Today's Energy Research Articles

Performance optimization of MoS2-doped PVDF-HFP nanofiber triboelectric nanogenerator as sensing technology for smart cities

The greatest potential for resolving today's energy crisis caused by social globalization is the invention of nanogenerators. Triboelectric nanogenerators (TENGs) are among the most advanced and promising technologies because of their simple and affordable device design. TENGs can capture mechanical energy from our surroundings. Herein, we fabricated a TENG device using a novel MoS2-doped poly (vinylidene fluoride-co hexafluoropropylene) (PVDF-HFP) electrospun fiber and amino-functionalized reduced graphene oxide-doped polyurethane (PU/A-rGO) electrospun fiber as tribonegative and tribopositive materials, respectively. The concentration of MoS2 nanofiller doping in PVDF-HFP fiber was varied to study and optimize the output performance of TENG. The highest open circuit potential of 150 V, short circuit current of 4.2 μA, and power density of 0.17 Wm−2 are displayed by the 3 wt% MoS2 filled PVDF-HFP and 2 wt% A-rGO-doped PU-based (3PHM-PU/2A-rGO) TENG device. The surface potential of the 3PHM fiber showed a saturation reading of -832 V, which is 4.3 times greater than that of 0PHM fiber (0PHM -190 V). Lastly, the TENG device is used to demonstrate practical and instantaneous applications like LED lighting and the operation of portable electronics by harvesting mechanical energy. Furthermore, the TENG device shows a lot of potential in using smart streetlight sensor applications.

Progress in the Application of LiMnPO4 Nanomaterials in Lithium-ion Battery Cathode

Lithium-ion batteries (LIBs) have become vital in today's energy storage systems, especially for electric cars and portable gadgets. High energy density, extended cycle life, and quick charging times are features of lithium batteries. Compared to conventional batteries, they are lightweight, ecologically benign, and have a low self-discharge rate. LiMnPO4 nanomaterials have garnered significant interest among various cathode materials due to their superior thermal stability, safety, and high operating voltage. The main topics of this paper are the structural characteristics, production techniques, and performance improvements of LiMnPO4 nanoparticles as LIBs cathodes. The basic operating principles of LIBs were covered in this article, with particular attention paid to the redox reactions occurring at the electrodes, the unique olivine structure of LiMnPO4, and how these factors affect electrochemical performance. The efficiency of many synthesis methods, such as spray pyrolysis, sol-gel, solid-state, hydrothermal, and solvothermal processes, in yielding superior LiMnPO4 nanoparticles is assessed. Additionally, surface modifications through ion doping and carbon coating are reviewed to highlight their roles in enhancing conductivity and stability. This article aims to provide ideas for developing high-performance LiMnPO4 cathode materials to affect LIBs' development positively. This article aims to provide ideas for developing high-performance LiMnPO4 cathode materials to influence LIBs' development positively.

Advanced Methods for Verifying Memory Controllers in Modern Computing Systems

The primary component of the computer system that requires enhancement is the memory's performance. A memory controller helps in the management of control between the memory as well as the processor. This study gives a general outline of how controller performance in systems based on power converters may be improved using AI approaches. Among the many uses for power converters in today's electrical and energy systems are the effective control and conversion of energy in electric cars, renewable energy sources, and industrial automation, among others. Complementary control strategies used in classical approaches, although work well, may experience difficulties when it comes to system complication, change, and unpredictability. To overcome these restrictions, artificial intelligence methods appear rather prospective. Among the AI types one can distinguish neural networks, fuzzy logic, machine learning that may help to control the converters with enhanced efficiency by using adaptive and intelligent control. These approaches enhance control precision, succession, and reaction time to enhance system effectiveness and dependability. Moreover, this integration of AI enhances the most power converters by making it easier to predict maintenance, detect faults, and optimise for energy hence enhancing the systems. The paper presents new trends in the advanced smart control of the power converters, total control techniques, advantages as well as the challenges posed by AI control strategies. It also describes future trends and research areas for achieving enhanced performance in power converter-based systems through AI and Control techniques

Managing the decline of coal in a decarbonizing China

AbstractPressures to address climate change are eroding the privileged role coal has held in China throughout its modernization. Phasing down coal requires a suite of supply‐ and demand‐side tools to both reduce production (and therefore, maintain sufficiently high prices) and shift to coal alternatives across diverse consumption sectors. This review outlines contours of the coming coal transition by documenting coal's rise in modern China, its status in key debates of today's energy system, and the range of modeling scenarios of coal's future to mid‐century. In addition, through an analysis of current efforts and impacts in four transition policy areas—supply‐side, demand‐side, employment and social impacts, and stranded assets and fiscal revenues—it identifies gaps and future recommendations. Emerging scholarship on enhancing political feasibility and fostering a “just transition” needs to move beyond global cases and address highly localized and temporally bound impacts.This article is categorized under: The Carbon Economy and Climate Mitigation > Future of Global Energy Policy and Governance > National Climate Change Policy

The interconnectedness of energy consumption with economic growth: A granger causality analysis

In considering today's energy challenges, the link between the usage of renewable and non-renewable energy sources and economic growth has gained substantial policy attention. This research examines the complex relationship between these three variables to understand how non-renewable energy consumption and renewable energy consumption interact and what that means for economic growth. This study uses the Granger causality approach to explore the relationships between non-renewable energy consumption, renewable energy consumption, and economic development. It draws on a comprehensive dataset from the Word Bank database, including 152 nations from 1990 to 2019. The analysis is further disaggregated by four subgroups of countries; least developed, developed, transitional economies and developing countries. The result of this study provides valuable empirical evidence of uni-directional causality running from renewable energy consumption to economic growth and non-renewable energy consumption to economic growth in transitional economies. Furthermore, policymakers should focus on both variables when making decisions because the results show that energy consumption and economic growth are interconnected. Implementing global energy efficiency standards, reducing fossil fuel usage, and adopting regulatory measures are all viable policies for limiting adverse effects on the environment while encouraging economic development.

Honey Badger Algorithm Based DVR Controllers for Improved Power Quality‏ in a Microgrid Combined of (Wind System\ Grid\Nonlinear Load)

Power quality (PQ) is crucial in today's energy supply networks, where even little voltage fluctuations can have a big impact on how well household appliances and technologies operate. The suggested dynamic voltage regulator (DVR) approach helps to create a new generation power grid that is more dependable and effective. In this study, the honey badger optimizer (HBO) is used to optimize the controllers of the DVR for improving PQ via voltage control. The efficacy of the optimized DVR is further increased by its integration with a microgrid (MG) wind supply. The suggested technique makes use of a low-complexity control approach for voltage regulation to adjust for harmonic distortion, swells, and voltage dips in the addressed system. The technique accomplishes voltage improvement, bus stabilization, energy-efficient utilization, and harmonic distortion reduction by using the DVR in conjunction with an MG wind supply. Various voltage disturbances, such as balanced and unbalanced swell and sag, voltage imbalance, notching, various fault states, and power system harmonic distortion, are taken into consideration to show the approach's usefulness. The findings indicate PQ enhancement, demonstrating that the load voltage roughly matches the nominal value.

Ultra-wideband solar perfect absorber for photothermal conversion with high manufacturing error tolerance

Solar energy is a key way to solve today's energy and environmental crises, and the full collection and utilization of solar energy requires a solar absorber with a broader spectrum and higher efficiency. Here, we present a solar metamaterial absorber, consisting of a Ti substrate, a Si3N4 dielectric spacer layer, and a Ti–SiO2 patterned layer. The results of the simulation show that the average absorption of the absorber is 98.16% in the range of 200–4200 nm under normal incidence. Its high absorption is attributed to the interaction of magnetic resonance (MR), cavity resonance (CR), guided mode resonance (GMR) and surface plasmon resonance (SPR). Moreover, the total absorption of the absorber in the AM1.5 standard solar radiation spectrum is 97.8% and the total absorption of blackbody radiation at 1500 K is 98.0%. In addition, the total photothermal conversion efficiency is still 92.2% at 1000 K. The proposed metamaterial absorber is also characterized by wide-angle incidence insensitivity, polarization-independence and a high tolerance of fabrication errors, which can be practically applied in the field of solar energy harvesting.

Performance modification of an acid gas incinerator to reduce atmospheric pollutants impact: Energy management, HAZOP and LCA analyses

In today's industrial landscape, energy management, process modification, and reduction of atmospheric concentrations of pollutants and safety risks have become paramount. This focus is driven by the need to address environmental concerns, economic efficiency, and the global energy and climate change crisis. In gas refineries, incinerators are widely used to convert deadly and environmentally polluting acid gases into less hazardous gases. Therefore, improving incinerator performance can significantly impact environmental, economic, and energy aspects. According to the results of an energy management study at the domestic gas processing plant, the acid gas incineration unit was identified as a significant energy use. Therefore, based on the effects of the performance of this incinerator from environmental and energy points of view, the mentioned unit was prioritized for modification in this work. For this purpose, incinerator performance was assessed using Promax simulation, and Hazard and Operability (HAZOP) analysis was employed to identify potential hazards. The simulations revealed that acid gas residence time was 0.81s, longer than the 0.6s initial design with the damper in place. This suggests damper removal is feasible. Removing the damper reduces residence time and lowers incinerator temperature, especially during startup. Therefore, temperature was considered as the keyword in the HAZOP study, and a number of recommendations were proposed to eliminate or mitigate the risks of system modification. Furthermore, the assistance of results obtained from energy management based on ISO 50001:2018 standards confirm improvements in energy efficiency and fuel consumption, which have positive economic and environmental impacts. Moreover, the study employs a Life Cycle Assessment (LCA) approach using SimaPro Software 9.5.0.1 and the CML-baseline method (Centrum voor Milieukunde Leiden) for environmental impact assessment. The results reveal that, across ten environmental impact categories, the modified project exhibits significantly reduced environmental impacts compared to its original state.

The Application of Intelligent Architectural Design in Energy Saving and Sustainable Development

In today's context, energy conservation, emissions reduction, and sustainable development are highly prioritized, and the architectural industry must recognize the value of intelligent buildings to maintain stable growth amidst fierce competition. Intelligent design not only enhances the energy efficiency of buildings, achieving energy savings and emissions reductions, but also significantly improves their safety and convenience, providing a more comfortable living environment for residents. Moreover, it is a key force driving technological innovation in the architecture industry, leading it towards more efficient, environmentally friendly, and sustainable development. In terms of application principles, intelligent architectural design emphasizes coordination, integrity, and flexibility. It requires considering the harmonious unity between architecture and the environment, ecosystems, and human needs during the design process, treating the building as an integrated system, and focusing on the flexibility and adjustability of the design to accommodate potential future changes. In specific applications, intelligent designs for natural lighting, ventilation, and electrical systems are important manifestations of intelligent architectural design. These applications, through intelligent control systems and devices, achieve efficient management and adjustment of the building environment, thereby enhancing the building's energy efficiency and contributing to sustainable development.

Full state observer-based pole placement controller for pulse width modulation switched mode voltage-controlled buck Converter

Switched mode DC-DC converters play an important role in today's renewable energy systems, electric Vehicles, consumer electrical appliances, and many more. While many researchers have designed controllers for DC-DC converters, achieving low implementation cost remains a significant hurdle. This paper proposes a cost-effective observer-based pole placement controller for a PWM voltage-controlled Buck converter with clear step by step design approach. The state space averaged model of the DC-DC power converter is used to design pole placement with integrator compensator and full state observer. Pole placement is employed to improve the transient and steady state behavior of Voltage reference tracking response and full state observer is applied to extract the inductor current with the aim of removing the actual current sensor. Design specifications are set to a settling time of less than 5 msec and an overshoot of less than 5 %. While designing Observer-Controller combination, the separation principle, designing the controller and observer independently, is utilized by placing the observer poles far to the left of the controller poles for the Observer to converge faster. The designed controller and observer is verified with simulation in MATLAB/SIMULINK software and design of developed controller and observer are realized using low-cost analog electronics circuit components The results shows that the proposed system's strength in tracking the reference output voltage even in the presence of input voltage disturbance and the mean value of inductor current is well extracted having only the output voltage and MOSFET gate signal.

Geothermal In-Situ Heat Transfer Control Factor Simulation and Numerical Analysis

Geothermal energy, as a renewable and clean energy source, holds immense potential in meeting energy demands and reducing carbon emissions. Its unique sustainability and environmental friendliness make it an important complement to addressing today's energy challenges. Coaxial tubing in-situ heat exchange technology for geothermal wells, as a key extraction method for geothermal energy, is subject to control by multiple critical factors that directly relate to its efficiency and feasibility. This paper aims to delve into the technology of coaxial tubing in-situ heat exchange for geothermal wells through numerical simulation analysis, with a focus on studying the impacts of three key factors on its performance: heat transfer medium flow rate, inlet water temperature, and cement thermal conductivity. Through numerical analysis, this study aims to reveal the variations of these factors to provide more refined control methods and optimize the coaxial tubing in-situ heat exchange technology for geothermal wells. By conducting experimental simulations and numerical analysis on these key factors, this paper aims to provide strong support for optimizing the coaxial tubing in-situ heat exchange technology for geothermal wells, which will contribute to advancing geothermal energy technology and promoting the sustainable utilization of clean energy.

Inductive effect in amino functionalized ionic liquids modified TS-1 nanosheets for efficiently sunlight-driven CO2 reduction

Photocatalytic technology for converting CO2 into useful chemicals or clean energy is an effective strategy to solve today's energy and environmental problems. In this study, we present a direct photocatalytic pathway for the conversion of CO2-to-CO involving the formation and activation of carboxyl intermediates over amino-functionalized ionic liquid (3-aminopiperidine hydrochloride, [3APip]Cl)-modified titanium silicalite-1 (TS-1) molecular sieve nanosheets. Various in-situ characterizations reveal that the key to activating this pathway lies in the CO2 adsorption capacity and the efficiency of photoexcited charge migration induced by [3APip]Cl in the hybrid catalyst. In the above catalytic pathway, CO2 molecules are first adsorbed on the surface of the [3APip]Cl/TS-1 hybrid catalyst under the induction of amino groups in the ionic liquid. Then, these adsorbed CO2 are activated and transformed into carboxyl intermediate, which can be further converted into CO and CH4 through photoexcited electrons captured by [3APip]Cl. Based on the results of CO2 reduction performance, the optimized [3APip]Cl/TS-1 hybrid catalyst achieves a 6-fold increase, and the CO selectivity is 83.0%. This research provides new insights into the CO2 reduction pathway in mild conditions and emphasizes the importance of the adsorption–activation tandem process for enhancing photoactivity and selectivity.

Extraction of Uranium by a Cheap Phosphite-Derived Polymer under Light Condition.

Uranium, as the main fuel of today's nuclear energy, is crucial to the development of nuclear energy. Therefore, the development of low-cost and powerful adsorbents is very important for the removal or recovery of uranium from uranium-containing solutions. Herein, we report the synthesis of a cheap phosphite-derived polymer for such use. Under visible-light irradiation, this phosphite-derived polymer was found to enable selective adsorption of uranium with an adsorption capacity as high as 1030 mg/g, suggesting its great potential in handling nuclear waste.

Enabling High-Performance Battery Electrodes by Surface-Structuring of Current Collectors and Crack Formation in Electrodes: A Proof-of-Concept

Today's society and economy demand high-performance energy storage systems with large battery capacities and super-fast charging. However, a common problematic consequence is the delamination of the mass loading (including, active materials, binder and conductive carbon) from the current collector at high C-rates and also after certain cycle tests. In this work, surface structuring of aluminum (Al) foils (as a current collector) is developed to overcome the aforementioned delamination process for sulfur (S)/carbon composite cathodes of Li-S batteries (LSBs). The structuring process allows a mechanical interlocking of the loaded mass with the structured current collector, thus increasing its electrode adhesion and its general stability. Through directed crack formation within the mass loading, this also allows an enhanced electrolyte wetting in deeper layers, which in turn improves ion transport at increased areal loadings. Moreover, the interfacial resistance of this composite is reduced leading to an improved battery performance. In addition, surface structuring improves the wettability of water-based pastes, eliminating the need for additional primer coatings and simplifying the electrode fabrication process. Compared to the cells made with untreated current collectors, the cells made with structured current collectors significantly improved rate capability and cycling stability with a capacity of over 1000mAhg−1. At the same time, the concept of mechanical interlocking offers the potential of transfer to other battery and supercapacitor electrodes.

Optimized Building Envelope: Lightweight Concrete with Integrated Steel Framework.

This study presents a novel construction method for prefabricated wall elements by integrating a framework made of thin-walled sheet steel profiles into an optimized thermally insulating lightweight aggregate concrete (LAC) building envelope. The load-bearing function of the framework is provided by cold-formed Sigma-profiles, which are spot-welded to non-load-bearing U-profiles at the vertical ends. The LAC shapes the wall and stabilizes the thin-walled steel profiles against buckling, but has no further load-bearing function, thus allowing the reduction of its necessary compressive strength and subsequently minimizing its density. As a result, the LAC exhibits strength and density values well beyond existing standards, providing highly competitive thermal conductivity values that meet today's energy requirements without the need for additional insulation materials. Tailored composite specimens verify the stabilization of load-bearing sheet steel profiles by the LAC, which not only prevents buckling but also increases the load-bearing capacity of the overall system. The feasibility of this approach is validated by the production of two prototypes, each comprising a full-sized wall, in two different precast plants using distinct process technologies.

Bio-based building materials: A prediction of insulating properties for a wide range of agricultural by-products

Sustainable construction is a key solution in the light of today's climate and energy challenges. Indeed, the use of plant-based aggregates in the construction sector helps to improve both energy and environmental efficiency. However, the use of bio-based aggregates as loose-fill insulation remains limited despite the wide availability of raw materials (agricultural by-products or wild plants) and their easy implementation. One of the problems is the diversity of resources that complicates both characterization procedures as well as the understanding and prediction processes of bio-material behaviors. One way to overcome these obstacles is to offer a unified method which is applicable to a wide range of plant-based aggregates. This is the purpose of the following study with the prediction of the thermal conductivity of bulk aggregates. This paper initially focuses on the particle scale in order to identify commonalities across a wide range of aggregates. Based on a multi-scale study, then distinguishes two different types of particulate morphologies. Particulate values of thermal conductivity - unavailable in the literature - can thus be provided over the full range of temperature and relative humidity conditions. A linear relationship between thermal conductivity and density is suggested at the particle scale while this type of relationship was previously known at the material scale. This work will also demonstrate the possibility of anticipating and offering equivalent insulation performances depending on the local resource available for loose-fill insulation cases.

Artificial Neural Network based FACTS in a Contingency Situation

The two biggest issues facing today's energy management systems are the ongoing monitoring of online voltage stability and the improved loadability of the transmission lines for the current electrical power system. As a result, it is highly difficult and time-consuming to assess online voltage stability under diverse loading conditions. This study describes a practical voltage stability monitoring system that automates online voltage monitoring and alerts the operator before voltage drops by computing line voltage stability indices using an ANN. This study compares evaluations of system voltage stability and loadability at the load with FACTS devices. The results suggest increase in system loadability while ensuring the security of power system operation.

Solar architecture: Significance and integration of technologies

Solar architecture is an innovative approach to building design and construction that focuses on integrating solar technology with architectural design. Solar-integrated architecture includes both passive and active use of solar energy. Due to the impact of global warming, today's energy environment is changing significantly from the usage of fossil fuels to the production of clean energy on-site. Buildings and the construction sector are responsible for almost a third of the world's total energy consumption and are the primary source of greenhouse gas emissions. Solar energy as a source of inexhaustible energy represents the future of modern sustainable buildings. This article deals with the basic principles and overview of solar architecture and analyses its impact on the environment. The paper includes the advantages of solar architecture, influencing factors, the latest technological innovations, practical aspects of implementing solar solutions, and examples of successful world projects. The paper aims to provide a comprehensive and informed overview of solar architecture and available solar technologies and solutions. Last but foremost, emphasize the importance of this issue in existing but especially in future designs of energy-efficient buildings.

Facile synthesis and electrochemical analysis of TiN-based ZnO nanoparticles as promising cathode materials for asymmetric supercapacitors.

In today's energy landscape, the rise of energy crises spurred by rapid industrial expansion demands the development of advanced energy storage systems, especially those leveraging renewable sources independently. Pseudocapacitors, renowned for their high specific capacitance (C s), offer a promising solution. Among them, transition metal nitride-based oxides stand out because of their remarkable conductivity and storage capacity, making them ideal candidates for supercapacitor (SC) cathode materials. In a recent study, we employed a wet-chemical method to synthesize a TiN-ZnO composite, showing potential as an electrode material for supercapacitor systems. The resulting composite exhibited promising crystallinity, indicating its suitability for electrode applications. Impressively, the TiN-ZnO electrode demonstrated a specific capacitance (C s) of 469 F g-1 during electrochemical testing. Additionally, it showcased a high energy density (E d) of 19.83 W h kg-1 and a power density (P d) of 6298.2 W kg-1. Moreover, it displayed exceptional cycling stability, retaining 95% of its performance over 7500 cycles. With superior electrochemical properties compared to pure materials, the fabricated TiN-ZnO electrode holds significant promise for supercapacitors and other energy-related technologies. This advancement presents a compelling solution to the urgent need for efficient and sustainable energy storage in the modern era.

Multi-objective optimization of cycle time and robot energy expenditure in human-robot collaborated assembly lines

The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has convinced many industries to shift towards semi-automated assembly lines with human-robot collaboration (HRC). In the HRC environment, robot agility can support human skill upon efficiently balancing tasks among the stations and operators. On the other hand, the robot energy consumption in today's energy crisis area demands that tasks be performed with as little energy utilization as possible by robots. In this context, the cycle time (CT) and total energy cost (TEC) of robots are among two conflicting objectives. Thus, this study balances HRC lines where a trade-off between CT and TEC of robots is sought. A mixed-integer linear programming model is proposed to formulate the problem. In addition, a multi-objective optimization approach based on ε-constraint is developed to address a case study from the automotive industry and a set of generated test problems. The computational results show that promising Pareto solutions in terms of CT and TEC can be obtained using the proposed approach.