Continuous Power Research Articles

A waveguide branch-line crossover based on metal gratings.

A waveguide branch-line crossover with broad bandwidth is designed for beam-forming networks in millimeter wavebands. To realize the power coupling between two parallel branch lines, a substrate with metal gratings patched replaces the common E-plane waveguide wall. Compared with the traditional crossover with coupling vias, the metal gratings achieve continuous and efficient power coupling, endowing the proposed crossover with advantages in compactness and broad bandwidth. A simulation-assisted transfer-matrix approach is used to rapidly estimate and optimize the parameters of the crossover. The coupling obtained from the simulation is over -0.5 dB from 32.1 to 39.1GHz, with isolation greater than 15 dB and reflection less than -20 dB. A prototype is fabricated, and the measurement results agree with the simulation results, demonstrating that the proposed crossover is a promising candidate for millimeter-wave beamforming networks.

Power control of an autonomous wind energy conversion system based on a permanent magnet synchronous generator with integrated pumping storage

Wind energy plays a crucial role as a renewable source for electricity generation, especially in remote or isolated regions without access to the main power grid. The intermittent characteristics of wind energy make it essential to incorporate energy storage solutions to guarantee a consistent power supply. This study introduces the design, modeling, and control mechanisms of a self-sufficient wind energy conversion system (WECS) that utilizes a Permanent magnet synchronous generator (PMSG) in conjunction with a Water pumping storage station (WPS). The system employs Optimal torque control (OTC) to maximize power extraction from the wind turbine, achieving a peak power coefficient (Cp) of 0.43. A vector control strategy is applied to the PMSG, maintaining the DC bus voltage at a regulated 465 V for stable system operation. The integrated WPS operates in both motor and generator modes, depending on the excess or shortfall of generated wind energy relative to load demand. In generator mode, the WPS supplements power when wind speeds are insufficient, while in motor mode, it stores excess energy by pumping water to an upper reservoir. Simulation results, conducted in MATLAB/Simulink, show that the system efficiently tracks maximum power points and regulates key parameters. For instance, the PMSG successfully maintains the reference quadrature current, achieving optimal torque and power output. The system’s response under varying wind speeds, with an average wind speed of 8 m/s, demonstrates that the generator speed closely follows turbine speed without a gearbox, leading to efficient power conversion. The results confirm the flexibility and robustness of the control strategies, ensuring continuous power delivery to the load. This makes the system a feasible solution for isolated, off-grid applications, contributing to advancements in renewable energy technologies and autonomous power generation systems.

Real-Time Short-Circuit Current Calculation in Electrical Distribution Systems Considering the Uncertainty of Renewable Resources and Electricity Loads

Existing short-circuit calculation methods for distribution networks with renewable energy sources ignore the fluctuation of renewable sources and cannot reflect the impact of renewable sources and load changes on short-circuit current in real time at all times of the day and in extreme scenarios. A real-time short-circuit current calculation method is proposed to take into account the stochastic nature of distributed generators (DGs) and electricity loads. Firstly, the continuous power flow of distribution networks is calculated based on the real-time renewable energy output and electricity loads. And then, equivalent DG models with low-voltage ride through (LVRT) strategies are substituted into the iterative calculation method to obtain the short-circuit currents of all main branches in real time. The effects of different renewable energy output curves on distribution network short-circuit currents are quantitatively analyzed during the fluctuation in distributed power output, which can provide an important basis for the setting calculation of distribution network relay protection and the study of new principles of protection.

Emergency Power Supply Management Strategy for Low-Performance Distribution Networks Based on Mobile Multi-Port Interconnection Equipment

Deploying emergency vehicles has become a key guarantee for power supply in post-disaster distribution networks on account of their flexibility, maneuverability, safety, and reliability. However, due to limitations in configuration, the continuous power supply capacity of existing electrical vehicles (EVs) is insufficient, making it difficult to meet the needs of energy transfer and flow regulation in post-disaster distribution networks. Therefore, in this study, we comprehensively considered the energy time-shift characteristics of EVs and the flexible control function of soft open points (SOPs), integrated their advantages, and designed an emergency vehicle with SOP (EV-SOP) and its management strategy for distribution network line faults. Firstly, we present the EV-SOP architecture and its mathematical model. Then, aiming to minimize the economic losses caused by power loss during line faults, an EV-SOP emergency management strategy based on data collection, scheduling judgment, and optimal modeling techniques is proposed. Finally, by taking the case study of an IEEE33-node distribution network with contact switches as an example, we validate the effectiveness and superiority of the EV-SOP and its emergency management strategy compared with traditional energy storage emergency vehicles.

Amidination of ligands for chemical and field-effect passivation stabilizes perovskite solar cells.

Surface passivation has driven the rapid increase in the power conversion efficiency (PCE) of perovskite solar cells (PSCs). However, state-of-the-art surface passivation techniques rely on ammonium ligands that suffer deprotonation under light and thermal stress. We developed a library of amidinium ligands, of interest for their resonance effect-enhanced N-H bonds that may resist deprotonation, to increase the thermal stability of passivation layers on perovskite surfaces. This strategy resulted in a >10-fold reduction in the ligand deprotonation equilibrium constant and a twofold increase in the maintenance of photoluminescence quantum yield after aging at 85°C under illumination in air. Implementing this approach, we achieved a certified quasi-steady-state PCE of 26.3% for inverted PSCs; and we report retention of ≥90% PCE after 1100 hours of continuous 1-sun maximum power point operation at 85°C.

Warranty-driven reliability analysis: a stochastic model for continuous solar power supply system with two photovoltaic cells and an inverter

Warranty-driven reliability analysis: a stochastic model for continuous solar power supply system with two photovoltaic cells and an inverter

Self-powered temperature pressure sensing arrays with stepped microcone structure and Bi2Te3-based films for deep learning-assisted object recognition

Flexible temperature-pressure bimodal sensing arrays can detect multiple types of information, including force and heat, making them crucial for applications such as object classification, human-machine interaction, and artificial intelligence. However, current sensors primarily focus on single-parameter and single-point measurements, while lacking a continuous and stable power supply. This study developed flexible, self-powered temperature-pressure sensing arrays by integrating a stepped microcone structure with thermoelectric materials. This stepped distribution microstructure design enabled effective pressure measurements across a wide range, with high sensitivity and fast response. Temperature-independent measurements were achieved synchronously over a wide temperature range (35–173 °C) by incorporating high-performance Bi2Te3-based thermoelectric films. These temperature and pressure sensing units can discern temperature and pressure stimuli without mutual interference. Furthermore, with the assistance of deep learning, these bimodal sensing arrays performed spatial mapping of temperature and pressure simultaneously, demonstrating their ability to identify different types of objects with an accuracy exceeding 98 %. Therefore, this study shows promise for advancing human-machine interaction, artificial intelligence, and self-powered electronic skins.

Synergistic Modulation of Orientation and Steric Hindrance Induced by Alkyl Chain Length in Ammonium Salt Passivator Toward High‐performance Inverted Perovskite Solar Cells and Modules

AbstractOrganic ammonium salts are extensively utilized for passivating surface defects in perovskite films to mitigate trap‐assisted nonradiative recombination. However, the influence of alkyl chain length on the molecular orientation and spatial steric hindrance of ammonium salt remains underexplored, hindering advancements in more effective passivators. Here, a series of organic ammonium salts is reported with varying alkyl chain lengths to passivate surface defects and optimize band alignment. It is revealed that long alkyl chains promote parallel molecular orientation on the perovskite surface, thereby reinforcing interaction with surface defects, whereas excessive chain length introduces steric hindrance, weakening anion‐perovskite interactions. Nonylammonium acetate (NAAc) with optimal chain length achieves the ideal balance between chemical interactions, resulting in superior passivation. Through NAAc passivation, high‐performance inverted perovskite solar cells (PSCs) and modules are achieved, with power conversion efficiencies (PCE) of 25.79% (certified 25.12%) and 19.62%, respectively. This marks a record PCE for inverted PSCs utilizing vacuum flash technology in ambient conditions. Additionally, the NAAc‐passivated devices retain 91% of their initial PCE after 1200 h of continuous maximum power point operation. This work offers new insights into the interplay between molecular orientation and steric hindrance, advancing the design of high‐performance PSCs.

Solar-based nighttime electric power generator based on radiative cooling

This study focuses on developing and investigating a hybrid nighttime electric power generator that integrates photovoltaic (PV) cells with thermoelectric generators (TEG) to provide continuous power generation during both day and night. During the day, PV cells efficiently capture solar energy and convert it into electricity. At night, radiative cooling lowers the surface temperature of the PV panels, creating a temperature differential between the ambient air and the cooled panels. This temperature difference drives the TEG modules, which generate electricity based on the Seebeck effect. The experimental results reveal that the size and configuration of TEG modules significantly affect power output. A single 3 cm×3 cm TEG produced up to 0.9 mW of power with a 55°C temperature difference, while a larger 4 cm×4 cm TEG generated up to 3.8 mW. Furthermore, connecting two 4 cm×4 cm TEGs in series resulted in a peak output of 7.7 mW, nearly double that of the single TEG setup. This hybrid system demonstrates potential for moderate nighttime power generation, suitable for small household applications such as LED lights, laptops, phone chargers, and wireless routers. The ability to generate power both during the day and night enhances the efficiency and reliability of renewable energy systems, offering a continuous, sustainable power supply that mitigates the limitations of conventional solar panels. The results underscore the feasibility of scaling up TEG modules to achieve higher power outputs, making this system a promising solution for addressing nighttime energy demands in off-grid and low-power applications.

Multirod Pumping Approach with Fresnel Lens and Ce:Nd:YAG Media for Enhancing the Solar Laser Efficiency

A multirod Ce:Nd:YAG solar laser approach, using a Fresnel lens as a primary concentrator, is here proposed with the aim of considerably increasing the efficiency of solar-pumped lasers. Fresnel lenses are cost-effective, rendering solar lasers more economically competitive. In this work, solar-pumped radiation collected and concentrated using the Fresnel lens is received by a secondary three-dimensional compound parabolic concentrator which transmits and funnels the light toward the Ce:Nd:YAG laser rods within a water-cooled tertiary conical concentrator that enables efficient multipass pumping of the rods. To explore the full potential of the proposed approach, the performance of various multirod configurations is numerically evaluated. Through this study, configurations with three and seven Ce:Nd:YAG rods are identified as being the most efficient. A maximum continuous wave total laser power of 122.8 W is reached with the three-rod configuration, marking the highest value from a Ce:Nd:YAG solar laser, leading to solar-to-laser conversion and collection efficiencies of 7.31% and 69.50 W/m2, respectively. These results represent enhancements of 1.88 times and 1.79 times, respectively, over the previous experimental records from a Ce:Nd:YAG/YAG single-rod solar laser with a Fresnel lens. Furthermore, the above results are also 1.58 times and 1.68 times, respectively, greater than those associated with the most effective three-rod Ce:Nd:YAG solar laser utilizing a parabolic mirror as the main concentrator. The present study also shows the great usefulness of the simultaneous pumping of multiple laser rods in terms of reducing the thermal stress effects in active media, being the seven-rod configuration the one that offered the best compromise between maximum efficiency and thermal performance. This is crucial for the applicability of this sustainable technology, especially if we wish to scale our system to higher power laser levels.

Performance Enhancement of Thermoelectric Generator‐Radiative Cooling System With Thermal and Electrical Energy Storage

ABSTRACTA thermoelectric generator (TEG) converts thermal energy into electrical energy when temperature gradients are created across its two surfaces. Integrating the TEG with a phase change material (PCM) and radiative cooling (RC) can increase the temperature gradient across its two surfaces. In this study, a two‐layer RC paint has been developed and applied to the cold side of a TEG, and its performance was compared with TEG‐white paint and TEG‐no paint. The RC lowers the temperature of the cold side by 3.5°C and 4.7°C compared to TEGs with white paint and no paint, respectively. Integrating PCM with TEG–RC ensured a high electrical output, enabling continuous power for a typical weather sensor. The PCM–TEG–RC generated 2.7and 0.61 mW during summer and winter days in Istanbul, and nighttime outputs of 0.302 W and 0.395 mW, respectively. Despite similar costs, the electrical performance of TEG–RC was nearly double that of the TEG‐white paint. It has also been determined that a storage capacitor with a value of 0.5 F can provide 24‐h power backup to the typical weather sensor.

A Novel development of soft computing based hybrid power point tracking controllers for hydrogen vehicle application with new wide source DC-DC converter

From the present power generation scenario, most of the power production companies are focusing on renewable energy systems because their merits are easy to install, more reliable power sources, free from atmospheric pollution, and better adaptable to all weather conditions. In this article, a Polymer Electrolyte Membrane Fuel Cell (PEMFC) module is selected in the first objective to produce constant and continuous power to the hydrogen-based electrical vehicle systems. This fuel module provides fast power production and gives good energy density. However, the demerits of this module are more current production and low-level voltage generation. A new single-switch DC-DC circuit is introduced in the second objective of this work for optimizing the current levels of the fuel module thereby reducing the source power loss of the proposed system. Here, another problem of the fuel module is nonlinear power production which is linearized by proposing the Cuckoo Search Optimization (CSO)-based Adaptive Network-based Fuzzy Inference System (ANFIS) in the third objective to extract the maximum voltage from the fuel module. The merits of this introduced Maximum Power Point Tracking (MPPT) Controller are better tracking speed, low-level disturbances in the consumer load power, high robustness, more sustainability, and easy operation. The entire proposed system is investigated by selecting the MATLAB Simulink tool. The introduced converter circuit is analyzed by selecting the programmed DC supply.

Fluid Classification via the Dual Functionality of Moisture-Enabled Electricity Generation Enhanced by Deep Learning.

Classifications of fluids using miniaturized sensors are of substantial importance for various fields of application. Modified with functional nanomaterials, a moisture-enabled electricity generation (MEG) device can execute a dual-purpose operation as both a self-powered framework and a fluid detection platform. In this study, a novel intelligent self-sustained sensing approach was implemented by integrating MEG with deep learning in microfluidics. Following a multilayer design, the MEG device including three individual units for power generation/fluid classification was fabricated in this study by using nonwoven fabrics, hydroxylated carbon nanotubes, poly(vinyl alcohol)-mixed gels, and indium tin bismuth liquid alloy. A composite configuration utilizing hydrophobic microfluidic channels and hydrophilic porous substrates was conducive to self-regulation of the on-chip flow. As a generator, the MEG device was capable of maintaining a continuous and stable power output for at least 6 h. As a sensor, the on-chip units synchronously measured the voltage (V), current (C), and resistance (R) signals as functions of time, whose transitions were completed using relays. These signals can serve as straightforward indicators of a fluid presence, such as the distinctive "fingerprint". After normalization and Fourier transform of raw V/C/R signals, a lightweight deep learning model (wide-kernel deep convolutional neural network, WDCNN) was employed for classifying pure water, kiwifruit, clementine, and lemon juices. In particular, the accuracy of the sample distinction using the WDCNN model was 100% within 15 s. The proposed integration of MEG, microfluidics, and deep learning provides a novel paradigm for the development of sustainable intelligent environmental perception, as well as new prospects for innovations in analytical science and smart instruments.

AQUILA OPTIMIZED NONLINEAR CONTROL FOR DC-DC BOOST CONVERTER WITH CONSTANT POWER LOAD

Constant power loads (CPL) can be operated by tight-controlled power electronic converters, which have negative impedance and absorb continuous power. Constant power load creates instability in an open-loop system because of its negative incremental impedance. To tackle this problem, a discrete sliding-mode (AQO-DSM) nonlinear control technique has been proposed for a DC-DC boost converter fed CPL based on Aquila optimization. In this paper, the proposed AQO-DSM controllers provide the system stability during a steady state and maintain output voltage regardless of input voltage or CPL variations. In this case, the DSM controller of a DC-DC boost converter's characteristics are adjusted using the Aquila optimization method (AQO). The Lyapunov stability concept is utilized to assess the system's overall stability. Under various system operating conditions, an experimental study and simulation are carried out to validate the proposed controller. The existing methods, such as sliding mode controller (SMC), fuzzy-based SMC (F-SMC), and super twisting algorithm (STA)-based SMC strategies, are compared with a proposed plan to demonstrate the superiority of the proposed AQO-DSMC. Simulated and experimental results have shown that the AQO-DSMC achieves the fastest convergence, the smallest steady-state, settling time under loaded conditions, and consistent chatter reduction compared with all contrasted control methods.

High-performance floating thermoelectric generator for all-day power supply

Thermoelectric generators (TEGs) offer notable benefits in harnessing diverse low-grade waste heat from the environment. However, the uninterrupted capture of these energy resources still remains a huge challenge. Herein, we have developed a temperature-adaptive floating thermoelectric generator (TAFTEG) by integrating a temperature-adaptive absorber/emitter (TAA/E) to synergistically exploit renewable energy from the sun, outer space, and the water bodies by leveraging diurnal spectrally selective absorption and nocturnal radiative cooling. The WxV1-xO2-based TAA/E demonstrates remarkably solar absorption of ∼96 % and a superior switching ability of dynamic thermal radiation modulation from the low emission of ∼45 % to high emission of ∼81 %. Assembled with 8 pairs of Bi2Te3-based TEG legs, the TAFTEG enables a stable temperature difference of 34°C under indoor solar irradiation (1 kW m−2), yielding a peak power output of ∼1.0 mW cm−2, and continuous all-day power supply under both clear and overcast conditions. This strategy paves a new avenue toward the round-the-clock power supply from ambient environments.

9.4 μm emitting quantum cascade lasers grown by MOCVD: Performance improvement obtained through AlInAs composition adjustment

Metal-organic chemical vapor deposition (MOCVD) is a prevalent technique for the epitaxial growth of quantum cascade lasers (QCLs), with the material quality being paramount to the overall device performance. Previous studies have indicated that the actual aluminum (Al) content in InAlAs barrier layers grown via MOCVD often diverges from the specified design values, particularly for layers with a thickness below 1 nm. To address this discrepancy, the Al content within the InAlAs layers can be fine-tuned by modifying the MOCVD growth parameters. This study undertakes an exhaustive analysis of QCL devices, comparing those with and without aluminum content compensation, through a combination of simulation and experimental approaches. The results demonstrate that the implementation of the Al compensation methodology facilitates the alignment of the QCL device wavelength with the intended design value. This approach also enhances the laser transition efficiency and gain coefficient of the QCL device, thereby improving its slope efficiency and threshold current density. The final QCL device exhibits a wavelength of 9.4 μm, with a maximum continuous wave (CW) and pulsed optical power and wall-plug efficiency (WPE) of 1.26 W and 7.4% and 2.08 W and 10.1%.

13 μm emission InAs/AlSb quantum cascade lasers with high slope efficiency and peak output power enabled by diagonal transition design

Long wavelength InAs/AlSb quantum cascade lasers (QCLs) emitting at 13 μm, based on a diagonal transition scheme design through band structure engineering, have been grown and fabricated. This band structure engineering focuses on enhancing transition efficiency and suppressing carrier leakage. Our 3-mm-long, 25-μm-wide InAs/AlSb QCL has achieved a slope efficiency of 210 mW/A and a maximum peak power of 515 mW, despite encountering a substantial waveguide loss of 27 cm−1 and a relatively high threshold of 4.8 kA/cm2, due to the elevated residual doping level. Our InAs/AlSb QCL devices have demonstrated record-breaking performance in terms of slope efficiency, maximum peak power, and injection efficiency. Cavity length analysis suggests that reducing the residual doping by half could pave the way for achieving continuous wave output power in the realm of hundreds of milliwatts at room temperature for our designed 13 μm QCLs.

ICCOS-Based Continuous Inductive Pulse Power Circuit Topology

ICCOS-Based Continuous Inductive Pulse Power Circuit Topology

Research on a New Topology and Reactive Power Compensation Application of Reinjection Multilevel Voltage Source Converter

Based on the principles of reinjection converter technology and submodule operation, a novel topology for a reinjection multilevel voltage source converter (RMVSC) is proposed. In this topology, submodules are dynamically connected in series as the reinjection circuit. This new topology retains all the functions of the RMVSC while offering flexible control of the reinjection circuit and ease of modularization, making it highly suitable for high-voltage, high-power applications. A circulating drive pulse sequence was developed for the 7-level serial submodule RMVSC, ensuring dynamic stability of the submodule voltage and maintaining low harmonic distortion when interfaced with the grid. Building on this, a double-loop control strategy—comprising an outer power loop and an inner current loop—was proposed for the static synchronous compensator (STATCOM) of RMVSC. A simulation model was constructed in PSCAD/EMTDC, and the simulation results confirm the excellent performance of the proposed topology and the effectiveness of both the modulation strategy and the double-loop control strategy. The RMVSC-STATCOM demonstrates continuous and bidirectional reactive power regulation, with high control accuracy and superior compensation current quality.

Optimal capacity allocation and scheduling strategy for CSP+PV hybrid standalone power plants

Solar photovoltaic (PV) power generation, as an important clean technology, has been widely adopted globally, especially in remote island areas where access to the main power grid is unavailable. PV power can serve as the primary energy source for standalone island grids. However, due to its dependence on sunlight, PV power output fluctuates, particularly during nighttime and under poor lighting conditions, necessitating the integration of energy storage technology or alternative power generation methods to ensure continuous power supply. Concentrating solar power (CSP) generation, as an emerging technology, can provide efficient power output when solar radiation is abundant and ensure continuous power supply through thermal energy storage systems during adverse weather conditions or nighttime. Although CSP offers advantages such as dispatchability, its high construction and maintenance costs may pose challenges in commercial deployment. Hybrid solar power plants combining both PV and CSP technologies leverage the strengths of both, ensuring more stable and economically viable power output. This study establishes a model for hybrid solar power plants, considering the impact of PV and CSP component capacities and proportions on performance and costs, i.e., capacity allocation. To maximize the overall benefits of standalone microgrids while ensuring the stability of the power station, a capacity allocation method guided by economic dispatch is proposed. Through iterative analysis, the optimal configuration is determined to minimize the system's equivalent annual costs. Simulation experiments validate the financial feasibility of hybrid solar power plants and the reliability of the proposed configuration method.