operation were analyzed. The synthesis of the adaptive notch filter was designed to compensate for the input currents. The power converter’s/inverter’s efficiency and control facility allowed us to link the energy storage system with an electrical grid. Several simulations were accomplished consistently with nonlinear control techniques for the simple inverter, multi-variable filter, notch filter, and without a filter. Finally, the performances of the nonlinear controller with various filters were carried out to regulate the DC bus of the proposed grid. The advantage of these controllers is compensating the reactive power and harmonic currents to obtain a disturbance-free power network. The overall installations and simulations were established using the Matlab/Simulink software.

In this paper, power-sharing management control on an AC islanded microgrid is investigated to achieve accurate reactive power sharing. The droop control method is primarily used to manage the active and reactive power sharing among the DGs in the microgrid. However, the line impedance mismatch causes unbalanced reactive power sharing. As a solution a consensus-based adaptive virtual impedance controller is proposed, where the consensus algorithm is used to set the reactive power mismatch; then a virtual impedance correction term is generated through a proportional-integral controller to eliminate the line impedance mismatch. Thus, reactive power sharing is achieved without knowledge of the line impedances or using a central controller. Moreover, the consensus algorithm is used to restore the AC bus voltage to the nominal value by estimating the DGs average voltage using neighbor communication to compensate for the decreased magnitude of the voltage reference. Matlab/Simulink is used to validate the accuracy of reactive power sharing and voltage restauration achievement of the proposed solution through simulation of different scenarios. In addition, a dSPACE DS1104 is used within a developed experimental testbench based on two parallel DGs to validate the effectiveness of the proposed solution in the real world.