Search Results (434)

Enhancing the resilience of renewable energy systems in ultra-weak grids is crucial for promoting sustainable energy adoption and ensuring a reliable power supply during disturbances. Ultra-weak grids characterized by a very low Short-Circuit Ratio, less than 2, and high grid impedance significantly impair voltage and frequency stability, imposing challenging conditions for Inverter-Based Resources. To address these challenges, this paper considers a 110 KVA, three-phase, two-level Voltage Source Converter, interfacing a 700 V DC link to a 415 V AC ultra-weak grid. X/R = 1 is controlled using Sinusoidal Pulse Width Modulation, where the Grid-Connected Converter operates in Grid-Forming Mode to maintain voltage and frequency stability under a steady state. During symmetrical and asymmetrical faults, the converter transitions to Grid-Following mode with current control to safely limit fault currents and protect the system integrity. After fault clearance, the system seamlessly reverts to Grid-Forming Mode to resume voltage regulation. This paper proposes an improved control strategy that integrates voltage feedforward reactive power support and virtual capacitor-based virtual inertia using Active Disturbance Rejection Control, a robust, model-independent controller, which rapidly rejects disturbances by regulating d and q-axes currents. To test the practicality of the proposed system, real-time implementation is carried out using the OPAL-RT OP4610 platform, and the results are experimentally validated. The results demonstrate improved fault current limitation and enhanced DC link voltage stability compared to a conventional PI controller, validating the system’s robust Fault Ride-Through performance under ultra-weak grid conditions. Full article

Multi-channel LED drivers are crucial for high-power lighting applications. Maintaining a constant average forward current is essential for stable LED luminous intensity, necessitating drivers capable of consistent current delivery across wide operating ranges. Meanwhile, achieving precise current sharing among channels without incurring high costs and system complexity is a significant challenge. Leveraging the constant-current characteristics of the LCL-T network, this paper presents a multi-channel DC/DC LED driver comprising a full-bridge inverter, a transformer, and a passive resonant rectifier. The driver generates a high-frequency AC bus with series-connected diode rectifiers, a structure that guarantees excellent current sharing among all output channels using only a single control loop. Fully considering the impact of higher harmonics, this paper derives an exact solution for the output current. A step-by-step parameter design methodology ensures soft switching and enhanced switch utilization. Finally, experimental verification was conducted using a prototype with five channels and 200 W, confirming the correctness and accuracy of the theoretical analysis. The experimental results showed that within a wide input voltage range of 380 V to 420 V, the driver was able to provide a stable current of 700 mA to each channel, and the system could achieve a peak efficiency of up to 94.4%. Full article

This article presents proposals to increase the efficiencies of energy conversion systems from renewable sources using a soft-switching technique in three-phase voltage source inverters. The first part of this article briefly presents basic systems for generating energy from renewable sources. Special attention is paid to both photovoltaic and wind power plants. The next section describes the voltage source inverter with the soft-switching system of transistors, which is resistant to disturbances in the control systems of inverters. Laboratory tests on cooperation between the voltage source inverter and the AC grid are carried out for two cases, when energy is transmitted from the DC circuit to the AC grid and vice versa. In the final part, the efficiencies of energy conversion systems operating under the voltage source inverter with the soft-switching technique are compared with those of an inverter using hard switching of transistors. A comparison is made for energy conversion systems with a rated power of 100 kW and 1 MW. Full article

Fuel cells (FCs) are widely used in various applications such as transportation, vehicles, and energy storage, as well as in commercial and residential buildings. The FC is connected to the grid via an inverter, which converts DC power to AC power for integration with the AC grid. Thus, it is essential to adjust the gain of the inverter’s controllers to improve FC performance and the quality of the power generated by the FCs. In this work, a fractional-order PID (FOPID) controller is used to control an inverter where the FOPID’s gain settings are determined optimally to improve the performance of the current controller of the solid-oxide fuel cell (SOFC). The optimal parameters of the FOPID are obtained using a newly developed and efficient algorithm called beluga whale optimization (BWO). To highlight the efficiency of the proposed optimization approach, the obtained results are compared with particle swarm optimization (PSO) and the conventional active power controller (APC). The findings of this paper demonstrate that the SOFC achieves significantly superior performance when the FOPID controller is optimally tuned using BWO across all performance metrics related to the FC inverter. PSO also yields good results, ensuring smooth system operation and good performance. Based on the results, the output current from the SOFC using the BWO and PSO algorithms aligns well with the reference current, whereas the APC exhibits poor performance in tracking reference current changes in two cases. Specifically, the APC introduces a delay of approximately one second (0.5 to 0.6 s), resulting in poor control performance. This delay causes the system to deviate from the reference current control (RCC) by 10%, leading to poor performance. However, the proposed optimization algorithms effectively resolve this issue, offering a robust solution for enhanced current control. Full article

Dual Maximum Power Point Tracking (MPPT) inverters are essential in residential and small commercial solar power systems, optimizing power extraction from two independent solar panel arrays to enhance efficiency and energy harvesting. On the other hand, the Three-Level T-Type Voltage Source Inverter (3L T-Type VSI) is known for its reduced switching losses, improved harmonic distortion, and reduced part count in comparison to other three-level topologies. In this paper, a novel architecture is proposed to integrate the dual MPPT structure directly to each DC-side split capacitor of the 3L T-Type VSI, taking advantage of the intrinsic characteristics of the inverter’s topology. Further performance enhancement is achieved by integrating a classical MPPT strategy to the control framework to make it feasible for a real-case grid integration. The combination of these methods ensures faster and stable tracking under dynamic irradiance conditions. Considering that strategies dedicated to balancing the DC-link capacitor’s voltage slightly affect the AC-side current waveform, an enhanced sliding mode control (SMC) strategy tailored for dual MPPT and 3L T-Type VSI is deployed, combining the simplicity of conventional PI controllers used in the independent MPPT-based DC-DC converters with the superior robustness and dynamic performance of SMC. Real-time results obtained using the OPAL-RT Hardware-in-the-Loop platform validated the performance of the proposed control strategy under realistic test scenarios. The current THD was maintained below 4.8% even under highly distorted grid conditions, and the controller achieved a steady state within approximately 15 ms following perturbations in the DC-link voltage, sudden irradiance variations, and voltage sags and swells. Additionally, the power factor remained unitary, enhancing power transfer from the renewable source to the grid. The proposed system was able to achieve efficient power extraction while maintaining high power quality (PQ) standards for the output, positioning it as a practical and flexible solution for advanced solar PV systems. Full article

The need for electrical energy is dramatically increasing, pushing researchers and industrial communities towards the development and improvement of microgrids (MGs). It also encourages the use of renewable energies to benefit from available sources. Thereby, the implementation of a photovoltaic (PV) system with a hybrid energy storage system (HESS) can create a standalone MG. This paper presents an MG that uses photovoltaic energy as a principal source. An HESS is required, combining batteries and supercapacitors. This MG responds “insure” both alternating current (AC) and direct current (DC) loads. The batteries and supercapacitors have separate parallel connections to the DC bus through bidirectional converters. The DC loads are directly connected to the DC bus where the AC loads use a DC-AC inverter. A control strategy is implemented to manage the fluctuation of solar irradiation and the load variation. This strategy was implemented with a new logic control based on Boolean analysis. The logic analysis was implemented for analyzing binary data by using Boolean functions (‘0’ or ‘1’). The methodology presented in this paper reduces the stress and the faults of analyzing a flowchart and does not require a large concentration. It is used in this paper in order to simplify the control of the EMS. It permits the flowchart to be translated to a real application. This analysis is based on logic functions: “Or” corresponds to the addition and “And” corresponds to the multiplication. The simulation tests were executed at T_au  =  6 s of the low-pass filter and conducted in 60 s. The DC bus voltage was 400 V. It demonstrates that the proposed management strategy can respond to the AC and DC loads. Full article

This paper proposes a novel three-phase two-level DC-AC inverter with significantly reduced common-mode voltage. The proposed inverter combines a conventional three-phase H7 configuration with a voltage multiplier network, effectively doubling the DC-link voltage relative to the input. Compared to existing solutions, the topology achieves a remarkably low common-mode voltage, limited to only 16.6% of the DC-link voltage. Additionally, the voltage stress across the additional switches remains at half of the DC-link voltage. The paper details the operating principles, mathematical formulation, and circuit-level analysis of the proposed inverter. Simulation results are provided to validate its performance. Furthermore, a hardware prototype has been implemented using a DSP TMS320F28379D microcontroller manufactured by Texas Instruments, headquartered in Dallas, TX, USA in conjunction with an Altera Cyclone® IV EP4CE22F17C6N FPGA-based digital control platform manufactured by Intel Corporation, headquarters in Santa Clara, CA, USA. Experimental results are presented to confirm the effectiveness and feasibility of the proposed design. Full article

Power systems need to meet the ever-increasing demand for higher quality and reliability of electricity in distribution systems while remaining sustainable, secure, and economical. The globe is moving toward using renewable energy sources to provide electricity. An evaluation of the influence of artificial intelligence (AI) on the accomplishment of SDG7 (affordable and clean energy) is necessary in light of AI’s development and expanding impact across numerous sectors. Microgrids are gaining popularity due to their ability to facilitate distributed energy resources (DERs) and form critical client-centered integrated energy coordination. However, it is a difficult task to integrate, coordinate, and control multiple DERs while also managing the energy transition in this environment. To achieve low operational costs and high reliability, inverter control is critical in distributed generation (DG) microgrids, and the application of artificial neural networks (ANNs) is vital. In this paper, a power management strategy (PMS) based on Inverter Control and Artificial Neural Network (ICANN) technique is proposed for the control of DC–AC microgrids with PV-Wind hybrid systems. The proposed combined control strategy aims to improve power quality enhancement. ensuring access to affordable, reliable, sustainable, and modern energy for all. Additionally, a review of the rising role and application of AI in the use of renewable energy to achieve the SDGs is performed. MATLAB/SIMULINK is used for simulations in this study. The results from the measures of the inverter control, m, VL-L, and Vph_rms, reveal that the power generated from the hybrid microgrid is reliable and its performance is capable of providing power quality enhancement in microgrids through controlling the inverter side of the system. The technique produced satisfactory results and the PV/wind hybrid microgrid system revealed stability and outstanding performance. Full article

Unlike diesel generators or energy storage systems, photovoltaic (PV) arrays lack inherent rotational inertia and have output limitations due to their operational environmental dependencies. These characteristics restrict their suitability as primary power system backbone components. This study proposes a grid-forming (GF) control strategy for PV inverters in low voltage grid (LVG) using a model predictive control (MPC) approach. The proposed method introduces a novel predictive model accounting for capacitor dynamics to precisely regulate both AC-side output voltage and DC-side voltage. Furthermore, in this paper, P-V droop control replaces the traditional frequency regulation, achieving the real-time balance of DC/AC power and seamless sharing of multiple photovoltaic power sources. By integrating a modified cost function, the controller can flexibly switch between maximum power point tracking (MPPT) mode and power reserve mode according to varying output demands. The proposed strategy can provide advanced frequency stability, MPPT accuracy, and fast dynamic response under rapidly changing solar irradiance and load conditions. Simulation and experimental tests are carried out to validate the effectiveness of the proposed strategy. Full article

This paper presents the optimal sizing of a hybrid renewable energy system (HRES) for an isolated residential building using modified smell agent optimization (mSAO). The paper introduces a time-dependent approach that adapts the selection of the original SAO control parameters as the algorithm progresses through the optimization hyperspace. This modification addresses issues of poor convergence and suboptimal search in the original algorithm. Both the modified and standard algorithms were employed to design an HRES system comprising photovoltaic panels, wind turbines, fuel cells, batteries, and hydrogen storage, all connected via a DC-bus microgrid. The components were integrated with the microgrid using DC-DC power converters and supplied a designated load through a DC-AC inverter. Multiple operational scenarios and multi-objective criteria, including techno-economic metrics such as levelized cost of energy (LCOE) and loss of power supply probability (LPSP), were evaluated. Comparative analysis demonstrated that mSAO outperforms the standard SAO and the honey badger algorithm (HBA) used for the purpose of comparison only. Our simulation results highlighted that the PV–wind turbine–battery system achieved the best economic performance. In this case, the mSAO reduced the LPSP by approximately 38.89% and 87.50% over SAO and the HBA, respectively. Similarly, the mSAO also recorded LCOE performance superiority of 4.05% and 28.44% over SAO and the HBA, respectively. These results underscore the superiority of the mSAO in solving optimization problems. Full article

In areas such as remote, rural, and mountainous regions, supplying low-voltage three-phase power has traditionally required distribution line extension and transformer installation. However, these areas often yield low electricity revenues, making cost recovery difficult for utilities. To address this challenge, this paper proposes a Single-to-Three-Phase Converter (STPC) capable of converting single-phase low-voltage input into three-phase output for use in low-voltage distribution systems. The STPC topology employs a single-phase half-bridge AC–DC stage and a three-phase full-bridge inverter stage using SiC-MOSFETs. To validate the system, simulations and experiments were conducted under various load conditions, including unbalanced, nonlinear, and motor loads. The results show that STPC maintains output stability while minimizing impact on the existing grid. The findings demonstrate STPC’s feasibility as an alternative to conventional line extension and transformer installation, with potential for application in grid-forming and low-voltage distribution current (LVDC) systems. Full article

A grid-connected converter is the interface between renewable energy power generation systems, such as solar power generation, wind power, hydropower, etc., and the power grid, responsible for the stable and efficient transmission of electric energy generated by renewable energy power generation systems to the grid. In order to realize local access for distributed photovoltaic power generation devices and energy storage devices, a composite three-port converter has the advantages of small size, low cost and high power density compared with a combined three-port converter. In view of the current problems of the existing compound three-port (AC/DC/DC) converters, such as DC and AC circulating current in current composite three-port converters and the harmonic control problem, the proposed compound three-port topology consists of a full-bridge inverter with six switching tubes, a zigzag transformer, two sets of filter inductors and two filter capacitors. Among them, the power frequency transformer adopts the zigzag connection method, which can effectively restrain the AC circulation and eliminate the DC magnetic flux of the iron core while introducing the third port. Firstly, the principle of AC/DC and DC/DC power conversion in the composite three-port topology is analyzed, which has higher efficiency than other topologies. Secondly, the topology control strategy is analyzed, and a two-loop hybrid current control method with improved current loop is proposed. When the DC-side voltage fluctuates, the DC offset of the battery can effectively improve the stability of the network side. Through the MATLAB/Simulink simulation experiment platform, the high efficiency of energy conversion and stable grid-connected operation characteristics are verified. Finally, the experiment of integrating into the power grid was carried out. Experiments were used to verify the effectiveness and feasibility of the proposed topology and strategy. The experimental results show that Total Harmonic Distortion (THD) can be controlled below 3%. Full article

The sizing of photovoltaic (PV) systems has been a concern since the 1990s, particularly with the trend of inverter undersizing as PV module prices decrease. While many studies have assessed the behavior of AC energy and economic parameters with varying Inverter Load Ratios (ILRs), they often neglect the impact of degradation on system lifetime or fail to analyze how it influences ILR selection in depth. This study examines the relationship between DC loss curves and ILRs, their evolution over time, and their effects on efficiency and Final Yield. Simulating solar resources in 27 Brazilian cities, it evaluates clipping losses and optimal ILR values ranging from 0.8 to 2.0 for 28 recent inverters. The research aims to identify the ILR that minimizes the Levelized Cost of Energy (LCOE) while maximizing Final Yield, revealing variations in optimal ILR ranges across different inverter–city combinations. The optimal ILR was between 1.1 and 1.3 for modern medium- and high-power inverters, while low-power inverters had a range of up to 1.8. The findings highlight that practical ILR considerations can overlook real-world challenges, leaving the system’s full potential untapped. Full article

This paper discusses the operation and control of a low-voltage DC (LVDC) isolated distribution network powered by distributed generation (DG) from a variable-speed wind turbine induction generator (WTIG) to supply unbalanced AC loads. The system incorporates a DC-DC storage converter to regulate network voltages and interconnect battery energy storage with the DC network. The wind turbines are equipped with a squirrel cage induction generator (IG) to connect a DC network via individual power inverters (WTIG inverters). Loads are unbalanced ACs and are interfaced using transformerless power inverters, referred to as load inverters. The DC-DC converter is equipped with a novel control strategy, utilizing a droop regulator for the DC voltage to stabilize network operation. The control system is modeled based on Clark and Park transformations and is developed for the load inverters to provide balanced AC voltage despite unbalanced load conditions. The system employs the perturbation and observation (P&O) method for maximum power point tracking (MPPT) to optimize wind energy utilization, while blade angle controllers maintain generator performance within rated power and speed limits under high wind conditions. System operation is analyzed under two scenarios: normal operation with varying wind speeds and the effects of load variations. Simulation results using PSCAD/EMTDC demonstrate that the proposed LVDC isolated distribution network (DC) achieves a stable DC bus voltage within ±5% of the nominal value, efficiently delivers balanced AC voltages with unbalanced levels below 2%, and operates with over 90% wind energy utilization during varying wind speeds, confirming LVDC network reliability and robustness. Full article

The deployment of photovoltaic single-phase inverters has been rapidly increasing worldwide. However, the performance of these systems is highly influenced by atmospheric conditions and load variations, necessitating the development of performance indices to enhance their efficiency and energy quality. In this study, four performance indices are proposed to evaluate the efficiency and energy quality of photovoltaic systems quantitatively. The entire process is analyzed, encompassing solar energy capture, DC-DC and DC-AC conversion, and filtering, to deliver maximum energy and quality to the load. Furthermore, eight system parameters are optimized using advanced techniques such as genetic algorithms, particle swarm optimization, and gray wolf optimization. These optimizations enhance the global performance of two critical stages: (1) the maximum power point tracking algorithm based on sliding mode control, which minimizes switching losses in the boost stage, and (2) the effective transfer of captured solar power to the load by optimizing the gains of a PI controller. The PI controller computes the switching triggers for the inverter stage, significantly improving the total harmonic distortion of voltage and current waveforms. Simulation results validate the proposed approach, demonstrating a marked improvement in overall system efficiency (95.8%) when compared to the incremental conductance method (−11.8%) and a baseline sliding mode control configuration (−1.14%). Full article