Calculation Of Energy Consumption Research Articles

Examining the Carbon Footprint of Conferences with an Emphasis on Energy Consumption and Catering

This research study presents a comparison of an in-person and an online conference in terms of environmental impact and energy efficiency. The main goal of our research was to prepare a complete life cycle assessment of a two-day (15-h), 200-participant in-person and online conference based on different impact assessment methods. Life cycle assessments focus on the numerical determination of the decarbonization of conference consumption (lunch, dinner, food and beverage consumption during breaks), conference organization (discussions, correspondence, abstract booklet, registration package), travel, and infrastructure. The meals were examined by connecting the stages of preparation, cooking, consumption and end-of-life cycle as a cradle-to-grave analysis. We paid particular attention to the calculation of energy consumption. After carbon footprint comparisons, the areas with the highest impacts with pie diagrams were identified. Lastly, a SWOT chart and an SAP-LAP analysis diagram summarize the achievable objectives and challenges. In conclusion, there is no outstanding difference between the impact assessment methods for the carbon footprint investigation. Travel contributes 57% of the overall carbon footprint at in-person conferences, while the environmental impact of meals holds the second largest share, at 8.41 kg CO2 equivalent/person/hour. Excluding meals and travel, the calculated carbon footprint is 0.362 kg CO2 equivalent/person/hour (only considering the effect of preparation, organization, administration and registration package). Our initial hypothesis was that an online conference reduces decarbonization, which the results confirm.

Identifying Practical Material Retrofit Measures for Energy Efficiency in Existing High-Rise Buildings in the Malaysian Climate

With the global focus on sustainable urban development, many cities are striving to formulate effective urban transformation strategies to transition from traditional urban structures to more sustainable ones. Enhancing the energy efficiency of buildings, particularly existing structures, is recognized as a crucial element in the fight against climate change. In the Malaysian context, improvements in energy consumption are predominantly propelled by retrofitting the country's existing building stock. However, targeted strategies are needed, especially for high-rise buildings, to address the unique challenges posed by the Malaysian climate. This study addresses this gap by focusing on retrofitting strategies specifically tailored for existing high-rise buildings in Malaysia. To evaluate energy efficiency accurately, a selected case study underwent modeling and simulation using Building Information Modeling (BIM) software for energy analysis. The simulation considered crucial aspects of window materials: U-factor, solar heat gain coefficient, visible transmittance, and emissivity. The study identified triple-glazed windows as the most energy-efficient choice, significantly outperforming single-glazed windows due to their lower U-factor and improved insulation properties. Light concrete bricks for walls demonstrated superior heat resistance owing to their lower density. Steel bar joists were found to enhance heat transfer efficiency in roofs. The recommended materials showed promising results, achieving a calculated energy consumption reduction to 266 kWh/m2/year. The study emphasizes that green consultants prioritize elements addressing excessive energy consumption during building upgrades, influencing their choice of retrofit options. Implementing energy-efficient retrofits can significantly reduce buildings' energy dependence, contributing to a substantial decrease in the country's overall energy consumption.

Design Process, Evaluation, and Sensitivity Analysis of an Activated Carbon Production Plant from Single-use Plastic Waste at the National University of Engineering

Objective: The objective of this study is to investigate the design process, economic evaluation, and sensitivity analysis for the construction of an activated carbon production plant from single-use plastic waste at the National University of Engineering. This project aims to transform plastic waste into a high-value-added product, thereby contributing to sustainability and aligning with circular economy principles. Theoretical Framework: The theoretical framework covers concepts related to the circular economy and sustainable waste management, emphasizing the need to reduce environmental impact through innovative alternatives such as recycling PET into activated carbon. Previous studies on pyrolysis and thermal or chemical activation of plastics for conversion into high-value materials are cited, establishing a solid foundation to contextualize the activated carbon production process. Method: The methodology adopted for this research includes a technical and economic study design based on the assessment of processes and equipment required for activated carbon production. An experimental approach is proposed, wherein plastic waste is collected, shredded, washed, dried, carbonized, activated, and finally packaged. Data collection involved detailed calculations of investment, energy consumption, and mass and energy balances for each stage of the production process. Results and Discussion: The results revealed that the project is economically viable, with a Net Present Value (NPV) of 59,733 USD and an Internal Rate of Return (IRR) of 13%. In the discussion, the project’s profitability is contextualized through a sensitivity analysis evaluating different scenarios of exchange rate and sale price. This analysis confirms that, in optimistic scenarios, the IRR can reach up to 341%, reducing the payback period to less than a year. Research Implications: The practical implications of this research include the potential to implement a circular economy model in educational institutions, promoting sustainability and efficient waste management. Theoretically, the study contributes to the field of plastic waste valorization through its transformation into activated carbon, which could positively impact sectors such as environmental management and industrial recycling. Originality/Value: This study contributes to the literature by presenting an innovative approach for plastic waste valorization into activated carbon within an educational institution, using pyrolysis and activation processes in a circular economy context. The relevance of this research lies in its practical applicability in academic settings and its potential impact on reducing plastic waste.

An optimal energy consumption calculation method of hybrid electric vehicles with frequency distribution characteristics of driving conditions

For a series of problems in the design and optimisation of series hybrid electric vehicles caused by the driving condition input, such as a variety of user conditions, which may hinder the energy-saving ability of such vehicles. Condition construction will inevitably lead to information loss, and traditional design methods require high computational power and encounter a time disaster during the real-world condition data explosion. This study proposes a condition representation method with driving condition frequency distribution characteristics (DCFDCs) and an optimal energy consumption calculation method, that is, instantaneous battery energy balance solution and global battery energy balance correction (IBGB–GBEB) with DCFDCs. The energy consumption calculation results show that the proposed optimal energy consumption method can guarantee the accuracy of the energy consumption calculation and reduce the calculation time cost. The difference in fuel consumption between the optimal energy consumption method and the dynamic planning (DP) algorithm is only 2.50%, but the difference in the calculation time between the two methods is 87.00%. Furthermore, the practical example of hybrid power system (HPS) design parameter optimisation shows that the energy consumption calculation results obtained by the TDCR–DP and DCFDCs–MIGA methods are consistent, and the relative error is only 1.81%. However, the calculation time of the TDCR–DP method is 472 h, whereas that of the DCFDC–MIGA method is only 2.17 h, which is a calculation time reduction of more than 99.54%. The results highlight the effectiveness and time advantage of the optimal energy consumption calculation method with DCFDCs. This study can provide theoretical guidance and technical support for solving system optimisation problems caused by the explosion of driving condition data.

Case Study of an Integrated Design and Technical Concept for a Scalable Hyperloop System

This paper presents the design process and resulting technical concept for an integrated hyperloop system, aimed at realizing efficient high-speed ground transportation. This study integrates various functions into a coherent and technically feasible solution, with key design decisions that optimize performance and cost-efficiency. An iterative design process with domain-specific experts, regular reviews, and a dataset with a single source of truth were employed to ensure continuous and collective progress. The proposed hyperloop system features a maximum speed of 600 kmh and a capacity of 21 passengers per pod (vehicle). It employs air docks for efficient boarding, electromagnetic suspension (EMS) combined with electrodynamic suspension (EDS) for high-speed lane switching, and short stator motor technology for propulsion. Cooling is managed through water evaporation at an operating pressure of 10 mbar, while a 300 kW inductive power supply (IPS) provides onboard power. The design includes a safety system that avoids emergency exits along the track and utilizes separated safety-critical and high-bandwidth communication. With prefabricated concrete parts used for the tube, construction costs can be reduced and scalability improved. A dimensioned cross-sectional drawing, as well as a preliminary pod mass budget and station layout, are provided, highlighting critical technical systems and their interactions. Calculations of energy consumption per passenger kilometer, accounting for all functions, demonstrate a distinct advantage over existing modes of transportation, achieving greater efficiency even at high speeds and with smaller vehicle sizes. This work demonstrates the potential of a well-integrated hyperloop system to significantly enhance transportation efficiency and sustainability, positioning it as a promising extension to existing modes of travel. The findings offer a solid framework for future hyperloop development, encouraging further research, standardization efforts, and public dissemination for continued advancements.

A Review of Algorithms and Platforms for Offloading Decisions in Mobile Cloud Computing

With the substantial growth of mobile applications and the emergence of cloud computing concepts, therefore mobile Cloud Computing (MCC) has been introduced as a potential mobile service technology. Mobile has limited resources, battery life, network bandwidth, storage, and processor, avoid mobile limitations by sending heavy computation to the cloud to get better performance in a short time, the operation of sending data, and get the result of computation call offloading. In this paper, a survey about offloading types is discussed that takes care of many issues such as offloading algorithms, platforms, metrics (that are used with this algorithm and its equations), mobile cloud architecture, and the advantages of using the mobile cloud. The trade-off between local execution of tasks on end-devices and remote execution on the cloud server for minimizing delay time and energy saving. In the form of a multi-objective optimization problem with a focus on reducing overall system power consumption and task execution latency, meta-heuristic algorithms are required to solve this problem which is considered as NP-hardness when the number of tasks is high. To get minimum cost (time and energy) apply partial offloading on specific jobs containing a number of tasks represented in sequences of zeros and ones for example (100111010), when each bit represents a task. The zeros mean the task will be executed in the cloud and the ones mean the task will be executed locally. The decision of processing tasks locally or remotely is important to balance resource utilization. The calculation of task completion time and energy consumption for each task determines which task from the whole job will be executed remotely (been offloaded) and which task will be executed locally. Calculate the total cost (time and energy) for the whole job and determine the minimum total cost. An optimization method based on metaheuristic methods is required to find the best solution. The genetic algorithm is suggested as a metaheuristic Algorithm for future work.

Fuzzy logic-supported building design for low-energy consumption in urban environments

Climate, building materials, occupancy patterns, and HVAC (heating, ventilation, and air conditioning) systems all interact in complex ways, making it difficult to design low-energy buildings. Thus, innovative architectural and engineering design strategies are required to meet the worldwide need to decrease building energy usage. To improve the calculation of energy consumption of buildings, this work introduces the FCR-BCS (fuzzy clustering rule-based building control systems), which integrates fuzzy logic concepts into computational simulations. FCR-BCS can contemplate real-world uncertainties and fluctuations using linguistic factors and approximate reasoning for more precise and trustworthy results in energy-efficient building design. This method's significance rests in its potential to significantly reduce energy use, advance sustainability, and improve urban residents' quality of life; architects and engineers can thus employ FCR-BCS to enhance the efficiency of HVAC systems and insulation. The outcomes of FCR-BCS simulation assessments show that it is capable of making buildings more energy efficient. The experimental outcomes demonstrate that the suggested model increases the sensitivity analysis by 99.4 %, energy efficiency analysis by 99.8 %, occupancy patterns analysis by 97.5 %, temperature profile analysis by 98.8 %, and energy consumption analysis by 99.6 % compared to other existing models.

Calculation of energy consumption for creation of thermoplastic holding in well conditions

The article deals with the methodology of calculation of the main technological parameters of friction welding used to create thermoplastic holdings in fishing devices for well workover operations. Thermoplastic holdings have high load capacity and can utilize existing surface equipment to provide the required relative rotation speed and controlled axial force. The article outlines two main stages of the friction welding process: the heating stage and the forging stage. In the heating stage, the key parameters are relative speed, axial force, and the duration of heating, all of which directly influence the temperature field at the contact cross-section. Equations for calculating the moment of friction forces, the work of friction forces per unit of time, and the amount of heat generated during the heating phase are provided. During the forging stage, the focus is on the axial force and its dependence on the mechanical properties of the materials as well as the temperature distribution within the welded object. The paper gives examples of calculations of the required energy using the derived formulas, taking into account the mechanical properties of contour bodies and forging forces. Specific examples of practical applications are given to ensure the creation of a quality thermoplastic holding. The presented methodology is significant for enhancing the efficiency and quality of well repair processes.

Research on Large Hybrid Electric Aircraft Based on Battery and Turbine-Electric

Hybrid electric aircraft use traditional engine and electric propulsion combinations to optimize aircraft architecture, improve propulsion efficiency, and reduce fuel consumption. As a new technology, the fuel and energy consumption calculation of hybrid electric aircraft is more complicated than traditional aircraft due to the usage of different energy forms. The purpose of this paper is to develop the analytical method for fuel and energy consumption for hybrid electric aircraft. This paper summarizes the working principle of hybrid electric aircraft, including the system architecture and power conversion mechanism. The calculation of fuel and energy consumption for hybrid electric aircraft is carried out in detail. In order to evaluate large hybrid electric aircraft, the architecture, based on energy flow, is established, and turbofan engine, electrical system, electric duct fan, and aerodynamic model characteristics are established. With a single-aisle aircraft as an example, the fuel and energy consumption under the 800 nautical mile range is performed. It shows that fuel consumption can be reduced by 10% and energy consumption by 4.7% compared with a traditional aircraft. The effects of different range and battery ratios are analyzed. The payload range for the hybrid electric aircraft is analyzed. The results show that even though the hybrid electric aircraft reduces the payload and range, it can significantly reduce fuel and energy consumption.

Particle Swarm Optimization for multi-chiller system: Capacity configuration and load distribution

This study applies Particle Swarm Optimization (PSO) to enhance the energy efficiency of a multi-chiller system in a large office building, with a focus on optimizing capacity configuration and load distribution. Given the rising demand for sustainable energy solutions in buildings, where HVAC systems, particularly chillers, account for a significant portion of energy consumption, this research aims to reduce energy use and improve system performance. EnergyPlus simulations, based on Baltimore weather data and a reference large office model, were conducted to build a baseline dataset. This dataset was then used in Python to calculate energy consumption and optimize load distribution and capacity configuration. PSO was applied in three stages: optimizing capacity configuration using five built-in EnergyPlus algorithms, optimizing load distribution, and simultaneously optimizing both. The results showed that optimizing capacity configuration alone improved performance, even using traditional load distribution methods. Load distribution optimization outperformed other algorithms and converged at a 0.7 Part Load Ratio (PLR) for staging. The integrated PSO application achieved an 11.3 % reduction in energy consumption, a 21.5 % improvement in Coefficient of Performance (COP), and a 12.8 % increase in the Seasonal Energy Efficiency Ratio (SEER) by precise operation of 15 different combinations throughout the entire load range. These results demonstrate the potential of PSO to significantly enhance the efficiency of multi-chiller systems, providing a novel approach to optimizing both capacity configuration and load distribution. This research contributes to a robust framework for improving energy performance in building systems and offers valuable insights for future sustainable energy solutions.

Optimizing Drone Delivery Paths from Shared Bases: A Location-Routing Problem with Realistic Energy Constraints

Recently, Amazon patented fulfillment centers for drones on a large scale in densely populated areas. A network of such shared centers can be used for landing and launching drones as an alternative to the traditional private bases in near future. This paper studies how a user of such a shared delivery infrastructure can optimally determine the required bases among the existing bases to perform her delivery tasks. To this end, a location-routing problem is studied where the problem determines the drone launching centers and their routes to deliver parcels. A realistic energy function is used that incorporates the effect of load weight for calculating energy consumption in all flight phases including take-off, level flight, hovering, and landing. Although the energy consumption is nonlinear, the problem is formulated as a mixed-integer linear programming model and strengthened by valid inequalities and a pre-processing algorithm that enables us to solve instances with up to 100 customers using off-the-shelf optimization solvers. Moreover, a heuristic method is presented to solve instances with up to 200 customers. Results indicate the importance of incorporating the load-dependent energy formula in contrast to using fixed flight duration constraints for drones. The value of allowing multiple visits on each trip versus only simple back-and-forth trips is also assessed. The advantage of using an integrated location-routing approach is shown over the sequential approach in which the locations of bases are decided first and the routes are constructed next. Moreover, to manage future demand uncertainty, the model is extended for the case that a number of demand scenarios are given.

Performance assessment of a multi-level shuttle system: an optimisation-embedded simulation study on time and energy consumption

ABSTRACT In response to the dynamic demands of modern e-commerce and supply chains, this paper addresses the critical need for adaptability and efficiency through the implementation of automated storage and retrieval systems. By using an optimisation-embedded simulation methodology, the proposed study focuses on a multi-level shuttle system designed to overcome the inherent limitations of traditional storage systems. A comprehensive discrete event simulation model is developed to evaluate the performance of the multi-level shuttle system. This model includes calculations of travel time and energy consumption, taking also into account stochastic handling times associated with repetitive tasks. In addition, a dynamic programming algorithm is integrated in the simulation model to optimise the sequencing of storage and retrieval missions performed by the handling machine. The study systematically investigates various design and operational parameters, including warehouse configurations and capacity, simultaneous handling of multiple unit loads, and the dimensions of the optimisation sessions. For all configurations tested, the research demonstrates operational advantages in the simultaneous handling of two unit loads. Theoretical contributions extend the current state of simulation models for automated warehousing systems. For practitioners, the study provides empirical insights to support decision making in the configuration of automated warehouses.

Destruction of perfluorooctane sulfonic acid (PFOS) in gas sparging incorporated UV-indole reductive treatment system – Benefits and challenges

Ultraviolet (UV) reductive treatment systems that generate hydrated electrons (eaq-) have emerged as a promising technology for the destruction of chemically inert per- and polyfluoroalkyl substances (PFAS). Here, we report on the evaluation of an indole derivative-based UV reductive treatment system that utilizes the amphipathic properties of PFAS at the gas-water interface (via nitrogen (N2) sparging) for more energy-efficient destruction of perfluorooctane sulfonic acid (PFOS). Results from this work illustrated that N2 sparging within UV systems can enhance the degradation and defluorination of PFOS compared to non-sparged conditions, but their overall treatment efficiency is low to industry standard. The inadequate system performance is likely originated from the insufficient accumulation of electron sources at the gas-water interface and their low water solubility level. In addition, carbonate species, which are ubiquitous in natural water and commonly applied as buffers in UV reductive treatment systems, negatively impact PFOS defluorination when indole is the electron source. The species-specific quenching imposed by carbonate species (e.g., HCO3- > H2CO3*) indicates that naturally occurring constituents and varying reactor conditions can substantially influence the remediation of PFOS. Other notable findings in this work include: 1) gramine, a cationic indole derivative, was able to remove > 99 % PFOS mass via electrostatic interaction within 0.5 h of reaction, signifying the electron source's structural property importance in UV reductive treatment systems, and 2) energy consumption calculations showed indole species are less energy-efficient as electron sources for PFOS destruction comparing to sulfite-iodide, but performance tradeoffs exist in both systems. The results of this work revealed both the benefits and challenges of utilizing N2 sparging and indole derivatives in UV-PFAS reductive treatment processes and provided critical information needed to improve the prediction and design of similar PFAS destruction technologies.

Relative fuel property variation of gas-pressurized and conventional torrefaction for biochar performance assessment

Exploring biochar from gas-pressurized torrefaction for solid biofuel production is of great concern for the process performance assessment. This study conducts several relative indexes of biochars produced from gas-pressurized and conventional torrefaction, identifying the merits of the former. The results suggest that a higher pressure is more feasible for reducing biochar volume and enhancing energy efficiency. The results of the relative higher heating value (1.01–1.07) and relative enhancement factor (1.00–1.06) indicate that gas-pressurized torrefaction is more efficient for energy density improvement. Furthermore, gas-pressurized torrefaction dramatically facilitates biochar grindability, with the relative Hardgrove grindability index value ranging from 1.20 to 2.40. The proximate and elemental analysis results suggest that a higher pressure facilitates biochar carbonization and deoxygenation with a higher carbonized component. The energy consumption, efficiency, and expense calculation results imply that gas-pressurized torrefaction is more energy-efficient and cost-saving, with the relative upgrading energy index range of 1.00–1.12.

Optimizing the Integration of Building Materials, Energy Consumption, and Economic Factors in Rural Houses of Cold Regions: A Pathway

Limited material options and economic conditions significantly restrict the potential for energy efficiency improvements in rural houses in China’s cold regions. It is worth exploring how to propose suitable energy-saving renovation plans for rural houses in cold regions under practical constraints. By using Grasshopper within Rhinoceros 8 software, an algorithm integrates material selection, energy consumption calculations, and economic analysis. The method efficiently generates thermal optimization schemes, providing insights into energy use, costs, and payback periods. In a case study of a typical rural house in Daqing City, the optimized scheme achieved over 70% energy savings compared to traditional homes, with renovation costs amounting to less than 40% of residents’ annual income and a 2-year payback period. This significant improvement highlights the potential of the proposed method in enhancing the energy efficiency and economic viability of rural house renovations.

Research on energy consumption evaluation and energy-saving design of cranes in service based on structure-mechanism coupling

Aiming at the problem that the life cycle energy consumption index of hoisting machinery is difficult to be objectively quantified, a crane energy consumption evaluation calculation method based on the working cycle of the service period is proposed, the typical service working mode of the crane is analyzed, and the working cycle process of the mechanism is clarified. On this basis, the stress cycle characteristics of the crane structure during the service period are determined based on the coupling relationship between the mechanism and the structure, which lays the foundation for accurately evaluating the life index of the crane. According to the relationship between the load rate and effective power of each mechanism during the service period of the crane, the calculation method for the evaluation and calculation of the structure energy consumption during the service period of the crane is studied. Finally, the crane is designed based on the concept of absolute service safety, and an optimal design model of the main girder structure of the crane with the goal of the lowest energy consumption in service is established. Using the research method of this paper to study a certain type of bridge crane, the energy consumption of the hoisting machinery during its service period is not only related to the accumulation of the operating characteristics of the mechanism but also related to the characteristic parameters such as the structure self-weight. The comprehensive evaluation of energy consumption provides an effective quantitative method and a reliable green design theory for crane design.

Implementation of monitoring and certification with the developed China heavy-duty vehicle energy consumption and carbon emission calculation model

Owing to escalating concerns regarding global warming, there has been a heightened focus on greenhouse gases emitted by vehicles. To effectively monitor and certify the fuel consumption and CO2 emissions of heavy-duty vehicles, this study proposes a calculation model named the China Heavy-Duty Vehicle Energy Consumption and Carbon Emission Calculation Model (CHECM). The CHECM is a simulation tool based on longitudinal dynamics. A classification learner was utilised to obtain shifting strategies, achieving accuracies of 92.9% and 93.5% under regulated driving cycles. A fuel-consumption model was incorporated to predict the transient performance of the engine and transmission. In addition, the Sobol method was used to assess the sensitivities of rolling resistance, air drag and rotational mass conversion coefficients to the driving force and a method was proposed to obtain the road resistance correction factor. The test results of three China-6 heavy-duty vehicles over two regulatory test cycles were obtained and used for model accuracy evaluation. The results showed that the deviations between the measured and calculated fuel consumption were 1.25–3.57%, whereas those between the measured and calculated CO2 emissions using the Chinese World Transient Vehicle Cycle were 3.23–4.16%. The CHECM has the potential to accurately replicate various driving conditions and vehicle configurations, particularly when specific sources of uncertainty are constrained.

Spatio-temporal distribution and peak prediction of energy consumption and carbon emissions of residential buildings in China

With the acceleration of urbanization and the improvement of people's living standards, the carbon emissions of residential buildings (BCE) in China have been increasing, hindering the achievement of carbon peaking and carbon neutrality goals. It has become increasingly urgent and important to analyze and grasp the dynamic trends of BCE. Given the notable regional variations in carbon emissions, it is necessary to delve into the distribution characteristics of BCE and the underlying factors influencing them. First, based on the emission factor method, the energy consumption and carbon emissions calculation models are established. Next, the main influencing factors are obtained by improving Kaya's constant equation. Meanwhile, the GA-PPC-Kmeans model is established to divide BCE into different regions. Then, the STIRPAT-Ridge model is built to predict the peak carbon emissions. Finally, a combination of static and dynamic methods is used to forecast peaks under three scenarios, which are low-carbon (LC) scenario, baseline (BA) scenario, and high-carbon (HC) scenario. The results show that five pivotal factors significantly impact BCE in China, which are energy carbon emission intensity (ECEI), energy intensity (EI), economic density (ED), residential housing level (RHL) and population size(P). Furthermore, BCE is categorized into five distinct regions: low-carbon demonstration area, energy efficiency improvement area, carbon concentration and innovation area, high-carbon optimization area, and carbon poverty development area. Under BA scenario, the peaks for BCE in these regions converge primarily around 2040 and 2045. This study provides a regional research perspective for China's residential buildings to reach the peak of carbon emissions, and serves as a reference for formulating carbon emission reduction plans in different regions.

Privacy protection of communication networks using fully homomorphic encryption based on network slicing and attributes

At present, social networks have become an indispensable medium in people's daily life and work. However, concerns about personal privacy leakage and identity information theft have also emerged. Therefore, a communication network system based on network slicing is constructed to strengthen the protection of communication network privacy. The chameleon hash algorithm is used to optimize attribute-based encryption and enhance the privacy protection of communication networks. On the basis of optimizing the combination of attribute encryption and homomorphic encryption,, a communication network privacy protection method using homomorphic encryption for network slicing and attribute is designed. The results show that the designed network energy consumption is low, the average energy consumption calculation is reduced by 8.69%, and the average energy consumption calculation is reduced by 14.3%. During data transmission, the throughput of the designed network can reach about 700 Mbps at each stage, which has a high efficiency.. The above results demonstrate that the designed communication network provides effective privacy protection. Encrypted data can be decrypted and tracked in the event of any security incident. This is to protect user privacy and provide strong technical support for communication network security.

The Impact of Renewable Energy on Low Energy Consumption in Civil Engineering Construction

As the main representative of new energy, photovoltaic energy is widely used in civil engineering construction, its purpose is to reduce the energy consumption in the project, there is a deviation in the integration of new energy and civil engineering, and it cannot effectively play its own advantages. Continuously analyze the changes in the energy consumption values of civil engineering. Then, the influencing factors of building energy consumption were introduced, and the covariance matrix was constructed, and the engineering construction benefit was taken as the ultimate goal. When calculating energy consumption, the dual benefits of building benefits are fully considered, and environmental protection and engineering energy consumption are estimated to reduce the error of energy consumption calculation. The results show that new energy can reduce the high energy consumption value in the project, improve the light transmittance, enhance the conversion rate of sunlight, and provide support for the transportation, lighting and thermal insulation of the building, with an increase rate of 10~25%, and the new energy can reduce the cost of civil engineering, with a reduction rate of 19~26%, and improve the economic and social benefits, with an increase of more than 10%. Therefore, new energy can reduce the energy and energy consumption of civil engineering, and expand the scope and application depth of new energy development.