Search Results (398)

For the high-voltage AC port of power electronic transformer (HVAC-PET) with three-phase independent DC buses on the low-voltage side, a decoupling control strategy, concerning the influence of grid voltage imbalance, three-phase active-load imbalance, and high-order harmonic distortion, is proposed in this paper to simultaneously realize the functions of active power control, reactive power compensation, and active power filtering. In the outer power control loop, according to the distribution rule of decoupled average active power components in three phases, stability control for the sum of cluster average active power flows is realized by injecting positive-sequence active current, so as to control the average cluster voltage (i.e., the average of all the DC-link capacitor voltages), and by injecting negative-sequence current, the cluster average active power flows can be controlled individually to balance the three cluster voltages (i.e., the average of the DC-link capacitor voltages in each cluster). The negative-sequence reactive power component is considered to realize the reactive power compensation. In the inner current control loop, the fundamental and high-order harmonic components are uniformly controlled in the positive-sequence dq frame using the PI + VPIs (vector proportional integral) controller, and the harmonic filtering function is realized while the fundamental positive-sequence current is adjusted. Experiments performed on the 380 V/50 kVA laboratory HVAC-PET verify the effectiveness of the proposed control strategy. Full article

This paper presents an advanced energy management system (EMS) for optimizing power distribution in a battery/ultracapacitor (UC) hybrid energy storage system (HESS) for electric vehicles (EVs). The proposed EMS accounts for all energy flow scenarios within a practical driving cycle. A regenerative braking control strategy is developed to maximize kinetic energy recovery using an induction motor, efficiently distributing the recovered energy between the UC and battery. Additionally, a power flow management approach is introduced for both motoring (discharge) and braking (charge) operations via bidirectional buck–boost DC-DC converters. In discharge mode, an optimal distribution factor is dynamically adjusted to balance power delivery between the battery and UC, maximizing efficiency. During charging, a DC link voltage control mechanism prioritizes UC charging over the battery, reducing stress and enhancing energy recovery efficiency. The proposed EMS is validated through simulations and experiments, demonstrating significant improvements in vehicle acceleration, energy efficiency, and battery lifespan. Full article

The article presents a new AM (Additive Manufacturing) process development, necessary to repair parts made from Aluminum 6061 material, with T6 treatment. The laser Directed Energy Deposition (DED) and Extreme High-Speed Directed Energy Deposition (EHLA) capabilities are evaluated for repairing Al large components. To optimize the process parameters, single-track depositions were analyzed for both laser-powder DED (feed rate of 2 m/min) and EHLA (feed rate 20 m/min) for AlSi10Mg and Al6061 powders. The cross-sections of single tracks revealed the bonding characteristics and provided laser-powder DED, a suitable parameter selection for the repair. Three damage types were identified on the Al component to define the specification of the repair process and to highlight the capabilities of laser-powder DED and EHLA in repairing intricate surface scratches and dents. Our research is based on variation of the powder mass flow and beam power, studying the influence of these parameters on the weld bead geometry and bonding quality. The evaluation criteria include bonding defects, crack formation, porosity, and dilution zone depth. The bidirectional path planning strategy was applied with a fly-in and fly-out path for the hatching adjustment and acceleration distance. Samples were etched for a qualitative microstructure analysis, and the HV hardness was tested. The novelty of the paper is the new process parameters for laser-powder DED and EHLA deposition strategies to repair large Al components (6061 T6), using AlSi10Mg and Al6061 powder. Our experimental research tested the defect-free deposition and the compatibility of AlSi10Mg on the Al6061 substrate. The readers could replicate the method presented in this article to repair by laser-powder DED/EHLA large Al parts and avoid the replacement of Al components with new ones. Full article

Island microgrids are essential for the exploitation and utilization of offshore renewable energy resources. However, voltage regulation and accurate reactive power sharing remain significant technical challenges that need to be addressed. To tackle these issues, this paper proposes an algorithm that integrates a dynamic leader election (DLE) mechanism and model-free reinforcement learning (RL). The algorithm aims to address the issue of fixed leaders restricting reactive power flow between buses during heavy load variations in island microgrids, while also overcoming the challenge of obtaining model parameters such as resistance and inductance in practical microgrids. First, we establish a voltage containment control and reactive power error model for island alternating current (AC) microgrids and construct a corresponding value function based on this error model. Second, a dynamic leader election algorithm is designed to address the issue of fixed leaders restricting reactive power flow between buses due to preset voltage limits under unknown or heavy load conditions. The algorithm adaptively selects leaders based on bus load, allowing the voltage limits to adjust accordingly and regulating reactive power flow. Then, to address the difficulty of accurately acquiring parameters such as resistance and inductance in microgrid lines, a model-free reinforcement learning method is introduced. This method relies on real-time measurements of voltage and reactive power data, without requiring specific model parameters. Ultimately, simulation experiments on offshore island microgrids are conducted to validate the effectiveness of the proposed algorithm. Full article

Rail transit as a high-energy consumption field urgently requires the adoption of clean energy innovations to reduce energy consumption and accelerate the transition to new energy applications. As an energy-saving fluid machinery, the ejector exhibits significant application potential and academic value within this field. This paper reviewed the recent advances, technical challenges, research hotspots, and future development directions of ejector applications in rail transit, aiming to address gaps in existing reviews. (1) In waste heat recovery, exhaust heat is utilized for propulsion in vehicle ejector refrigeration air conditioning systems, resulting in energy consumption being reduced by 12~17%. (2) In vehicle pneumatic pressure reduction systems, the throttle valve is replaced with an ejector, leading to an output power increase of more than 13% and providing support for zero-emission new energy vehicle applications. (3) In hydrogen supply systems, hydrogen recirculation efficiency exceeding 68.5% is achieved in fuel cells using multi-nozzle ejector technology. (4) Ejector-based active flow control enables precise ± 20 N dynamic pantograph lift adjustment at 300 km/h. However, current research still faces challenges including the tendency toward subcritical mode in fixed geometry ejectors under variable operating conditions, scarcity of application data for global warming potential refrigerants, insufficient stability of hydrogen recycling under wide power output ranges, and thermodynamic irreversibility causing turbulence loss. To address these issues, future efforts should focus on developing dynamic intelligent control technology based on machine learning, designing adjustable nozzles and other structural innovations, optimizing multi-system efficiency through hybrid architectures, and investigating global warming potential refrigerants. These strategies will facilitate the evolution of ejector technology toward greater intelligence and efficiency, thereby supporting the green transformation and energy conservation objectives of rail transit. Full article

Focusing the over simplification of existing models in simulating river flow evolution process and lack of coordination of hydropower generation and export, this paper proposes a hydropower generation and export coordinated optimal operation model that, at the same time, incorporates dynamic water flow delay by finely modeling the water flow evolution process among cascade hydropower stations within a river basin. Specifically, firstly, a dynamic water flow evolution model is built based on the segmented Muskingum method. By dividing the river into sub-segments and establishing flow evolution equation for individual sub-segments, the model accurately captures the dynamic time delay of water flow. On this basis, integrating cascade hydropower systems and the transmission system, a hydropower generation and export coordinated optimal operation model is proposed. By flexibly adjusting the power export, the model balances local consumption and external transmission of hydropower, enhancing the utilization efficiency of hydropower resources and achieving high economic performance. A case study verified the accuracy of the dynamic water flow evolution model and the effectiveness of the proposed hydropower generation and export coordinated optimal operation model. Full article

Phase-shifting transformers play a crucial role in power grid stability and efficiency. They adjust phase differences between loads, improve transmission efficiency, and balance loads during large-scale power transmission and grid integration. However, traditional mechanical phase-shifting transformers use fixed-tap designs with limited taps, preventing continuous and precise adjustments. This discrete adjustment method affects control accuracy and optimal tap position selection for proper power flow. This paper proposes a hybrid open-loop and closed-loop control strategy. This strategy maintains the phase-shifting transformer at its optimal tap position, enhancing system regulation precision and control effectiveness. Full article

In this paper, we address the problem of intelligent operation of Distribution Static Synchronous Compensators (D-STATCOMs) in power distribution systems to reduce energy losses and CO₂ emissions while improving system operating conditions. In addition, we consider the entire set of constraints inherent in the operation of such networks in an environment with D-STATCOMs. To solve such a problem, we used three master–slave methodologies based on sequential programming methods. In the proposed methodologies, the master stage solves the problem of intelligent D-STATCOM operation using the continuous versions of the Monte Carlo (MC) method, the population-based genetic algorithm (PGA), and the Particle Swarm Optimizer (PSO). The slave stage, for its part, evaluates the solutions proposed by the algorithms to determine their impact on the objective functions and constraints representing the problem. This is accomplished by running an Hourly Power Flow (HPF) based on the method of successive approximations. As test scenarios, we employed the 33- and 69-node radial test systems, considering data on power demand and CO₂ emissions reported for the city of Medellín in Colombia (as documented in the literature). Furthermore, a test system was adapted in this work to the demand characteristics of a feeder located in the city of Talca in Chile. This adaptation involved adjusting the conductors and voltage limits to include a test system with variations in power demand due to seasonal changes throughout the year (spring, winter, autumn, and summer). Demand curves were obtained by analyzing data reported by the local network operator, i.e., Compañía General de Electricidad. To assess the robustness and performance of the proposed optimization approach, each scenario was simulated 100 times. The evaluation metrics included average solution quality, standard deviation, and repeatability. Across all scenarios, the PGA consistently outperformed the other methods tested. Specifically, in the 33-node system, the PGA achieved a 24.646% reduction in energy losses and a 0.9109% reduction in CO₂ emissions compared to the base case. In the 69-node system, reductions reached 26.0823% in energy losses and 0.9784% in CO₂ emissions compared to the base case. Notably, in the case of the Talca feeder—particularly during summer, the most demanding season—the PGA yielded the most significant improvements, reducing energy losses by 33.4902% and CO₂ emissions by 1.2805%. Additionally, an uncertainty analysis was conducted to validate the effectiveness and robustness of the proposed optimization methodology under realistic operating variability. A total of 100 randomized demand profiles for both active and reactive power were evaluated. The results demonstrated the scalability and consistent performance of the proposed strategy, confirming its effectiveness under diverse and practical operating conditions. Full article

This study investigates the integration of advanced optimization algorithms within energy-intensive infrastructures and industrial plants. In fact, the authors focus on the dynamic interplay between computational intelligence and operational efficiency in wastewater treatment plants (WWTPs). In this context, energy optimization is thought of as a hybrid process that emerges at the intersection of engineered systems, environmental dynamics, and operational constraints. Despite the known energy-intensive nature of WWTPs, where pumps and blowers consume over 60% of total power, current methods lack systematic, real-time adaptability under variable conditions. To address this gap, the study proposes a computational framework that combines hydraulic simulation, manufacturer-based performance mapping, and a Memetic Algorithm (MA) capable of real-time optimization. The methodology synthesizes dynamic flow allocation, auto-tuning mutation, and step-by-step improvement search into a cohesive simulation environment, applied to a representative parallel-pump system. The MA’s dual capacity to explore global configurations and refine local adjustments reflects both static and kinetic aspects of optimization: the former grounded in physical system constraints, the latter shaped by fluctuating operational demands. Experimental results across several stochastic scenarios demonstrate consistent power savings (12.13%) over conventional control strategies. By bridging simulation modeling with optimization under uncertainty, this study contributes to sustainable operations management, offering a replicable, data-driven tool for advancing energy efficiency in infrastructure systems. Full article

This study introduces a stochastic optimization framework designed to effectively manage power flows in flexible medium-voltage DC (MVDC) link systems within distribution networks (DNs). The proposed approach operates in coordination with a battery energy storage system (BESS) to enhance the overall efficiency and reliability of the power distribution. Given the inherent uncertain characteristics associated with forecasting errors in photovoltaic (PV) generation and load demand, the study employs a distributionally robust chance-constrained optimization technique to mitigate the potential operational risks. To achieve a cooperative and optimized control strategy for MVDC link systems and BESS, the proposed method incorporates a stochastic relaxation of the reliability constraints on bus voltages. By strategically adjusting the conservativeness of these constraints, the proposed framework seeks to maximize the cost-effectiveness of DN operations. The numerical simulations demonstrate that relaxing the strict reliability constraints enables the distribution system operator to optimize the electricity imports more economically, thereby improving the overall financial performance while maintaining system reliability. Through case studies, we showed that the proposed method improves the operational cost by up to 44.7% while maintaining 96.83% bus voltage reliability under PV and load power output uncertainty. Full article

In islanded microgrids with high-proportion renewable energy, the disconnection from the main grid leads to the characteristics of low inertia, weak damping, and high impedance ratio, which exacerbate the safety risks of frequency and voltage. To balance the requirements of system operation economy and frequency–voltage safety, a coordinated optimization scheduling method for frequency and voltage in islanded microgrids considering the active support of battery energy storage (BES) is proposed. First, to prevent the state of charge (SOC) of BES from exceeding the frequency regulation range due to rapid frequency adjustment, a BES frequency regulation strategy with an adaptive virtual droop control coefficient is adopted. The frequency regulation capability of BES is evaluated based on the capacity constraints of grid-connected converters, and a joint frequency and voltage regulation strategy for BES is proposed. Second, an average system frequency model and an alternating current power flow model for islanded microgrids are established. The influence of steady-state voltage fluctuations on active power frequency regulation is analyzed, and dynamic frequency safety constraints and node voltage safety constraints are constructed and incorporated into the optimization scheduling model. An optimization scheduling method for islanded microgrids that balances system operation costs and frequency–voltage safety is proposed. Finally, the IEEE 33-node system in islanded mode is used as a simulation case. Through comparative analysis of different optimization strategies, the effectiveness of the proposed method is verified. Full article

This study investigated the performance of Savonius hydrokinetic turbine blades through three-dimensional computational fluid dynamics simulations conducted at a fixed tip speed ratio of 0.87. A multi-factor experimental design was employed to construct 45 V-shaped rotor blade models, systematically examining the effects of a V-angle (30–140°) and straight-edge length (0.24 L–0.62 L) on hydrodynamic performance, where L = 25.46 mm (the baseline length of the straight edge). The results indicate that, as the V-angle and the straight-edge length vary independently, the performance of each blade first increases and then decreases. At TSR = 0.87, the maximum power coefficient (C_P) of 0.2345 is achieved by the blade with a 70° V-Angle and a straight edge length of 0.335 L. Pressure and velocity field analyses reveal that appropriate geometric adjustments can optimize the high-pressure zone on the advancing blade and suppress negative torque on the returning blade, thereby increasing net output. The influence mechanisms of the V-angle and straight-edge length variations on blade performance were further explored and summarized through a comparative analysis of the vorticity characteristics. This study established a detailed performance dataset, providing theoretical and empirical support for V-shaped rotor blade design studies and offering engineering guidance for the effective use of low-flow hydropower. Full article

To achieve efficient prediction and optimization of the energy consumption of ship central cooling systems, this paper first constructed and validated a high-precision multi-physical domain simulation model of the ship central cooling system based on fluid heat transfer principles and the physical network method. Then, simulation experiments were designed using the Box–Behnken design (BBD) method to study the effects of five key parameters—main engine power, seawater temperature, seawater pump speed, low-temperature fresh water three-way valve opening, and low-temperature fresh water flow rate—on system energy consumption. Based on the simulation data, an energy consumption prediction model was constructed using response surface methodology (RSM). This prediction model exhibited excellent goodness of fit and prediction ability (coefficient of determination R² = 0.9688, adjusted R²_adj = 0.9438, predicted R²_pred = 0.8752), with a maximum relative error of only 1.2% compared to the simulation data, confirming its high accuracy. Sensitivity analysis based on this prediction model indicated that main engine power, seawater pump speed, seawater temperature, and three-way valve opening were the dominant single factors affecting energy consumption. Further analysis revealed a significant interaction between main engine power and seawater pump speed. This interaction resulted in non-linear changes in system energy consumption, which were particularly prominent under operating conditions such as high power. This study provides an accurate prediction model and theoretical guidance on the influence patterns of key parameters for the simulation-driven design, operational optimization, and energy saving of ship central cooling systems. Full article

Fluid effects are important in films and advertisements, where their realism and aesthetic quality directly impact the visual experience. With the rapid advancement of digital technology and computer-aided design (CAD), modern visual effects are used to simulate various water-related phenomena, such as flowing water, ocean waves, and raindrops. However, creating these realistic effects is not solely dependent on advanced software and hardware; it also requires an understanding of the technical and artistic aspects of visual effects artists. In the creation process, the artist must possess a keen aesthetic sense and innovative thinking to craft stunning visual effects to overcome technological constraints. Whether depicting the grandeur of turbulent ocean scenes or the romance of gentle rain, the artist needs to transform fluid effects into expressive visual language to enhance emotional impact, aligning with the storyline and the director’s vision. The production process of fluid effects typically involves the following critical steps. First, the visual effects artist utilizes CAD-based tools, particle systems, or fluid simulation software to model the dynamic behavior of water. This process demands a solid foundation in physics and the ability to adjust parameters flexibly according to the specific needs of the scene, ensuring that the fluid motion appears natural and smooth. Next, in the rendering stage, the simulated fluid is transformed into realistic imagery, requiring significant computational power and precise handling of lighting effects. Finally, in the compositing stage, the fluid effects are seamlessly integrated with live-action footage, making the visual effects appear as though they are parts of the actual scene. In this study, the technical details of creating fluid effects using free software such as Blender were explored. How advanced CAD tools are utilized to achieve complex water effects was also elucidated. Additionally, case studies were conducted to illustrate the creative processes involved in visual effects production to understand how to seamlessly blend technology with artistry to create unforgettable visual spectacles. Full article

With the development of modern power systems, AC distribution networks face increasing demands for supply flexibility and reliability. Energy storage-based soft open points (E-SOPs), which integrate energy storage systems into the DC side of traditional SOP connecting AC distribution networks, not only maintain power flow control capabilities but also enhance system supply performance, providing a novel approach to AC distribution network fault recovery. To fully leverage the advantages of E-SOPs in handling faults in flexible interconnected AC distribution networks (FIDNs), this paper proposes an E-SOP-based FIDN islanding recovery method. First, the basic structure and control modes of SOPs for AC distribution networks are elaborated, and the E-SOP-based AC distribution network structure is analyzed. Second, with maximizing total load recovery as the objective function, the constraints of E-SOPs are comprehensively considered, and recovery priorities are established based on load importance classification. Then, a multi-dimensional improvement of the dung beetle optimizer (DBO) algorithm is implemented through Logistic chaotic mapping, adaptive parameter adjustment, elite learning mechanisms, and local search strategies, resulting in an efficient solution for AC distribution network power supply restoration. Finally, the proposed FIDN islanding partitioning and fault recovery methods are validated on a double-ended AC distribution network structure. Simulation results demonstrate that the improved DBO (IDBO) algorithm exhibits a superior optimization performance and the proposed method effectively enhances the load recovery capability of AC distribution networks, significantly improving the self-healing ability and operational reliability of AC distribution systems. Full article