Efficient Use Of Energy Research Articles

Literature Review on The Whole Life Cycle Assessment of Passive Buildings in The Context of Dual Carbon Emissions

With the increasing global demand for sustainable buildings, passive building design has become an area of concern. The design concept of passive buildings is known for its efficient energy use and excellent indoor environmental quality. However, there is a need to delve deeper in order to fully assess the economics and sustainability of passive buildings. The whole life cycle management of passive buildings is a relatively new management concept, and the evaluation research of the whole life cycle of passive buildings under the dual-carbon target is still limited. This paper reviews the evaluation methods and criteria based on the whole life cycle of passive buildings. The literature review includes research conducted over the past two decades and will focus on evaluation indicators for passive buildings. Many reviews present evaluation indicators for low energy design in the full life cycle evaluation of passive buildings and discuss future design directions. This literature review serves as a preliminary step to guide the evaluation criteria of passive buildings in light of China's two-carbon target, which will help to enrich the evaluation indicators of passive buildings and promote the transition to high-quality development of passive buildings.

Machine learning-based predictive model for thermal comfort and energy optimization in smart buildings

In the current context of energy transition and increasing climate change, optimizing building performance has become a critical objective. Efficient energy use and occupant comfort are paramount considerations in building design and operation. To address these challenges, this study introduces a predictive model leveraging Machine Learning (ML) algorithms. The model aims to predict thermal comfort levels and optimize energy consumption in Heating, Ventilation, and Air Conditioning (HVAC) systems. Four distinct ML algorithms Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), and EXtreme Gradient Boosting (XGBOOST) are employed for this purpose. Data for the model is collected using a network of Raspberry Pi boards equipped with multiple sensors. Performance evaluation of the ML algorithms is conducted using statistical error metrics, including, Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R2). Results reveal that the RF and XGBOOST algorithms exhibit superior performance, achieving accuracies of 96.7 % and 9.64 % respectively. In contrast, the SVM algorithm demonstrates inferior performance with a R2 of 81.1 %. These findings underscore the predictive capability of the RF and XGBOOST model in forecasting Predicted Mean Vote (PMV) values. The proposed model holds promise for enhancing occupant thermal comfort in buildings while simultaneously optimizing energy consumption in HVAC systems. Further research could explore the practical applications of these findings in building design and operation.

Assessment of health consequences of fossil fuel energy use in Osun state, Nigeria: burden and implications

The use of fossil fuel energy persists in all the continents of the world, especially in Africa. This study examined fossil fuel energy usage and its health implications in residents of Osun State, Nigeria. This was a cross-sectional study done across Osun State Nigeria. The study took place between January and June 2020. 1044 participants were recruited by multi-stage random sampling. Structured questionnaires were used to obtain necessary information from the study participants. The study data shows there were 534 females (51.1%). 601 (57.6%) relied solely on fossil fuel energy compared to 443 (42.4%) who use non-traditional energy sources. The proportion of people whose annual income is less than 56.6 USD (fifty thousand Naira based on the current official exchange rate as of Jan 2024) is far higher among those who use fossil fuel energy (88.0%) compared to those who use modern energy (59.1%). Electricity consumption accessibility was also more likely among those who used modern energy (91.9%) compared to 52.4% of those who use fossil fuel energy for daily energy needs. Reports of ill-health were significantly commoner among those who used fossil fuel than modern energy in the population including asthma illness (15.3% vs. 11.3%), cough (21.1% vs. 16.7%), catarrh (19.3% vs. 10.8%) and difficulty in breathing (9.3% vs. 6.3%) respectively. This study showed that fossil fuel energy use is very prevalent among residents of Osun State, Nigeria. And may be linked with many indices of poverty. It is associated with significant health impacts including respiratory diseases and poor quality of life. There is a need to encourage and implement policies toward effective and efficient energy use among residents in Osun State to reduce the associated long-term health impact.

Planting and Harvesting Mechanization on Productivity, Energy Efficacy and Profitability of Potato Production

Potato occupied the first position among all the vegetables in respect of area and total production in Bangladesh. Effective and efficient use of energy are necessary for an improved agricultural production. Therefore, this research was undertaken for potato production to assess productivity, quantify energy flow and financial profitability of different production systems. The experimented four systems were manual planting and manual harvesting, machine planting and manual harvesting, manual planting and machine harvesting and machine planting and machine harvesting, respectively. The experiment was conducted at Farm Machinery and Postharvest Process (FMP) Engineering Division of Bangladesh Agricultural Research Institute (BARI) during 2017-18. Yield of potato including yield contributing characters for different treatments was not significantly varied. Direct energy was the highest in mechanical planting and harvesting system (25%) and the lower manual planting and harvesting system (18%). Indirect energy shared 82% in manual planting and harvesting system, 78% in machine planting and manual harvesting system, 80% in manual planting and mechanical harvesting system, and 75% in machine planting and machine harvesting system, respectively. The largest source of indirect energy consumption was from fertilizer (22-27% of the total energy). The higher specific energy of 1.93 MJ/kg was found in manually planted and mechanized harvesting system. The higher product value was from manual planting and mechanical harvesting system. The highest BCR (2.25) was found from machine planted and machine harvested followed by manually planted and mechanically harvested plot (2.16), machine planted and manually harvested plot (1.93) and manual planting and harvesting plot (1.91). Thus, mechanically planted and harvested system can be recommended for potato production since it can reduce 52% labour requirement than manual method and can give higher BCR among the tested production methods.

Research on Establishment and Application of Evaluation System of Urban Energy Strategy Development Indicators under the Perspective of Carbon Neutrality

A scientific, comprehensive and integrated assessment of urban energy development is of great significance for the establishment of a clean, low-carbon and efficient urban modern energy system. From the perspective of carbon neutrality, this paper sets 25 evaluation indicators in seven dimensions: energy supply, energy consumption, energy efficiency improvement, clean and low-carbon, safety and reliability, low-carbon transport, and scientific and technological innovation, and constructs a secondary indicator system for evaluating the strategic development of urban energy. The system adopts the hierarchical analysis method to determine the weights of the indicators, the double-baseline progression method to standardize the indicator scores, and finally the weighted composite index method to calculate the level of urban energy strategy development. This paper applies the index system to evaluate the current energy development status of Wenzhou city in 2020 and 2022, and to predict the energy strategy development in 2025 and 2030. The scores of Wenzhou city's urban energy strategy development level in the corresponding four periods are 63.56, 70.59, 77.87 and 85.06, indicating that by 2023, Wenzhou city's urban energy development level will go from medium development to high development. Wenzhou City should accelerate the proportion of renewable energy in the future. It is necessary to complement multiple energy sources and improve the integration of heat, electricity, gas and cold. In terms of end consumption, it is necessary to improve the efficiency of energy use, reduce energy intensity, implement electric energy substitution and form an energy consumption pattern centered on electricity.

Low-carbon economic dispatch of hydrogen-containing integrated energy system considering stepped demand response

Vigorously developing an integrated energy system (IES) centered on the utilization of hydrogen energy is a crucial strategy to achieve the goal of carbon peaking and carbon neutrality. During the energy conversion process, a hydrogen storage system releases a large amount of heat. By integrating a heat recovery mechanism, we have developed a sophisticated hydrogen energy utilization model that accommodates multiple operational conditions and maximizes heat recovery, thereby enhancing the efficiency of energy use on the supply side. To harness the potential of load-side response, an integrated demand response (IDR) model accounting for price and incentives is established, and a ladder-type subsidy incentive mechanism is proposed to deeply unlock load-side response capacity. Considering system economics and low carbon, an IES source-load coordinated optimal scheduling model is proposed, optimizing source-load coordinated operation for optimally integrated economy, factoring in reward and punishment ladder-type carbon trading. Demonstrations reveal that the proposed methodology not only improves the efficiency of energy utilization but also minimizes wind energy wastage, activates consumer engagement, and reduces both system costs and carbon emissions, thus proving the effectiveness of our optimization approach.

Design of CoN/ZIS heterojunction with yolk-shell structure for impressive photocatalytic H2 evolution promoted by the photothermal effect

Non-precious metal catalysts are the best choice for efficient use of solar energy and cost reduction. In this work, a non-noble metal catalyst with a yolk-shell structure CoN/SiO2 (CNS) was prepared and recombined with ZnIn2S4 (ZIS). The H2 evolution of CNS/ZIS was 17.168 mmol/h/g, meanwhile, the apparent quantum efficiency (AQE) was 20.69 %. The yolk-shell structure of CNS/ZIS greatly improves the catalytic stability, and the H2 evolution efficiency of four consecutive experiments can still reach 94 % for the first time. There are several reasons for the outstanding performance of CNS/ZIS catalysts: (1) The yolk-shell structure improves light absorption and creates numerous reaction sites. (2) The internal electric field formed by the heterostructure promotes the migration of carriers. (3) The photothermal effect accelerates catalytic kinetics and promotes H2 precipitation.

Study on the Structure, Efficiency, and Driving Factors of an Eco-Agricultural Park Based on Emergy: A Case Study of Jinchuan Eco-Agricultural Park

The eco-agricultural park is a new comprehensive agricultural technology system integrating agricultural production, rural economic development, ecological environment protection, and efficient resource utilization. Therefore, an in-depth analysis of the ecosystem structure of eco-agricultural parks will help achieve the goal of coordinated symbiosis between human development and environmental protection. This study takes the research area of the Eco-agricultural Park of Jinchuan Town, Huinan County, a typical town in the Changbai Mountains of Northeast China. Based on field surveys, market research, farmer consultation, and related data collection, emergy theory and methods are used to construct an emergy model for the park. The value evaluation index system integrates the unique emergy index of the agricultural ecosystem with the traditional emergy index system to conduct a targeted evaluation of the park’s functional structure and sustainable development capabilities in order to improve the efficiency of material and energy use and provide technical reference for ecological construction and comprehensive development of agricultural industry in mountainous areas in northern China. The research results show that: (1) The annual input total emergy of the eco-agricultural park is 4.04E+24 sej/a, and the emergy of labor input, electricity input, and topsoil loss is relatively high. The park is in a labor-intensive stage. The annual output total emergy is 5.09E+24 sej/a, the park is dominated by planting and forestry industries. (2) The park’s emergy utilization intensity is high—production efficiency is high, economic development is advanced, and the system’s self-control, adjustment, and feedback functions are vital—and plays a significant role in promoting the development of the regional economy. However, the park relies more on investment from external resources, and production in the park puts pressure on the environment. (3) The current sustainable development capability of the study area is weak, and the factors affecting the sustainable development capability are mainly energy loss and uneven distribution of industrial areas in the park. Effective measures to promote the transformation of the park to develop technology-intensive industries and improve the sustainable development performance of the park were proposed. These include: adjusting the proportion of industries in the park; reducing high-energy external input emergy, such as industrial auxiliary emergy; reducing the loss of non-renewable natural resources through ecological engineering measures, such as reducing the depth of slope runoff in the park; and combining modern resource-based production technology and environmentally sound management methods to reduce energy loss and rational use of natural resources.

Predictive machine learning in optimizing the performance of electric vehicle batteries: Techniques, challenges, and solutions

AbstractThis research paper explores the importance of optimizing the performance of electric vehicle (EV) batteries to align with the rapid growth in EV usage. It uses predictive machine learning (ML) techniques to achieve this optimization. The paper covers various ML methods like supervised, unsupervised, and deep learning (DL) and ways to measure their effectiveness. Significant battery performance factors, such as state of charge (SoC), state of health (SoH), state of function (SoF), and remaining useful life (RUL), are discussed, along with methods to collect and prepare data for accurate predictions. The paper introduces an operation research model for optimizing the performance of EV Batteries. It also looks at challenges unique to battery systems and ways to overcome them. The study showcases ML models' ability to predict battery behavior for real‐time monitoring, efficient energy use, and proactive maintenance. The paper categorizes different applications and case studies, providing valuable insights and forward‐looking perspectives for researchers, practitioners, and policymakers involved in improving EV battery performance through predictive ML.This article is categorized under: Technologies > Classification Fundamental Concepts of Data and Knowledge > Explainable AI Technologies > Machine Learning

A value-based framework from Building Stock Model to Retrofit Model

The study has as its original database the decarbonization process initiated in Mexico by the National Commission for the Efficient Use of Energy (CONUEE) as part of its “Savings Program of Electric Power in Buildings of the Federal Public Administration” (PAEIAPF) of 1999. The primary purpose of PAEIAPF was to reduce the levels of electric power consumption in Federal Government buildings. The program has operated for 20 years; however, its scope only reaches operational carbon. Since 90% of existing buildings will be in use by 2050, the Retrofit Models will be the base to determine solutions for a more resilient living environment that fortifies and extends the grid’s capacity and meets climate change mitigation targets. Secondly, significant socioeconomic and profound environmental impacts are not calculated explicitly in existing tools and are often referred to as “secondary” or Non-Energy Benefits (NEB). “The goal is to give them a measurement value to be considered in the decision-making calculus. It is assumed that soon; such factors will enter the general climate change economy, not unlike carbon in the past decade.” In this context, the proposed research aims to develop a value-based framework that will support a Building Stock Model and subsequent Retrofit Models, documented in a web-tool platform. The framework has three main steps:A) Building Stock Model: Mapping of selected buildings of the program PAEIAPF in a GIS system. Documentation of the baseline energy consumption and embodied CO2-eq of the existing building.B) Retrofit Models: Involving a Whole Life Cycle Assessment (WLCA) and Non-Energy Benefits (resilience coefficient, health, productivity).C) Web Tool Platform: Application and toolset that allows for consistent documentation, environmental impact evaluation of existing building stock, and solution design in identifying energy reduction concepts.

A Topology Control Algorithm Taking into Account Energy and Quality of Transmission for Software-Defined Wireless Sensor Network

The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for softwaredefined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the Max Power algorithm in terms of average node degree and energy expansion ratio.

An Experimental Analysis of Three-Phase Low-Voltage Power Factor Controllers Used in a Deforming Regime

In industry, to improve the power factor in low-voltage power substations, a power factor controller (the most used method) can be installed which connects capacitors banks (connected, or not, with coils) in the electrical installation. The most important parameters of power engineering are the power factors that indicate the efficiency of energy use. Currently, many non-linear consumers (more single-phase than three-phase) are used on low voltages. Harmonics (currents and/or voltages) are the most important dynamic component of power quality, affecting electrical equipment performance and also reducing power factors. The purpose of this analysis is to increase the displacement power factor and to decrease the total harmonic distortion (for the current) in the conditions where there are linear and non-linear consumers, where the power factor must be improved with capacitors banks. Relevant different consumers have been selected for both the industry and the home sector, as follows: inductive motors that are linear, inductive consumers, compact fluorescent lamps that are non-linear, and capacitive consumers. This analysis was carried out depending on the number of steps used for the power factor controller, the values of the capacitors banks, the AC reactor (connected in series with all consumers), and the LC shunt filters. For a slight deformation regime, a large number of capacitors banks with different values ensure a finer adjustment of the displacement factor. The maximum number of steps that regulators can command should not necessarily be used (the reliability of the installation decreases with the increase in the number of capacitors banks), but a reduced number of steps can be used, which can lead to higher values of displacement power factors. To improve the deforming regime and to increase the displacement power factor, the use of LC shunt filters, connected to a small number of steps, will also increase the displacement power factor (over 0.9) and decrease the total harmonic distortion (up to 7–10%) for the current. Weaker results were obtained with AC reactors connected to the power supply phases of consumers and, if a larger number of stages were used, to which LC shunt filters were connected, these filters become difficult to calibrate (resonances occur).

Aspects Regarding of Passive Filters Sustainability for Non-Linear Single-Phase Consumers

The efficient use of electrical energy (an important component of sustainability) has become increasingly important for electrical consumers (industrial and non-industrial) as we face the challenges of climate change and the need to protect the environment. This theme is essential for guaranteeing a secure and sustainable future for both present and future generations. The power quality and the efficiency of electrical energy are connected to each other. Some power quality problems are caused by natural and unpredictable events, but many disturbances affecting power quality are caused by suppliers and consumers. One of the most important parameters in power engineering is the power factor, which indicates the degree of efficient use of electrical energy. Harmonics is the most important dynamic component of power quality, which affects the operation of electrical equipment and, at the same time, reduces the power factor. Harmonic sources in power systems are generally associated with nonlinear loads. To analyze the operating of passive filters (series L, shunt LC, T type LCL), two groups of experiments (relevant consumers were chosen for the industry as well as from the household sector) were carried out with single-phase nonlinear consumers: in the first group of experiments, a variable-frequency drive is used to supply a three-phase induction motor with variable load; in the second group of experiments, compact fluorescent lamps and LED lamps were used. Following the experiments, it was found that the difficulty of calibrating coils (to size a filter), especially the coils with a core, and the change in electrical properties over time for capacitors. For a certain type of consumer, the improvement of the current waveform depends on the type of filter used, the possibility of improving the power factor (to use electrical energy efficiently), and the role of the source impedance, which is particularly important to improve the efficiency of passive filters. Through the appropriate choice of the passive filter, a decrease in the deforming regime is obtained, with a slight decrease in the active power, and by increasing the power factor, a decrease in the losses of electrical energy from the electrical networks is obtained, with direct implications for the emission of greenhouse gases.

Optimizing Nutrient and Energy Efficiency in a Direct-Seeded Rice Production System: A Northwestern Punjab Case Study

This study was carried out in Amritsar, Punjab, to find out how efficiently nutrients were used and how much energy was employed in direct-seeded rice (DSR) production. In this study, four levels of nitrogen (0, 40, 50, and 60 kg N ha−1) and three levels of phosphorus (0, 37.5, and 45 kg P2O5 ha−1) were tested. In a rice production system, the energy indices of various inputs and outputs were evaluated through the application of energy equivalency. The nutrient-use efficiencies in rice were assessed using different efficiency indices. The maximum grain yields of 38.9 q ha−1 and 36.9 q ha −1 were recorded at 50 kg N ha−1 and 45 kg P2O5 ha−1, respectively. On the other hand, application of nitrogen at 60 kg N ha−1 and phosphorus at 45 kg P2O5 ha−1 resulted in maximum straw yield of 57.1 q ha−1 and 51.1 q ha−1, respectively. In comparison with the control, application of 60 and 50 kg N ha−1 resulted in 161.9% and 151.0% higher grain yield, respectively. On the other hand, with applications of 45 kg P2O5 ha−1 and 37.5 kg P2O5 ha−1, an increase in the grain yield of 17.3 and 28.6%, respectively, over the control was recorded. Moving further towards nutrient-use efficiencies (NUEs), the highest values of partial factor productivity of nitrogen (PFPN), agronomic efficiency of nitrogen (AEN), partial nutrient balance of nitrogen (PNBN), and recovery efficiency of nitrogen (REN) were 89.1, 50.4, 1.78 and 0.72, respectively, which were obtained at 40 kg N ha−1, after which the values started decreasing steadily. In the case of phosphorus, the partial factor productivity (PFPP) of 88.6 was the maximum at 37.5 kg P2O5 ha−1, but partial nutrient balance (PNBP) of 0.36 and recovery efficiency (REP) of 0.08 were highest at 45 kg P2O5 ha−1. The main results revealed that the farmer field had an excessive amount of non-renewable energy inputs. The experimental field depicted greater energy-usage efficiency (EUE) of 4.5, energy productivity (EP) of 0.14, and energy profitability (EP1) of 3.5. These results were primarily ascribed to a significant drop in energy inputs under direct-seeded rice (DSR). In the case of non-renewable energy inputs, fertilizer made the maximum contribution to energy input (47.9%) in the farmer’s field. We conclude that nutrient-use efficiencies and energy-use efficiency were highest at 50 kg N and 45 kg P2O5 ha−1. This recommendation is beneficial for farmers because lower inputs and higher outputs are the main objective of every farmer.

Assessing energy fluxes and carbon use in soil as controlled by microbial activity - A thermodynamic perspective A perspective paper

Soil organic matter (SOM) plays a central role for both the C cycle and soil functions. Plants provide the input and heterotrophic (micro)organisms are essential for the turnover. Microbial metabolism links matter and energy fluxes and generates the highest energy turnover dynamics in SOM because the organisms need both energy and matter for maintenance and growth. In this perspectives paper, we evaluate the knowledge on thermodynamic approaches potentially applicable to study the turnover of organic matter in the soil system. Thermodynamics is essential for understanding organic matter turnover in soil as turnover and storage are controlled by the energy supply to, and consumption by, microbes. Instead of just comparing the heat of combustion of compounds without considering microbial anabolism, we need to apply conventional thermodynamic state variables that can be either estimated using established thermodynamic equations, or measured empirically in soil. In particular, we can follow and quantify overall changes of enthalpies by calorimetry. Here, we suggest to apply a thermodynamic concept with the related experimental approaches of calo(respiro)metry and turnover mass balances including biomass formation. This enables us to better interpret and understand the highly variable carbon use efficiency (CUE) in a multi-substrate system such as soil and to relate this to energy use efficiency (EUE). Combining the experimental measurements of the thermodynamic state variables with mass turnover data allow prediction of whether compounds can be metabolized with energy delivery to microorganisms, or be thermodynamically stabilized under the respective redox and electron acceptor conditions. Energy balancing shows how much energy is actually used and retained in the soil, how much is emitted as heat, and how much may be stabilized due to endergonic turnover reactions. Thermodynamic stabilization should therefore be considered as basic stabilization process for organic compounds in soil.

Disentangled Seasonal-Trend representation of improved CEEMD-GRU joint model with entropy-driven reconstruction to forecast significant wave height

In recent years, wave energy has gained popularity among marine researchers for its sustainability, cleanliness, high energy density and wide distribution. As one of the most important parameters of wave energy, Significant Wave Height (SWH) is difficult to predict accurately due to complex sea conditions and the ubiquitous chaotic phenomena in nature. The efficient use of wave energy cannot be achieved without accurate analysis and prediction of SWH. In this study, a novel DST-CEEMD-SampEn-GRU joint model is proposed, which combines Disentangled Seasonal-Trend (DST) to reduce the computational time of the Complementary Ensemble Empirical Mode Decomposition (CEEMD). This is combined with SampEn-based reconstruction to avoid the tremendous computational effort associated with IMF components of CEEMD. The final prediction is made using the Gate Recurrent Unit (GRU). In this paper, we demonstrate the effectiveness of CEEMD, SampEn and DST in improving accuracy through forward ablation experiments respectively. Finally, the proposed model is validated with multi-single machine learning models for muti-hour ahead SWH forecasting. The experimental results demonstrate that DST-CEEMD-SampEn-GRU is statistically superior to all the other methods.

Study on Multivariable Dynamic Matrix Control for a Novel Solar Hybrid STIGT System

To construct a clean and efficient energy system, advanced solar thermal power generation technology is developed, i.e., a solar hybrid STIGT (Steam Injected Gas Turbine) system with near zero water supply. Such a system is conducive to the efficient use of solar energy and water resources, and to improvement of the performance of the overall system. Given that the strong correlation between multiple-input and multiple-output of the new system, the MDMC (Multivariable Dynamic Matrix Control) method is proposed as an alternative to a PID (Proportional-Integral-Derivative) controller to meet requirements in achieving better control characteristics for a complex power system. First, based on MATLAB/Simulink, a dynamic model of the novel system is established. Then it is validated by both experimental and literature data, yielding an error no more than 5%. Subsequently, simulation results demonstrate that the overshoot of output power on MDMC is 1.2%, lower than the 3.4% observed with the PID controller. This improvement in stability, along with a reduction in settling time and peak time by over 50%, highlights the excellent potential of the MDMC in controlling overshoot and settling time in the novel system, while providing enhanced stability, rapidity, and accuracy in the regulation and control of distribution networks.

Superhydrophobic Bulgy Windmill for Synchronous Efficient Fog Collection and Power Generation.

The shortage of freshwater resources is a serious problem faced by mankind in the 21st century. To maximize the acquisition of freshwater resources, numerous fog collectors have been constructed. In the process of fog collection accompanied by the movement of the wind, the mechanical energy brought about by the wind is often ignored. Based on this, inspired by beetles and origami art, we designed a windmill installation with a bump on the edge. Droplets nucleate at the windmill bulge and accelerate the transport process under the action of centrifugal force. This leads to quick fog collection and reduces the secondary evaporation rate of freshwater resources. The fog collection efficiency can reach 2.8 times that of the original sample. Moreover, the windmill can convert mechanical energy into electricity while collecting fog, and the operating voltage of a single windmill can reach 0.85 V. After the array, the amount of fog collected by the windmill and the power generation voltage can be increased by multiple times, which realizes the efficient use of energy and provides a new idea for the design of an efficient fog collector in the future.

Arduino Based Framework for Automatic Street Light Switching and Fault Detection System

ABSTRACT- The necessity for automated street lighting systems in India is underscored by the significant potential for energy savings, crucial for a country where efficient energy use is imperative. Research indicates that implementing LED street lighting could lead to an estimated 30% reduction in energy consumption, translating to a substantial electricity saving of approximately 2,326 GWh. LED technology, known for reducing energy usage by up to 80% compared to conventional lighting, offers a greener alternative that significantly lowers electricity demand. The adoption of energy- efficient lighting systems not only aids in diminishing energy consumption but also plays a vital role in environmental preservation by reducing CO2 emissions. Furthermore, integrating automatic controls in street lights, equipped with daylight sensors and adaptive solar panels, maximizes energy efficiency. These systems tailor lighting levels to real-time environmental conditions and activity, such as the presence of vehicles, thus optimizing power usage and minimizing waste. The extended lifespan of LED lamps, reaching up to 50,000 hours, further contributes to economic savings and a decrease in maintenance frequency, supporting ongoing conservation efforts. Therefore, the implementation of automated and energy- efficient street lighting in India is a pivotal step towards attaining energy conservation, economic benefits, environmental sustainability, and enhanced urban safety. This move towards innovative and sustainable lighting solutions positions India on a path to a brighter, more sustainable future.

Experimental study on heat-transfer characteristics of spray cooling for microchannel radiators

Spray cooling is an emerging and promising thermal-management solution with a wide range of applications. However, its application in engineering vehicles remains in the formative stage. In this study, an innovative spray-cooling system for engineering vehicles was proposed. The study, using thermocouples and visualisation methods, focused on how factors such as the spray angle, height, volume flow, nozzle aperture, and arrangement impact the uniformity of the surface temperature and heat-transfer enhancement. Optimal cooling was achieved using a spray angle of 60°, height of 90 mm, and flow rate of 500 l/h. Moreover, a nozzle aperture of 1.6 mm demonstrated superior efficiency in energy use and cooling. Higher temperature differentials (90–140 °C) enhanced the heat transfer but led to a 332.81 % increase in the non-uniformity of the surface temperature. Further, the study compared the spray-cooling efficiency between alumina nanofluids and deionised water. Alumina nanofluids with a 0.7 % mass fraction achieved a maximum heat-transfer coefficient of 450.6 W/(m2·K), 15.48 % higher than that of deionised water. Moreover, based on the experimental results, an empirical formula for enhanced heat transfer using spray cooling in construction machinery was developed, providing a valuable reference for guiding engineering practice. The proposed spray-cooling method, which exhibited a two- to three-time improvement over traditional air-cooled systems, holds considerable promise in the field of engineering vehicle applications.