Search Results (493)

Photovoltaic-storage direct current (DC) flexible (PEDF) systems are susceptible to DC bus voltage disturbances, with the constant power load (CPL) characteristics further exacerbating the risk of system instability. To address these challenges, a collaborative control scheme integrating distributed consensus and demand-side response (DSR) based on a consensus protocol is proposed in this study. A fully distributed control architecture is constructed, wherein the upper layer achieves power coordination through voltage deviation of parallel DC/DC converters and neighborhood interaction, whilst the lower layer dynamically optimizes inter-unit power allocation via the DSR mechanism. Distributed state estimation (DSE) is incorporated to enhance voltage control accuracy. Simulations conducted in the MATLAB (R2022a)/Simulink environment demonstrate that the proposed strategy enables rapid stabilization of bus voltage under load step changes and photovoltaic fluctuation scenarios, with system disturbance rejection capability being effectively enhanced. The effectiveness of the approach in maintaining stable system operation and optimizing power distribution is validated. The results indicate that the voltage deviation of the PEDF system remains below 2% under compound disturbances, with the steady-state error being controlled within 2%. The proposed control strategy, through the integration of the power DSR mechanism, effectively improves the system’s anti-disturbance capability. Compared with conventional droop control methods, which typically result in voltage deviations of 3–5%, the proposed strategy achieves a reduction in voltage deviation of over 50%, demonstrating superior voltage regulation performance. Full article

The global transition towards decentralized, decarbonized energy systems worldwide must include robust methods for controlling hybrid AC/DC microgrids to integrate diverse renewables and storage technologies effectively. This paper presents a Finite Control Set–Model Predictive Control (FCS-MPC) architecture for coordinated control of a hybrid microgrid comprising photovoltaic and wind generation, along with an energy storage system and MATLAB/Simulink component-level modeling. The islanded and grid-connected modes of operation are seamlessly simulated at the component level, ensuring maximum power point tracking and stability. The method has been experimentally validated through dynamic simulations across a range of operating conditions, demonstrating good performance: PV and wind MPPT efficiency > 99%, DC-link voltage control with < 2% overshoot, AC voltage THD < 3%, and efficient grid synchronization. It is superior to conventional PID and sliding mode control in terms of dynamic response, voltage deviation (reduced compared to before), and power quality. The proposed FCS-MPC is an all-in-one solution to enhance the stability, reliability, and efficiency of modern hybrid microgrids. Full article

Hybrid AC/DC microgrids (HMGs) are increasingly recognized as a solution for the transition toward future energy systems because they can combine the efficiency of DC networks with an AC system. Despite these advantages, HMGs still have challenges in protection, cybersecurity, and reliability. Conventional protection schemes often fail due to reduced fault currents and the dominance of power electronic converters in islanded or dynamically reconfigured topologies. At the same time, IEC 61850 protocols remain vulnerable to advanced cyberattacks such as Denial of Service (DoS), false data injection (FDIA), and man-in-the-middle (MITM), posing serious threats to the stability and operational security of intelligent power networks. Previous surveys have typically examined these challenges in isolation; however, this paper provides the first integrated review of HMG protection across three complementary dimensions: traditional protection schemes, cybersecurity threats, and artificial intelligence/machine learning (AI/ML)-based approaches. By analyzing more than 100 studies published between 2012 and 2024, we show that AI/ML methods in simulation environments can achieve detection accuracies of 95–98% with response times under 10 ms, while these values are case-specific and depend on the evaluation setting such as network scale, sampling configuration, noise levels, inverter control mode, and whether results are obtained in simulation, hardware in loop (HIL)/real-time digital simulator (RTDS), or field conditions. Nevertheless, the absence of standardized datasets and limited field validation remain key barriers to industrial adoption. Likewise, existing cybersecurity frameworks provide acceptable protection timing but lack resilience against emerging threats, while conventional methods underperform in clustered and islanded scenarios. Therefore, the future of HMG protection requires the integration of traditional schemes, resilient cybersecurity architectures, and explainable AI models, along with the development of benchmark datasets, hardware-in-the-loop validation, and implementation on platforms such as field-programmable gate array (FPGA) and μPMU. Full article

The global energy transition to renewable energy sources requires a rigorous assessment of the environmental impacts of all system components, including power electronics converters (PECs), which play a critical role in adapting generated energy to grid and load requirements. This paper presents a comprehensive comparative assessment of conventional PECs used in renewable energy systems, with a focus on DC-AC, DC-DC, and AC-DC converters. The study combines life cycle assessment (LCA) with the Circular Energy Sustainability Index (CESI) to evaluate both environmental performance and material circularity. The LCA is conducted using a functional unit defined as a representative converter, within consistent system boundaries that encompass material extraction, manufacturing, and end-of-life stages. This approach enables comparability among converter topologies but introduces limitations related to the exclusion of application-specific design optimizations, such as maximum efficiency, spatial constraints, and thermal management. CESI is subsequently applied as a decision-support tool to rank converter technologies according to sustainability and circularity criteria. The results reveal substantial differences among converter types: the controlled rectifier exhibits the lowest environmental impact and the highest circularity score (95.3%), followed by the uncontrolled rectifier (69.3%), whereas the inverter shows the highest environmental burden and the lowest circularity performance (38.6%), primarily due to its higher structural complexity and the material and manufacturing intensity associated with its switching architecture. Full article

This paper presents the design, modeling and experimental validation of an on-grid photovoltaic system with self-consumption, sized for the sustainable supply of a water pumping station. The system, composed of 68 photovoltaic panels, uses an architecture based on a Boost DC-DC converter controlled by the Perturb and Observe algorithm, raising the operating voltage to a high-voltage DC bus to maximize the conversion efficiency. The study integrates dynamic performance analysis through simulations in the Simulink environment, testing the stability of the DC bus under sudden irradiance shocks, with rigorous experimental validation based on field production data. The simulation results, which indicate a peak DC power of approximately 34 kW, are confirmed by real monitoring data that records a maximum of 35 kW, the error being justified by the high efficiency of the panels and system losses. Long-term validation, carried out over three years of operation (2023–2025), demonstrates the reliability of the technical solution, with the system generating a total of 124.68 MWh. The analysis of energy flows highlights a degree of self-consumption of 60.08%, while the absence of chemical storage is compensated for by injecting the surplus of 49.78 MWh into the national grid, which is used as an energy buffer. The paper demonstrates that using the grid to balance night-time or meteorological deficits, in combination with a stabilized DC bus, represents an optimal technical-economic solution for critical pumping infrastructures, eliminating the maintenance costs of the accumulators and ensuring continuous operation. Full article

The increasing penetration of photovoltaic (PV) generation, energy storage systems, and flexible loads within modern buildings demands advanced control strategies capable of harnessing dynamic assets while maintaining grid reliability. This Perspective article presents a comprehensive overview of reinforcement learning-driven (RL-driven) control methods for DC flexible microgrids—focusing in particular on building-integrated systems that shift from AC microgrid architectures to true PV–Energy storage–DC flexible (PEDF) systems. We examine the structural evolution from traditional AC microgrids through DC microgrids to PEDF architectures, highlight core system components (PV arrays, battery storage, DC bus networks, and flexible demand interfaces), and elucidate their coupling within building clusters and urban energy networks. We then identify key challenges for RL applications in this domain—including high-dimensional state and action spaces, safety-critical constraints, sample efficiency, and real-time deployment in building energy systems—and propose future research directions, such as multi-agent deep RL, transfer learning across building portfolios, and real-time safety assurance frameworks. By synthesizing recent developments and mapping open research avenues, this work aims to guide researchers and practitioners toward robust, scalable control solutions for next-generation DC flexible microgrids. Full article

Driven by the global energy transition, the rapid expansion of photovoltaic (PV) capacity—particularly in China’s “sand-Gobi-desert” mega-bases—demands highly efficient collection technologies. DC collection, offering low losses, compactness, and high reliability, is emerging as a critical solution for large-scale integration. This paper provides a comprehensive review of PV DC step-up collection systems. First, it analyzes typical network architectures, compares AC versus DC schemes, and examines design constraints imposed by DC bus voltage levels. Second, control strategies are summarized across device, equipment, and system levels. Third, based on engineering practices in ultra-large-scale bases, key challenges regarding fault detection, efficiency optimization, economic viability, and grid code compatibility are identified alongside representative solutions. Finally, future trends in high-voltage hardware maturation, protection bottlenecks, real-time artificial intelligence, and specialized standardization are proposed. This study serves as a vital reference for the topology design and engineering standardization of PV DC collection systems. Full article

The primary objective of this study is to bridge the gap between descriptive geometry and mechanistic design by establishing a dual-domain fractal framework to analyze the internal architecture of asphalt mixtures. This research quantitatively assesses the sensitivity of volumetric indicators—namely air voids (VV), voids in mineral aggregate (VMA), and voids filled with asphalt (VFA)—by employing the coarse aggregate fractal dimension (D_c), the fine aggregate fractal dimension (D_f), and the coarse-to-fine ratio (k) through Grey Relational Analysis (GRA). The findings demonstrate that whereas D_f and k substantially influence macro-volumetric parameters, the mesoscopic void fractal dimension (D_V) remains structurally unchanged, indicating that gradation predominantly dictates void volume rather than geometric intricacy. Sensitivity rankings create a prevailing hierarchy: Process Control (Compaction) > Skeleton Regulation (D_c) > Phase Filling (Pb) > Gradation Adjustment (k, D_f). D_c is recognized as the principal regulator of VMA, while binder content (Pb) governs VFA. A “Robust Design” methodology is suggested, emphasizing D_c to stabilize the mineral framework and reduce sensitivity to construction variations. A comparative investigation reveals that the optimized gradation (OG) achieves a more stable volumetric condition and enhanced mechanical performance relative to conventional empirical gradations. Specifically, the OG group demonstrated a substantial 112% enhancement in dynamic stability (2617 times/mm compared to 1230 times/mm) and a 75% increase in average film thickness (AFT), while ensuring consistent moisture and low-temperature resistance. In conclusion, this study transforms asphalt mixture design from empirical trial-and-error to a precision-engineered methodology, providing a robust instrument for optimizing the long-term durability of pavements in extreme cold and arid environments. Full article

This paper addresses the limitations of conventional single-stage direct-control maximum power point tracking (MPPT) methods, such as the Perturb and Observe (P&O) algorithm. Fixed-step-size duty-cycle perturbations cause a trade-off between slow tracking with small oscillations and fast tracking with large oscillations, along with poor responsiveness to rapid weather variations and output voltage fluctuations. Two main contributions are presented. First, a fractional-order DC–DC boost converter (FOBC) is introduced, incorporating fractional-order dynamics to enhance system performance beyond improvements in control algorithms alone. Second, a novel indirect-control MPPT strategy based on a two-stage architecture is developed, where the P&O algorithm generates the optimal voltage reference and a fractional-order linear-quadratic-integral (FOLQI) controller—designed using a fractional-order small-signal model—regulates the PV module voltage to generate the FOBC duty cycle. Hardware-in-the-loop simulations confirm substantial performance improvements. The proposed FOLQI-based indirect-control approach with FOBC achieves a maximum MPPT efficiency of 99.26%. An alternative indirect method using a classical linear-quadratic-integral (LQI) controller with an integer-order boost converter reaches 98.38%, while the conventional direct-control P&O method achieves only 94.21%, demonstrating the superiority of the proposed fractional-order framework. Full article

This paper examines the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for voltage regulation in a small-scale wind turbine (SWT) system intended for off-grid rural electrification in Uzbekistan. The proposed architecture consists of a wind turbine, a permanent-magnet DC generator, and a buck converter supplying a regulated 48 V DC load. While ANFIS-based control has been reported previously for wind energy systems, the novelty of this work lies in its focused application to a DC-generator-based SWT topology using real wind data from the Bukhara region, together with a rigorous quantitative comparison against a conventional PI controller under both constant- and reconstructed variable-wind conditions. Dynamic performance was evaluated through MATLAB/Simulink simulations incorporating IEC-compliant wind turbulence modeling. Quantitative results show that the ANFIS controller achieves faster settling, reduced voltage ripple, and improved disturbance rejection compared to PI control. The findings demonstrate the technical feasibility of ANFIS-based voltage regulation for decentralized DC wind energy systems, while recognizing that economic viability and environmental benefits require further system-level and experimental assessment. Full article

The growing incorporation of distributed energy resources (DER) in power distribution grids, although pivotal to the energy transition, increases operational variability and amplifies the exposure to disturbances that can compromise resilience and the continuity of service during contingencies. Addressing these challenges requires both a shift toward flexible distribution architectures and the adoption of advanced power electronics interfacing systems. In this setting, this paper proposes a resilience-oriented strategy for medium-voltage (MV) distribution systems and clustered hybrid AC/DC microgrids interfaced through solid-state transformers (SSTs). When a fault occurs along an MV feeder segment, the affected microgrids naturally transition to islanded operation. However, once their local generation and storage become insufficient to sustain autonomous operation, the proposed framework reconfigures the power routing within the cluster by activating an emergency low-voltage DC (LVDC) power path that bypasses the faulted MV section. This mechanism enables controlled power sharing between microgrids during prolonged MV outages, ensuring the supply of priority loads without oversizing SSTs or reinforcing existing infrastructure. Experimental validation on a reduced-scale SST prototype demonstrates stable grid-forming and grid-following operation. The reliability of the proposed scheme is supported by both steady-state and transient experimental results, confirming accurate voltage regulation, balanced sinusoidal waveforms, and low current tracking errors. All tests were conducted at a switching frequency of 50 kHz, highlighting the robustness of the proposed architecture under dynamic operation. Full article

Achieving a balance between rapid adaptation and robustness is a critical yet challenging objective in the design of industrial control systems. Model Reference Adaptive Control (MRAC) is a standard approach for managing system uncertainties; however, it suffers from a fundamental trade-off between adaptation speed and robustness. The high adaptation gains required for fast tracking often lead to parameter bursting or instability in the presence of noise. To resolve this issue, this paper proposes a new Dual-Loop Optimal Feedback Control (OFC) architecture applied to a Brushless DC (BLDC) motor drive. Unlike conventional methods that rely solely on tuning the adaptive mechanism, the proposed architecture introduces a parallel compensation loop designed to decouple disturbance rejection from reference tracking. This structure utilizes a Genetic Algorithm (GA) as an offline optimization engine to identify the Optimal Compensator gains that balance transient recovery with steady-state stability. Experimental validation demonstrates that the proposed Dual-Loop OFC architecture significantly outperforms traditional approaches. Specifically, it achieves an 88.99% reduction in overshoot and a 13.8% reduction in settling time compared to Conventional MRAC (CMRAC). Furthermore, it exhibits an 86.7% faster rise time compared to Self-Tuning Fuzzy PID (STFPID). These results confirm that the proposed Dual-Loop structure effectively mitigates the classic adaptability–robustness trade-off, offering a stable and high-performance solution for industrial actuators under varying operating conditions. Full article

With the gradual rise of battery-powered ships, the high-power charging demand during berthing is poised to exacerbate the peak-to-valley difference in the port grid, possibly leading to grid congestion and logistical disruption. To address this challenge, this paper proposes a bi-level coordinated scheduling scheme across both logistical operations and energy flow dispatch. Initially, by developing a refined model for the dynamic power characteristics of quay crane (QC) clusters, the surplus power capacity that can be stably released through an orderly QC operational delay is quantified. Subsequently, a hybrid AC/DC ship–shore interconnection architecture based on a smart interlinking unit (SIU) is proposed to utilize the QC peak-shaving capacity and satisfy the increasing shore power demand. In light of these, at the logistics level a coordinated scheduling of berths, QCs, and ships charging is performed with the objective of minimizing port berthing operational costs. At the energy flow level, the coordinated delay in QC clusters’ operations and SIU-enabled power dispatching are implemented for charging power support. The case studies demonstrate that, compared with the conventional independent operational mode, the proposed coordinated scheduling scheme enhances the shore power supply capability by utilizing the QC peak-shaving capability effectively. Moreover, as well as satisfying the charging demands of electric ships, the proposed scheme significantly reduces the turnaround time of ships and achieves a 39.29% reduction in port berthing operational costs. Full article

This paper presents the design, modeling and control of a flywheel actuator for mobile platform stabilization. A Lagrangian-based model couples platform mechanics with DC-motor electromechanics. Analytical calculations estimate natural frequencies, damping and actuator limits. Numerical simulations in Python 3.12 evaluate cascade and state-feedback controllers for suppressing free oscillations and rejecting external disturbances. Additional studies examine filtering to improve measurement quality and unloading strategies to avoid actuator saturation. The results validate the proposed control architecture and demonstrate its applicability to robotic and energy systems operating under dynamic loads. Full article

Microwave wireless power transfer (MWPT) technology has the advantages of long distance and high transmission efficiency; therefore, MWPT has many applications in aerospace, space solar power stations (SSPSs), and so on. The receiving and fixing subsystem is the core component for gathering and converting power and it is the main part of the system. If this step is both efficient and possible, the whole system will also be efficient and its success possible. This paper mainly introduces a systematic review of the key technologies, research status, and development trends of the receiving-end part in MWPT. High-performance rectifying devices are analyzed in detail, with the use of GaN Schottky barrier diodes (GaN SBDs), in addition to rectification circuits that have good rectification and impedance matching. Additionally, it compares the advantages and disadvantages of three power synthesis architectures, including RF synthesis, DC synthesis, and hybrid subarray synthesis, and proposes a strategy for optimizing power distribution through intelligent subarray partitioning. Finally, this paper looks at future development trends in receiving-end technology, including miniaturized monolithic microwave integrated circuits (MMICs) and efficient broadband reconfigurable rectification. The research presented herein offers a systematic technical reference and theoretical foundation for enhancing the performance of the receiving ends in microwave wireless power transfer systems. Full article