Energy Power Research Articles

Research Progress of Lithium Iron Phosphate in the Cathode of Lithium-Ion Battery

Lithium-ion batteries (LIBs) have been a new candidate for various industries. Unlike other types of lead-acid batteries, LIBs have a very high energy density, power density, and nominal voltage, making them a beneficial choice of battery for many electronic devices like electric vehicles. The role of cathode material in the battery is to start the electrochemical reaction, and the rate capacity is highly dependent on the ion-diffusion rate at the cathode. This makes the cathode the most critical component in the battery. Therefore, it is essential to have excellent cathode material to perform its function. Lithium iron phosphate has always been a desirable cathode material due to its stable structure, high safety, and low cost. By choosing the appropriate material, high capacity and performance can be achieved. By modifying the material through different strategies, LFP has the potential to exceed its theoretical capacity and be applied in the broader field of the electronics industry. First, this article focuses on a comparison of different cathode materials and explains why LFP is superior. Then, it will introduce the synthesis methods, including solid-state, hydrothermal, and sol-gel methods. Finally, it will discuss ways to modify LFP, including nanostructured LFP, carbon coating, and doping. This paper aims to serve as a guide and reference for research in the battery industry.

Mid-infrared enhanced Raman soliton generation in an erbium-doped ZBLAN with record energy and peak power

The advancement of tunable ultrafast sources in the mid-infrared spectrum would bring about significant progress in various scientific fields. This study suggests a gain-modulation technique to increase the peak power and pulse energy of mid-infrared tunable Raman solitons. By utilizing a high-power 2-2.23 µm Raman soliton pulse as a pump source, mid-infrared Raman solitons within the 2-3.2 µm tuning range can be generated in a segment of Er3+: ZBLAN fiber. Additionally, the introduction of 976 nm pump light into the Er3+: ZBLAN fiber leverages the gain of Er3+ to amplify the frequency shift velocity and pulse energy of the Raman soliton. Consequently, the frequency shift range of the Raman soliton is extended to 3.5 µm, with peak power and pulse energy reaching 0.93 MW and 107 nJ, respectively. These achievements represent the highest peak power and energy levels of Raman solitons generated in mid-infrared fibers to date.

Study on improved control strategy of virtual synchronous generator

Virtual synchronous generator (VSG) control technology for photovoltaic, energy storage, wind power, and other new energy to provide flexibility in the grid interface characteristics, is conducive to improving the stability of the power system, and has been widely considered by many scholars. Firstly, an improved VSG control method is proposed through simulation and analysis, which realizes the complete decoupling of the frequency response time constant and the inertia quantity of the active power control loop and reduces the complexity of the parameter design of the VSG system. Secondly, to avoid the frequent action of the VSG system caused by small-scale frequency change perturbation, this study proposes a VSG frequency optimization control method for VSG frequency control with rated angular velocity ωset feedforward composed of multivariate factors when considering a primary frequency regulation dead zone. Thirdly, the impact of VSG parameter design on the system is investigated through the system response characteristics of power scheduling, primary frequency regulation at the grid connection, and the small-signal dynamic characterization of the improved VSG. Finally, Simulation and experimental verification yielded an active power overshoot of 7% and a maximum frequency deviation of 0.17 Hz for the improved system. The improved control method resulted in an improvement of 0.1 s in the frequency response time and a reduction of 0.15 Hz in the oscillation amplitude. The response speed of the improved control method is much better, while the oscillation amplitude is reduced to meet the grid's regulation requirements. The simulation and experimental analysis verify the feasibility of the improved VSG control method.

Prognostics and Health Management for Electrified Aircraft Propulsion: State of the Art and Challenges

Abstract In recent years, the aviation industry has witnessed a transformative wave of innovation in electrified aircraft propulsion (EAP), driven by sustainability and efficiency goals. Integration of novel electrical subsystems, including high-voltage power electronics, motors/generators, and energy storage devices, has introduced intricate complexities. In this context, an intensified focus on prognostics and health management (PHM) is imperative, considering the heightened reliability needs in a transportation propulsion application. This paper extensively analyzes the current state of the art in PHM applicable to various EAP systems and components crucial for the functioning of electric aircraft. Typical fault modes and fault management strategies are analyzed at various levels of systems hierarchy. An integral aspect of our investigation involves the identification of critical gaps within existing PHM frameworks, guiding the research agenda for enhanced reliability and performance. Moreover, the distributed nature and increasing complexity of electric propulsion systems underscore the importance of model-based systems engineering (MBSE). We advocate for the exploration of MBSE not only to inform the design and implementation of PHM solutions but also to facilitate certification and Verification and Validation activities. Additionally, the paper offers insights into existing tools and simulation software packages capable of integrating traditional gas turbine modules with electric subsystems, as well as simulating various faulty conditions in EAP relevant to PHM development. Key gaps in these tools are emphasized, drawing attention to areas that require further refinement and development. This comprehensive exploration aims to pave the way for future advancements in PHM tailored for the unique challenges posed by electric aircraft propulsion systems.

Hybrid Simulation Model of Lifecycle Simulation and Replacement Simulation Considering Carbon Lock-In by Coal-Fired Power Plants

To meet the temperature goal set by the Paris Agreement, cumulative CO2 emissions must be kept below 300 GtCO2. Road transportation accounted for approximately 18% of the CO2 emissions from fuel combustion in 2017. Electric vehicles (EVs) have been rapidly adopted by environmentally conscious consumers in many countries to reduce CO2 emissions. EVs have lower emission intensities than do internal combustion engine vehicles (ICEVs) in most parts of the world, except where the penetration of renewable energy is low in the energy production mix. In such places, the CO2 emissions of EVs are larger than those of ICEVs. Despite the obvious need to increase renewable energy sources to reduce CO2 emissions, Japan and many other countries around the world have yet to shift away from fossil fuels. This is due in part to carbon lock-in, which refers to prior decisions related to technologies and infrastructure that constrain the implementation of better paths toward low-carbon technologies. Coal-fired power plants are the most problematic in terms of carbon lock-in because of their high carbon intensities and long physical lives. In addition, because carbon lock-in by coal-fired power plants has a significant impact on the embodied CO2 intensity of grid power, it impacts society through products that use electric power. In this study, we propose a hybrid simulation model of lifecycle simulation and replacement simulation, considering carbon lock-in by coal-fired power plants. In the replacement simulation, we simulated the replacement of end-of-life coal- and oil-fired power plants with renewable energy power plants using a probability called the lock-in rate and estimated the changes in the embodied CO2 intensity of grid power in Japan. In the lifecycle simulation, we evaluated cumulative CO2 emissions from entire product lifecycles of ICEVs and EVs based on three different EV diffusion scenarios. The results showed that the lock-in rate of coal-fired power plants strongly affects the decarbonization effect due to the market diffusion of EVs.

Two‐stage stochastic energy and reserve market clearing model considering real‐time offering strategy of renewable energy

AbstractWith the introduction of decarbonization policies worldwide, renewable energy, especially wind and solar power, is gradually taking a significant share in the power system. The two‐stage stochastic optimization methods are generally adopted to address the uncertainty issues and the two‐stage stochastic market clearing models are established with the participation of renewable energy. However, most existing two‐stage stochastic market clearing models usually intuitively presume the offering quantities of renewable energy are equal to their forecast values, neglecting the potential impacts of the strategic offerings on the market results and thus affecting the secure operation of power systems. To fill the gaps, this paper incorporates the strategic offering models of renewable energy into the two‐stage stochastic energy and reserve market clearing model. Within the two‐stage framework, the first day‐ahead stage serves for energy and reserve market clearing, while the second real‐time stage considers the adjustments on offering quantities of renewable energy according to the fluctuations of renewable generations. The two‐stage stochastic market clearing model is formulated as a mixed‐integer non‐linear programming problem, and an iterative algorithm is devised to obtain market clearing results after proper linearizations. The effectiveness of the proposed method is validated using the extended IEEE‐118 test system.

Performance of a hybrid thermosyphon cooling system using airside economizers for data center free cooling under different climate conditions

Thermosyphon cooling system is an efficient data center cooling system for energy saving, but its commonly used free cooling technology (water-side economizer) has multiple heat transfer processes, which limit the utilization rate of natural cold sources. In this study, a hybrid thermosyphon cooling system (HTCS) that uses air economizers to assist the water-cooled row-level thermosyphons (terminal equipment part) for free cooling is proposed and investigated in a case data center. The previous cooling system (PCS) designed for this case data center, which used the same terminal equipment part and water-side economizers, is employed for comparison. To analyze the application potential of HTCS under different climate conditions, the energy models of HTCS and PCS are built for comparative studies on energy efficiency, environmental and economic potential in five typical climate cities. The results show that the HTCS has 575–4589 h longer free cooling periods than that of PCS in five typical climate cities, which leads to the annual energy consumption and Power Usage Efficiency of HTCS in most typical climate cities except Kunming are 13.7–24.7 % and 0.014–0.041 lower than those of PCS, respectively. Meanwhile, HTCS's annual CO2 emissions and life cycle costs are 344.2–1248.4 tons and 9.5–25.4 % lower than those of PCS in five typical climate cities except Kunming, which illustrates HTCS has good energy-saving and economic performance for data centers.

Two-Stage Locating and Capacity Optimization Model for the Ultra-High-Voltage DC Receiving End Considering Carbon Emission Trading and Renewable Energy Time-Series Output Reconstruction

With the load center’s continuous expansion and development of the AC power grid’s scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking due to the high strength of AC-DC coupling and the low level of system inertia, which brings many complexities and uncertainties to economic scheduling. In addition, the large-scale grid integration of wind power, photovoltaic, and other intermittent energy sources makes the ultra-high-voltage (UHV) DC channel operation state randomized. The deterministic scenario-based timing power simulation is no longer suitable for the current complex and changeable grid operation state. In this paper, we first start with the description and analysis of the uncertainty in renewable energy (RE) sources, such as wind and solar, and reconstruct the time-sequence power model by using the stochastic differential equation model. Then, a carbon emission trading cost (CET) model is constructed based on the CET mechanism, and the two-stage locating and capacity optimization model for the UHV DC receiving end is proposed under the constraint of dispatch safety and stability. Among them, the first stage starts with the objective of maximizing the carrying capacity of the UHV DC receiving end grid; the second stage checks its dynamic safety under the basic and fault modes according to the results of the first stage and corrects the drop point and capacity of the UHV DC line with the objective of achieving safe and stable UHV DC operation at the lowest economic investment. In addition, the two-stage model innovatively proposes UHV DC relative inertia constraints, peak adjustment margin constraints, transient voltage support constraints under commutation failure conditions, and frequency support constraints under a DC blocking state. In addition, to address the problem that the probabilistic constraints of the scheduling model are difficult to solve, the discrete step-size transformation and convolution sequence operation methods are proposed to transform the chance-constrained planning into mixed-integer linear planning for solving. Finally, the proposed model is validated with a UHV DC channel in 2023, and the results confirm the feasibility and effectiveness of the model.

Game-theoretic analysis of suppliers’ pricing power in thermal-electric local energy markets

The integration of renewable energy resources can be facilitated by local energy markets (LEMs) for multiple energy commodities. While multi-energy LEMs are designed to alleviate entry barriers for smaller players, the limited capacity and participant count within an LEM can cause imperfect competition. This study formulates a Nash–Cournot game to analyze the market power of local suppliers in a thermal-electric LEM. By comparing the prices and welfare outcomes of a perfectly competitive market with those of an oligopolistic market, we highlight the impact of the number and mix of market participants on the distribution of social welfare and market efficiency. Additionally, we introduce and assess two strategies aimed at mitigating the supplier’s market power. Based on simulations of a LEM with demand and installed capacity similar to that of a large German city, we show that LEM should not be assumed to be perfectly competitive, as the strategic behavior of supplier agents significantly affects the market outcome. Our analyzed mitigation strategies exhibit the potential to curtail suppliers’ market power, redistribute social welfare, and contribute to more balanced market dynamics.

Maximizing energy efficiency and system throughput using a self-adaptive penalty function with a whale optimization algorithm in social-aware device-to-device communications

Device-to-device (D2D) communication is an emerging approach for 5 G networks. It allows for high capacity, low latency, and increased bandwidth. These features have prompted several research studies to focus on meeting customers’ expectations. This research concentrates on obtaining optimal resource and power allocation, better quality of service, and reliable connectivity between D2D clients through a whale optimization algorithm (WOA). The WOA possesses greater stability, faster integration speeds, a powerful global search ability, and greater accuracy than traditional methods. The WOA utilizes an unconstrained objective function obtained through a self-adaptive penalty function. This unconstrained objective function yields optimal solutions for the resource as well as power allocation, higher throughputs, and energy and spectral efficiencies in D2D communications. For D2D communications, the energy efficiency of the WOA is 47.12 % higher than a genetic algorithm (GA) and 70.33 % higher than particle swarm optimization (PSO), and it yields high spectral efficiency and system throughput. Obviously, the WOA in this proposal is more efficient than a GA or PSO and shows the advantages of combining physical and social parameters for improved wireless network performance.

Capacity Optimization of Wind–Solar–Storage Multi-Power Microgrid Based on Two-Layer Model and an Improved Snake Optimization Algorithm

A two-layer optimization model and an improved snake optimization algorithm (ISOA) are proposed to solve the capacity optimization problem of wind–solar–storage multi-power microgrids in the whole life cycle. In the upper optimization model, the wind–solar–storage capacity optimization model is established. It takes wind–solar power supply and storage capacity as decision variables and the construction cost of the whole life cycle as the objective function. At the lower level, the optimal scheduling model is established, considering the output characteristics of various types of power supplies and energy storage, microgrid sales, and purchases of power as constraints. At the same time, the model considers constraints, such as the power balance, the operating state of the energy storage system, the power sales and purchases, and the network fluctuations, to ensure the system operates efficiently. Taking a microgrid in South China as an application scenario, the model is solved and the optimal capacity allocation scheme of the microgrid is obtained. Meanwhile, the demand response mechanism and the influence of planning years are introduced to further optimize the configuration scheme, and the impact of different rigid–flexible load ratios and various planning horizons on microgrid capacity optimization is analyzed, respectively, by a numerical example. The comparison shows that the ISOA has better optimization performance in solving the proposed two-layer model.

Effect of Solar Irradiation Inter-Annual Variability on PV and CSP Power Plants Production Capacity: Portugal Case-Study

The sizing of solar energy power plants is usually made using typical meteorological years, which disregards the inter-annual variability of the solar resource. Nevertheless, such variability is crucial for the bankability of these projects because it impacts on the production goals set at the time of the supply agreement. For that reason, this study aims to fill the gap in the existing literature and analyse the impact that solar resource variability has on solar power plant production as applied to the case of Portugal (southern Europe). To that end, 17 years (2003–2019) of meteorological data from a network of 90 ground stations hosted by the Portuguese Meteorological Service is examined. Annual capacity factor regarding photovoltaic (PV) and concentrating solar power (CSP) plants is computed using the System Advisor Model, used here for solar power performance simulations. In terms of results, while a long-term trend for increase in annual irradiation is found for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI), 0.4148 and 3.2711 kWh/m2/year, respectively, consistent with a solar brightening period, no corresponding trend is found for PV or CSP production. The latter is attributed to the long-term upward trend of 0.0231 °C/year in annual average ambient temperature, which contributes to PV and CSP efficiency reduction. Spatial analysis of inter-annual relative variability for GHI and DNI shows a reduction in variability from the north to the south of the country, as well as for the respective power plant productions. Particularly, for PV, inter-annual variability ranges between 2.45% and 12.07% in Faro and Santarém, respectively, while higher values are generally found for CSP, 3.71% in Faro and 16.04% in São Pedro de Moel. These results are a contribution to future instalments of PV and CSP systems in southern Portugal, a region with very favourable conditions for solar energy harvesting, due to the combination of high production capacity and low inter-annual variability.

Preface

The International Conference on Power System and Energy Technology (ICPSET) has confirmed once again this year the enthusiasm and determination of students and young researchers to play a major role in the scientific progress. Since 2020, we have gathered together to discuss the most recent developments and achievements on power system and energy technology, and we firmly convince that sharing our expertise and experience is the foundation of research activity. The 2024 3rd International Conference on Power System and Energy Technology (ICPSET 2024) took place from July 5th to 7th, 2024 in Hangzhou, China, attracting more than 100 leading delegates worldwide. The format we chose is a formal meeting primarily aimed at graduate students and leading researchers, who were encouraged to present their work through oral or poster presentations that provide genuine engagement of the audience and cross-pollination of ideas. The main purposes of the conference were to create an international forum for researchers, both experimentalists and theorists, and foster fruitful collaborations across different branches of power system and energy technology. With the strong organizing team, committee member, the great number of excellent submission as well as the wide international fame, the ICPSET was held for the third time. The success of this year’s event was testified by an increased number of participants and institutions all around the world. This resulted in an extremely rich and interactive keynote speech, oral and poster session that covered several areas related to power system and energy technology. With the intent of broadening the contents and stimuli adopting academic communication, the keynote speech part was held. This choice reflects the growing importance of the activity performed by scientists and researchers as a way of increasing their expertise and developing soft skills. Included among the keynote speakers were Professor Qian Chen (Jiangsu University, China), Professor Qingshan She (Hangzhou Dianzi University, China), Professor Jingfeng Mao (Nantong University, China), Associate Professor Zafar Said (University of Sharjah, the United Arab Emirates), as well as Associate Professor Wentao Huang (Jiangnan University, China). They gave wonderful keynote speeches and shared their latest research results and insights through their research and experimental experiences and professional knowledge in the fields of power systems and energy technologies. This conference provided a high-level academic exchange platform for participants, promoted the exchange and collision of new ideas and technologies, and promoted the innovation and development of power systems and energy technologies as well as their affiliated industries and disciplines. In this volume, we collected the excellent contributions that have also been presented at the conference through oral or poster presentations, covering topics on Intelligent Protection and Substation Integrated Automation, Power System Real-Time Simulation System, Smart Grid, Renewable Energy, Energy Storage Technology, Energy Efficiency, Energy Conversion and Application, among others. Finally, we would like to thank all the keynote speakers, authors, reviewers, and everyone who contributed to the conference. We owe gratitude to all the committee members for providing necessary help and support throughout the conference. Special acknowledgements to the IOP Press-Journal of Physics: Conference Series for its help in making this volume published. The Committee of ICPSET 2024 List of Committee Member is available in this Pdf.

Preface

Abstract The International Conference on Power System and Energy Internet (PoSEI) originates from 2021 and has gained significant recognition over the years and attracted various promising scholars and researchers who are developing new directions in the fields of power system and energy internet. The 2024 4th International Conference on Power System and Energy Internet (PoSEI 2024) took place in Fuzhou, China from July 26th to 28th, 2024. Building upon the success of its predecessors, PoSEI 2024 was meant to unite researchers, scientists, experts, academic staff as well as a wide range of participants of professional community from China and other countries, and to further advance the understanding and development of energy systems, particularly focusing on the integration of power systems and energy internet, a novel ecosystem that deeply intertwines systematic thinking, digital technologies, and various aspects of energy production, transmission, storage, consumption, and markets. The highly eventful program of the conference, the list of well-established organizations-participants as well as the devoted engagement of many colleagues throughout all stages of the conference’s preparation instill confidence in practical importance of mutual communication and initiative. The framework of the conference mainly comprised opening speech, keynote speech, oral presentation, poster presentation, and academic investigation, discussing significant problems facing power system and energy internet, proposing innovative ideas and approaches to solutions of these problems, and considering new possibilities of application and development of cutting-edge technology. The topics discussed include but are not limited to architecture and design of energy internet, artificial intelligence for energy internet, energy control and storage, data centers for energy internet, microgrid, operational flexibility of power systems, transmission and distribution systems and apparatus, energy system integration, cyber-physical systems and cybersecurity in energy internet, etc. The conference has become one of the venues for demonstrating scientific achievements of international class by leading scientists and young scholars and would facilitate the strengthening of academic cooperation, meanwhile the conference’s Proceedings would be expressed in the form of international scientific publishing. The contributions in the Proceedings reflect the high quality and diversity of research presented during the conference. Each paper underwent a rigorous peer-review process, ensuring that only the most innovative and scientifically rigorous contributions were included. We are particularly grateful to the authors for their contributions, which not only enrich the Proceedings but also contribute to the overall progress of knowledge in the field. The conference would not have been possible without the tireless efforts of the organizing committee, reviewers, sponsors, and participants. Their dedication and support made PoSEI 2024 a truly international and interdisciplinary event. Last but not the least, we acknowledge the publishing support from the members of IOP Press-Journal of Physics: Conference Series. Finally, we would like to express our sincere hope that PoSEI 2024 will serve as a catalyst for further progress and innovation in the field of power systems and energy internet. We look forward to welcoming you all again at future PoSEI conferences. The Committee of PoSEI 2024 List of Committee Member is available in this Pdf.

The application and optimization of scene reduction algorithm in integrated prediction of wind and photovoltaic energy

Abstract Wind power and photovoltaic energy, as the most representative clean energy sources, have experienced rapid development. However, they are highly dependent on meteorological conditions and have poor predictability, posing a significant challenge for the integrated forecasting of wind power and photovoltaic energy. This paper investigates a scenario reduction algorithm based on Latin hypercube sampling and probability distribution to optimize the integrated forecasting of wind power and photovoltaic energy. By generating a large number of wind power and photovoltaic scenarios and utilizing Euclidean distance and probability distribution calculations, the scenarios are streamlined. The algorithm is implemented in MATLAB, and the effectiveness and superiority of the algorithm are demonstrated through detailed experiments and plots.

Multi‐timescale optimal scheduling of microgrids for generating new energy output scenarios based on correction error sampling intervals

AbstractMicrogrid can realize energy saving and emission reduction and multi‐energy complementation, but the fluctuation of renewable energy output and the error of day‐ahead scheduling will threaten the stability of microgrid operation. For this reason, this article proposes a microgrid multi‐timescale optimal scheduling method based on new energy output scenario generation. First, the microgrid framework of this article is introduced, and an energy cycle emission reduction model taking into account electricity‐to‐gas conversion is designed; second, a new energy prediction error model is established based on the prediction box and Gaussian hybrid model, and the scenario of wind and photovoltaic power generation is generated by correcting the sampling intervals for error sampling; and then, based on the day‐ahead scheduling plan, an intraday cooling, heating and electricity two‐layer rolling optimization model is established to correct the day‐ahead scenario. Finally, the example analysis shows that the cyclic emission reduction model can realize the recycling of resources, reduce the fuel cost and carbon emission, and the generation of scenarios for wind power can smooth out the fluctuation of new energy power, which, together with the intra‐day two‐layer rolling optimization, can reduce the day‐ahead scheduling error and improve the stability of microgrid operation.

Various pulse nonlinear evolution and dynamics employing CuCrO2 nanocrystals as a promising saturable absorber

Considering that fiber lasers are a far richer nonlinear optical system, a systematical study on various pulse nonlinear evolution and dynamics by one SA has great significance. However, investigating these important pulse nonlinear dynamic evolution processes of CuCrO2 nanocrystals as new SAs applied in ultrafast fiber lasers has never been explored. Herein, we demonstrate the excellent nonlinear optical properties of CuCrO2 nanocrystals and investigate the potential of CuCrO2 nanocrystals for generating various pulse nonlinear dynamic evolution processes. Firstly, the output characteristics of the passively Q-switching pulsed fiber lasers have been regulated by using CuCrO2 nanocrystals-polyimide film and a tapered fiber. The pulse duration and repetition rate were simultaneously compressed by 10 and 222 times, the pulse energy and peak power were increased by 79 and 827 times, respectively. Secondly, we are able to generate chaotic multi-pulse wave packets and optical rogue waves by the polarization mode dispersion of single-mode fiber together with the non-instantaneous relaxation of CuCrO2 nanocrystals. Finally, the transition from chaotic multi-pulse wave packet to giant chirped mode-locked pulse is realized by introducing high nonlinear fibers. Our results show that CuCrO2 nanocrystals are an efficient nonlinear material for studying various nonlinear phenomena, and give a new impetus to the development of nonlinear optics and ultrafast photonics.

One step glow-discharge electrolysis-based preparation of Al doped Ni-Co layered double hydroxide/ graphene oxide as supercapacitor electrode material

Nickel-cobalt layered double hydroxides (LDHs) are promising materials for supercapacitor electrodes; however, they face challenges in terms of cycling stability and rate capability owing to agglomeration and low conductivity. In this study, Ni(III)CoAlx-LDH/GO with an extended layer spacing and excellent electronic conductivity was synthesized by one-step glow discharge electrolysis. A nickel–cobalt alloy was used as the anode, a graphite rod as the cathode, and sodium chloride as the electrolyte. In addition, incorporating an appropriate amount of aluminum chloride into the electrolyte can alter the microstructure of the electrode material, leading to enhanced electrochemical performance. Ni(III)CoAl0.2-LDH/GO, synthesized using 0.2 g AlCl3, demonstrated exceptional electrochemical performance of 1014C g−1 at 2 A/g. At a current density of 5 A/g, the capacitance retention rate was 85.3 % after 10,000 cycles, indicating strong cyclic stability. Moreover, an asymmetric supercapacitor built with Ni(III)CoAl0.2-LDH/GO as the anode and commercial activated carbon as the cathode achieved a specific capacitance of 146.2F/g at a current density of 1 A/g. This device demonstrated outstanding circular stability, retaining 85.07 % of its capacitance after 10,000 cycles. In addition, the device achieves relatively high energy density and power density (energy density of 66.63 Wh kg−1 at a power density of 1022.23 W kg−1). This study introduces a novel synthesis method for the preparation of high-performance electrode materials aimed at advancing energy storage devices.

Giant energy storage capacity of graphene quantum dots prepared by facile method

Supercapattery technology focuses on high specific capacity with both high energy density and power density. In the present work, the electrochemical performance of Graphene quantum dots (GQDs) is compared with graphene oxide (GO). GO is synthesized by the modified Hummer's method. Less than 5 nm size of GQDs are synthesized by a facile chemical cutting method. High frequency vibrational mode of sp-sp2 bonded carbon at 2198 cm−1 is revealed from Raman analysis. The energy gap of GQDs of different sizes was calculated using the Quantum Espresso code based on Plane-Wave Self-Consistent Field (PWSCF). The forbidden gap between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) levels with the size of the GQDs cluster. The electrochemical results show that GQDs exhibit pseudocapacitor behavior with high specific capacity and energy density of 1516.7C/g and 425.9 Whkg−1 respectively at current density of 4 A/g. This is very high compared to the electric double layer capacitor (EDLC) behavior (115C/g) of GO. These results illustrate enhanced electrochemical performance, electrical conductivity and ion transport rate implying that the material can facilitate the movement of ions within the device, allowing for fast charging and discharging.

Synthesis and Characterization of Synergetic Pd/MoO3–rGO Hybrid Material as Efficient Electrode for Supercapacitor Application

In this work, study synthesized Pd–rGO and Pd/MoO3–rGO nanocomposites via a one-pot hydrothermal method, serving as efficient electrodes for supercapacitor applications. Various analytical techniques, including XRD, XPS, HRTEM, BET, and Raman spectroscopy, were employed to characterize the structural, morphological, and physiochemical properties to assess the electrochemical supercapacitor performance of nanocomposite materials. The analyses confirmed that the charge transfer mechanism between the MoO3-NR with Pd-rGO in Pd/MoO3–rGO samples has significantly improved the electrochemical performance of Pd/MoO3–rGO by 2.7 times compared to Pd-rGO sample (105.00 F/g at 0.5 A/g). Remarkably, the Pd/MoO3–rGO hybrid material exhibited excellent electrochemical activity, boosting a specific capacitance of 291.50 F/g at a current density of 0.5 A/g, accompanied by energy density and power density values of 18.06 Wh/kg and 250.00 W/kg, respectively. Furthermore, it demonstrated noteworthy stability over prolonged usage, retaining 88.46% of its capacity after 1,000 cycles at a constant current density of 1.0 A/g. These findings underscore the promising potential of the Pd/MoO3–rGO nanocomposite as a highly effective electrode material for supercapacitors.