Energy Efficiency Of System Research Articles

OPTIMIZATION OF R744 CONTENT IN MIXTURES WITH R290, R600, R600A, R170 TO INCREASE THE ENERGY EFFICIENCY OF THE REFRIGERATION SYSTEM

This paper presents a general theoretical analysis of binary refrigerant blends based on R744 (carbon dioxide) in combination with certain hydrocarbons, including R290 (propane), R600 (butane), R600a (isobutane), and R170 (ethane). The main goal of the study was to determine the optimal molar ratios for each of the mixtures that maximize the coefficient of performance (COP), an indicator that characterizes the energy efficiency of the cooling system. In addition, the volumetric cooling capacity (qν) was analyzed, which is an important criterion for assessing the overall efficiency of refrigeration systems. The study analyzed the operation of refrigeration systems, taking into account both subcritical and supercritical conditions. As initial parameters for building a mathematical model, the boiling and condensation/heat removal temperatures were used, which were determined as the average values of the process temperatures in heat exchangers. This approach ensured accurate maintenance of the set temperature in the refrigerating chamber. The best results were obtained for R744/R600 and R744/R600a blends. R744/R600 in the proportion of 58.5/41.5 % has a COP 36.6 % higher than that of pure R600, and the volumetric cooling capacity increased by 10.2 times. Similarly successful results were demonstrated by the R744/R600a blend with an optimal ratio of 93/7 %, which showed a 39.2 % increase in COP and a 16.8-fold increase in volumetric cooling capacity compared to pure R600a. However, the study showed that the use of a R744/R290 blend was less efficient due to relatively lower COP and volumetric cooling capacity compared to pure R744. Similar conclusions were drawn for the R744/R170 blend, which also demonstrated lower efficiency compared to pure R744. At the same time, it is noted that in most component ratios, the mixture operates in a supercritical mode. This indicates that it is inexpedient to use such refrigerant blends at the given initial parameters to improve energy efficiency. This result emphasizes the importance of careful selection of blend components to achieve optimal performance. Overall, the study results demonstrate that the use of R744 blends with R600 and R600a can be a promising alternative to improve the energy efficiency of refrigeration systems. Optimization of the molar fractions can achieve a significant improvement in COP and a significant increase in volumetric cooling capacity, making such blends promising candidates for practical use. However, further development of an in-depth mathematical model that will be close to real operating conditions, as well as experimental studies to verify the actual performance of these blends and identify possible limitations of their use, are required to confirm these conclusions.

Development of an energy-efficient cctv camera system for real-time human detection using YOLOv8 model

Human recognition is widely used in variety of fields such as autonomous vehicles, surveillance field, automatons, assisting blind peoples and many more. Many machine learning (ML) and deep learning (DL) algorithms exist for video analysis the main motive of these algorithms is to find human in complicated image. The research presented in this paper focuses on the development of an energy-efficient, smart CCTV camera system for real-time human detection, utilizing the YOLOv8 (You Only Look Once) model. The problem addressed is the need for more advanced, autonomous surveillance systems capable of human detection under various background conditions, overcoming the limitations of traditional CCTV systems, which require constant manual monitoring. The proposed system was trained on the PASCAL VOC 2012 dataset and optimized through hyperparameter tuning, achieving high accuracy and real-time performance. Key results demonstrate that the YOLOv8 model, implemented on the NVIDIA Jetson Nano platform, offers remarkable accuracy, precision, and energy efficiency. It consistently detects human figures in real-time, even in non-ideal conditions like poor lighting or complex backgrounds. This success can be attributed to YOLOv8’s cross-stage partial network (CSPNet) architecture, which enhances its ability to process images quickly and accurately, ensuring it meets the demands of continuous surveillance. The distinguishing features of this system are its energy-efficient design and adaptability to diverse environmental conditions. These characteristics not only solve the challenge of real-time human detection but also make the system a robust and scalable solution for modern security and surveillance applications

Hybrid MWGSO: Developing Hybrid Heuristic Algorithm for Energy Efficient D2D Communication System with Optimal Resource Allocation

Hybrid MWGSO: Developing Hybrid Heuristic Algorithm for Energy Efficient D2D Communication System with Optimal Resource Allocation

Исследование работы инверторной системы запуска дизельного двигателя при эксплуатации тепловоза 3ТЭ28

Purpose: carrying out operational tests of the start converter as a device of the preliminary diesel engine cranking of a diesel locomotive 3TE28 and the analysis of the obtained results. Methods: the functioning of the inverter starting system was studied within the framework of its operation as part of a diesel locomotive under different conditions of diesel engine starting (battery residual voltage, oil temperature) using a measuring complex and a set of additional sensors, as well as accumulation and analysis of the obtained measurement results. Results: operational tests of the inverter system of the start power plant on the diesel locomotive 3TE28 in locomotive depot “Tynda-Severnaya” were carried out. The circuit solutions and algorithms of the automatic control system of the inverter are verified. Comparative analysis of energy efficiency of inverter and starter-generator engine start systems is performed. Practical relevance: according to the results of operational tests the possibility of application of start converters for reliable diesel engine starts of diesel locomotives equipped with synchronous traction units instead of widespread nowadays starter-generator starting systems is confirmed. The developed technical solution can be duplicated on other series of locomotives, both newly developed and operated as part of their modernization or repair. The data accumulated in operation can be used for further improvement of the control system algorithms of the start converter.

Multi-stage algorithm for energy efficiency and data rate trade-off in imperfect CSI downlink NOMA systems

Multi-stage algorithm for energy efficiency and data rate trade-off in imperfect CSI downlink NOMA systems

Development of Energy Efficient Domestic Hot Water Loop System Integrated with a Chilled Water Plant in Commercial Building

This study investigates a novel approach to reduce energy consumption in large commercial buildings by recovering waste heat from the condenser of a chiller and utilizing it to preheat domestic hot water (DHW). While numerous energy-saving strategies have been developed for building heating and cooling systems, the energy efficiency of DHW systems has lagged behind due to the increasing demand for hot water driven by improving living standards and hygiene concerns. By integrating a heat exchanger between the chiller and the DHW system, the proposed system effectively improves the chiller’s performance and significantly reduces the energy consumption of the DHW heater. Simulation results demonstrate that during the cooling season (June–August), the chiller achieved a 3% reduction in energy consumption, while the DHW heater experienced energy savings exceeding 70%. Additionally, the operating frequency of the DHW heater was substantially decreased. Notably, despite the significantly higher energy consumption of the chiller compared to the DHW heater, the reduction in greenhouse gas emissions from the DHW heater accounted for more than 50% of the total reduction. This finding highlights the significant contribution of energy savings in the natural gas-fired DHW heater to improving the building’s overall sustainability.

Architecting Ultra-Robust Zr(IV) Metal-Organic Framework for Energy-Efficient Desiccant Air Conditioning.

Air-conditioning systems, composed mainly of humidity control and heat reallocation units, play a pivotal role in upholding superior air quality and human well-being across diverse environments ranging from international space stations and pharmacies to granaries and cultural relic preservation sites, and to commercial and residential buildings. The adoption of sorbent water as the working pair and low-grade renewable or waste heat in adsorption-driven air-conditioning presents a state-of-the-art solution, notably for its energy efficiency and eco-friendliness vis-à-vis conventional electricity-driven vapor compression cycles. Here, we introduce a rational π-extension strategy to engineer an ultrarobust and highly porous zirconium metal-organic framework (Zr-MOF). This MOF sorbent showcases hysteresis-free S-shaped water sorption isotherms, characterized by a rapid ascent within the 40-60% relative humidity range with a working capacity of 0.63 g g-1, thus facilitating intelligent indoor humidity regulation. Moreover, we demonstrate, for the first time, that this material with such distinctive isotherms can yield a 10 °C temperature lift between ambient and chiller output with a high cooling capacity of 336 kW h m-3 per cycle, even at exceptionally low driving temperatures (below 50 °C), while also delivering a substantial coefficient of performance of 0.96. This material is amenable to scale-up and is chemically ultrastable that can endure strong acids and be cycled for at least 200 runs without compromising any of its capacity. These exceptional attributes signify the viability of this material as a pragmatic alternative for deployment in energy-efficient desiccant air-conditioning systems, particularly in hot and humid climatic regions.

Response Surface Methodology for Modelling and Optimizing Efficiency in Deep Well Pumping Systems

This study presents research on modelling the efficiency and flow rate of deep well pumping facilities using the response surface method, evaluating the models, and assessing optimization based on target flow rate. Regression and variance analysis techniques have been successfully employed to evaluate the relationship between input factors (input pressure and power drawn from the grid) and responses (system efficiency and flow rate). ANOVA analysis has been used to examine the effects of linear and quadratic terms, and the results have shown that pressure and power drawn from the grid have a significant effect on pump system efficiency. Additionally, the performance of the regression models has been evaluated using error metrics such as R2 value, RMSE, and MAPE. These values for the pumping facility system efficiency model were found to be 0.9993, 0.292%, and 0.71%, respectively, and for the flow rate model, they were 0.9997, 0.69 m3h-1, and 1.07%. The results obtained demonstrate that the model operates with high accuracy and explains a large part of the variance in the response variables. An optimization study was conducted to maximize pump system efficiency by maintaining the flow rate at a certain target value. According to the experimental results obtained, the target flow rate was predicted with an error rate of 1.49%, and the pump system efficiency was predicted with an error rate of 2.14%. This study highlights the effective use of various analytical and experimental methods to improve the efficiency of pump systems. Future researchers are encouraged to conduct similar analyses on a larger scale and under different operating conditions. Furthermore, evaluating different optimization strategies to improve the energy efficiency of pump systems, which can lead to significant energy savings in industrial applications, is recommended.

A Multi-Area Illumination Adjustment Method based on Metro Passenger Flow

Lighting energy consumption in subway stations is an important part of energy consumption, and improving lighting energy efficiency in stations can effectively reduce overall energy consumption. The article proposes a multi-area, intelligent lighting control model based on passenger flow density to realize the dynamic adjustment of lighting intensity in each area, effectively enhance the energy efficiency of the subway lighting system and save subway operating costs. At the same time, this control model also helps to reduce energy consumption and carbon emissions, and promote the sustainable development of urban transportation.

Using frequency regulation to improve the energy efficiency of pumping units in switching circuits with a water tower

The development of the water supply system for small settlements involves the use of frequency converters and specialized control algorithms capable of maintaining the pressure level established in the network within certain limits. The implementation of one of the standard schemes involves decommissioning a water tower, which, on the one hand, allows reducing the cost of its maintenance, on the other hand, if the pump fails, the water tower provides a certain supply of water to the consumer, which increases the overall uptime. The paper considers the potential for increasing the energy efficiency of a water supply system when operating well pumps on a water tower through the use of frequency converters. The study has analyzed the operating conditions of more than 300 wells. This has made it possible to establish that most pumps have overestimated pressure values when lifting water into the tower (median excess of about 30 m). For the wells under study, optimization of the operating modes of the pumping units has revealed energy saving potential of up to 50 % by reducing excess pressure and up to 2.0 % due to a reduction in starting power at the moment of engine acceleration. An assessment of the energy saving potential based on similarity theory emphasizes that when the pump motor speed is reduced, it is important to take into account the reduction in its performance, which is a significant limitation in the design of automated control systems. The study results confirm the significant theoretical and practical potential of using frequency converters to improve the efficiency of water supply systems without the need to mothball water towers. The research provides a basis for further developments in the field of optimization and automation of water supply systems in order to achieve high energy efficiency.

Electric Aviation: Pioneering the Future through Advances in Electric Vehicle Technologies

This paper explores the technological advancements in electric vehicles (EVs) and their potential applications in electric aviation. Core EV technologies such as battery systems, electric motors, and electronic control systems are analyzed to understand their relevance to aviation. The evolution of various battery types, including lithium-ion, solid-state, and next-generation alternatives, is emphasized, focusing on their critical role in addressing energy density challenges that electric aircraft will face. Additionally, this paper discusses the technical, regulatory, and manufacturing hurdles that must be overcome for electric aviation to become commercially viable. From battery weight and endurance limitations to energy-efficient propulsion systems, the complexities of translating EV innovations to aviation are assessed. The paper concludes by examining future possibilities for electric aviation, highlighting how breakthroughs in EV technology could lead to sustainable air travel. Through this lens, the technological trajectory of EVs provides key insights into the opportunities and challenges of developing electric aircraft.

Solar-Driven Sulfide Oxidation Paired With CO2 Reduction Based on Vacancies Engineering of Copper Selenide.

Photovoltaic-driven electrochemical (PV-EC) carbon dioxide reduction (CO2R) coupled with sulfide oxidation (SOR) can efficiently convert the solar energy into chemical energy, expanding its applications. However, developing low-cost electrocatalysts that exhibit high selectivity and efficiency for both CO2R and SOR remains a challenge. Herein, a bifunctional copper selenide catalyst is developed with copper vacancies (v-CuSe2) for the CO2R-SOR. The Faradaic efficiency (FE) of 62.4% for methane at -200mA cm-2 is achieved in the cathodic CO2R. In a two-electrode CO2R-SOR system with 16 h of long-term operation at a current density of 200mAcm-2, an average Faradaic efficiency of 57.2% for methane and 97.7% for sulfur powder generation is achieved at cathode and anode, respectively. Compared to the coupling of CO2R with oxygen evolution reaction (OER), the energy efficiency (EE) of the CO2R-SOR system can be increased to 22.9%. The mechanism study has found that the synergistic effect of copper vacancies and introduced Se significantly enhances the selectivity toward methane. Driven by silicon solar cells, a solar-to-methane conversion efficiency of 2% is achieved.

The Decarbonizing Strategies of China’s Iron and Steelmaking Industry: A Comprehensive Perspective

Decarbonizing the iron and steelmaking industry is critical for China to pursue the net-zero emissions target and advance sustainable industrialization (SDG 9). This paper addresses the urgent need for decarbonization strategies in this sector, aiming to align with China’s carbon neutrality goals by 2060. By reviewing the current technological advancements and potential pathways for deep decarbonization, including process optimization, hydrogen-based direct reduction, and carbon capture, utilization, and storage (CCUS), these decarbonization technologies are categorized into six strategic approaches: systemic energy efficiency improvement, resource recycling, process optimization and innovation, breakthrough smelting, product iterative upgrading, and CCUS. These strategies also align with SDG 13 (climate action) by reducing greenhouse gas emissions and SDG 7 (affordable and clean energy) through the promotion of clean energy technologies. These strategies are evaluated for their emission reduction potential and technological maturity. The results indicate that, while efficiency improvements and resource recycling are currently the most mature and widely implemented strategy, significant breakthroughs in hydrogen metallurgy and CCUS are essential for achieving long-term carbon neutrality. Based on an analysis, a comprehensive roadmap is proposed, detailing the near-term to long-term actions required for the industry’s transition. The near-term focus (up to 2030) should be on enhancing energy efficiency and process optimization, whereas the mid-term (2030–2050) focus should emphasize the adoption of hydrogen-based technologies and CCUS. By the 2050–2060 period, the industry should achieve widespread commercialization of breakthrough smelting technologies and CCUS, ensuring the achievement of carbon neutrality. This study intends to provide a systematic framework and strategic recommendations for policymakers and industry stakeholders to guide the decarbonization of China’s iron and steelmaking sector, addressing both technological and economic challenges to achieve sustainable and low-carbon development.

Additive Manufacturing of a Frost-Detection Resistive Sensor for Optimizing Demand Defrost in Refrigeration Systems.

This article presents the development of a resistive frost-detection sensor fabricated using Fused Filament Fabrication (FFF) with a conductive filament. This sensor was designed to enhance demand-defrost control in industrial refrigeration systems. Frost accumulation on evaporator surfaces blocks airflow and creates a thermal insulating barrier that reduces heat exchange efficiency, increasing energy consumption and operational costs. Traditional timed defrosting control methods can mitigate these effects but often lead to inefficiencies due to their inability to align with actual frost accumulation, which can vary according to system and environmental conditions. Frost-detection sensors aim to solve this problem by acting as a tool to support defrosting control. A series of tests were conducted to evaluate the sensor's performance in detecting frost under controlled conditions on a heat exchanger (HX). The sensor reliably detected frost in all cases, demonstrating its effectiveness in real-time frost detection. The sensor measurements were validated by comparison with results obtained through a computer vision method, confirming its reliability. It was also found that the sensor can detect temperature changes. This advancement in sensor technology highlights the potential of additive manufacturing to provide cost-effective, customizable, replicable, and compact sensor designs, contributing to improved system performance and energy efficiency in refrigeration systems.

PV SYSTEM MPPT CONTROL: A COMPARATIVE ANALYSIS OF P&O, INCCOND, SMC AND FLC ALGORITHMS

The importance of solar energy is manifested in the growing demand for renewable energy sources around the world, which is fueled by environmental concern and the scarcity of conventional energy. Maximum power point trackers (MPPTS) are necessary in solar energy systems due to atmospheric changes that threaten the efficiency of solar energy systems. This article compares MPPT technologies. Including traditional and modern techniques, and despite the results achieved by classical techniques in maximizing and extracting as much energy as possible, they face a big problem in reaching the bone energy point. These provide modern technologies such as FLC and SMC. They provide exceptional accuracy and excellent response in all environmental conditions but come with additional complexity and higher cost. These technologies are ideal in applications that require high performance under continuously changing conditions or in difficult environments (such as large solar power systems or systems dealing with large fluctuations in illumination). This research aims to conduct a comprehensive study and compare of classical technologies (P&O and IncCond) and modern technologies sliding mode control (SMC, Fuzzy Logic Control – FLC), taking into account factors such as efficiency, complexity and response time. Tests were conducted under different climatic conditions to understand and enhance the efficiency of MPPT technologies. Our study highlights the enhanced performance for methods based on modern technologies. This study provides a comprehensive comparative analysis, and by improving the efficiency and reliability of solar energy systems, our research supports the advancement of sustainable energy solutions.

Secure Cluster Based Routing Scheme for Neuro‐Fuzzy Assisted MANET in 5G

ABSTRACTThe Fifth Generation (5G) of wireless networks has increasingly focused significantly on energy‐saving methods for mobile communication systems. The objective of combining MANET with 5G communication is to achieve a high data throughout while simultaneously reducing latency and cost. The main issues with MANET are elevated energy use, security, and reduced longevity. The self‐configuring characteristics and dynamic architecture of MANET may lead to frequent changes in topology and resource allocation. This mobility results in frequent connection failures, which increase routing overheads and decrease data transmission dependability. A secured clustering technique is essential to enhance the routing performance and establish reliable routing. In MANET, the cluster mechanism is the prominent way to improve the network lifetime and routing mechanism. The proposed secure cluster routing‐based neuro‐fuzzy logic (SCR‐NFL) establishes a secure cluster mechanism via the use of the Trust value method. It guarantees cluster stability by taking into account node mobility and energy while selecting cluster heads. The important components in the proposed system are Mobility (M), Residual Energy Level (REL), and Trust Value (TV). The neural fuzzy logic system is implemented to handle the data uncertainty and make effective decisions during routing path selections. The proposed SCR‐NFL performance is measured in an NS‐2 simulation environment. The result is compared with the existing Improved Particle Swarm Optimization Algorithm, Trust‐Based Secure Neuro Fuzzy Clustering mechanism and Mobility Aware Energy Efficient Clustering system using Particle Swarm Optimization mechanism. The performance parameters for comparison are packet delivery ratio, average number of clusters, end‐to‐end delay, average number of cluster instances, mobility speed and mobility distance.

A Pressure-Bearing Microwave Transmission Line for Rapid Energy-Efficient Manufacturing Systems of High-End Composite Parts

Currently, a 2-port microwave transmission line with a glass window is usually used to transmit microwave energy to a pressure vessel while sealing the high-pressure gas. In this situation, the damage of the brittle glass window will inevitably result in disastrous accidents. In this paper, the idea of a “2+4”-port microwave transmission line is first proposed to solve this problem. A 4-port waveguide bridge structure is connected to the input port of a traditional 2-port structure, which can release the high-pressure gas safely when the glass window of the 2-port microwave transmitting structure fails. To test this idea, a “2+4”-port microwave transmission line at 2.45 GHz was designed and fabricated. The effectiveness of the whole system in microwave transmission was validated by both simulations and experiments. A high microwave transmittance of more than 97% in the simulation and 91% in the experiment was achieved. The long-time transmission of 15-kW microwave energy, 5 times higher than the previous work, was realized. Moreover, the effectiveness of the transmission line in releasing high-pressure gas (0.6 MPa) was validated by a series of fluid-structure interaction simulations. This research proposes a new transmission structure for transmitting microwave into a pressurized environment safely and efficiently, which can be promoted to a series of applications including vacuum electron devices, microwave ovens, and so on.

An Investigation into High-Accuracy and Energy-Efficient Novel Capacitive MEMS for Tire Pressure Sensor Application.

Tire pressure monitoring systems (TPMSs) are essential for maintaining driving safety by continuously monitoring critical tire parameters, such as pressure and temperature, in real time during vehicle operation. Among these parameters, tire pressure is the most significant, necessitating the use of highly precise, cost-effective, and energy-efficient sensing technologies. With the rapid advancements in micro-electro-mechanical system (MEMS) technology, modern automotive sensing and monitoring systems increasingly rely on MEMS sensors due to their compact size, low cost, and low power consumption. This study presents a novel high-precision capacitive pressure sensor based on a capacitive micromachined ultrasonic transducer (CMUT) structure and a silicon-silicon direct bonding process. The proposed design offers exceptional performance with high accuracy, ultra-low power consumption, and reduced production costs, making it an optimal solution for enhancing the precision and efficiency of TPMS. Leveraging its low power requirements, capacitive sensing technology emerges as a superior choice for energy-efficient systems in the automotive industry.

TRIPLE-OBJECTIVE OPTIMIZATION OF SUPERCRITICAL CO2 RECOMPRESSION BRAYTON CYCLE IN SOLAR TOWER SYSTEMS WITH ENERGY, EXERGY AND EXERGOECONOMIC ANALYSIS

This study addresses the energy, exergy and exergoeconomic analyses of the supercritical CO2 recompression Brayton cycle used in solar tower systems. In the study, a three-objective optimization model was developed using artificial neural networks (ANN) to optimize the system performance. The model provides information for the development of sustainable solar energy systems by providing analyses on key factors such as energy efficiency, environmental impact and economic viability. The results show that the supercritical CO2 cycle provides higher thermal efficiency compared to conventional systems and offers cost advantages by reducing the size of system components. In addition, the analyses show that energy and exergy losses can be minimized and the cost effectiveness of the system can be increased, providing important findings in terms of the efficiency and economic viability of solar energy systems.

Trends, prospects, challenges, and security in the healthcare internet of things

The Healthcare Internet of Things (H-IoT) is a rapidly developing problem solving model with significant potential to improve patient care and healthcare outcomes. This study focuses on integrating cryptographic platforms into H-IoT systems to enable secure data access. We present insights on how to manage challenges such as cyber risks, resource constraints, latency, and energy consumption by exploring cryptographic approaches in diverse H-IoT applications. We explore important topics including big data management, blockchain, machine learning, edge computing, and software-defined networks. Additionally, we examine real-time operational challenges and emerging trends, such as remote patient monitoring and predictive analytics. Our research underscores the need for strong encryption mechanisms, access controls, device authentication, and proactive threat detection to improve the safety and efficiency of healthcare services. By combining cryptographic approaches with the architecture of the H-IoT system, this work provides the foundation for resilient healthcare infrastructures. Addressing current challenges and anticipating future opportunities contribute to strategic healthcare planning that prioritizes patient privacy and data security while anticipating future strategic healthcare planning opportunities. This article aims to provide valuable information to researchers by covering energy-efficient and resource-optimized healthcare system approaches that are integrated into the development of H-IoT systems.