Energy-efficient Problem Research Articles

The effect of the design angle of the turbine nozzle outlet of the piston engine boost system on its effectiveness

The article is devoted to the actual problem of insufficient energy efficiency of combined internal combustion engines. One of the directions of its solution, which became the goal of this work, is a reasonable choice of the optimal value of the design angle of installation of nozzles in a radial-axial turbine, taking into account both its effective power and the coefficient of completeness of using the supplied pulse energy. The authors applied a closed-loop model of the combined engine, embedded in a new calculation method, which was divided into conditional blocks. In the first block, the method of indefinite Lagrange multipliers calculates the optimal values of the turbine elements in which the gas moves. In the second block, for a preliminary assessment of the calculated geometrical parameters of the flow path, the turbine characteristics are calculated: an assumption is made about the one-dimensionality and quasi-stationary flow. For calculations, a method for calculating the parameters of a stage at an average radius was used, supplemented by a semi-empirical method for calculating gas energy losses during the movement of the latter from the turbine inlet to the outlet section. In the third block, the efficiency of the turbine was estimated when working together with a piston engine by using a closed model for it. This made it possible to objectively evaluate such characteristics of the turbine as efficiency and power, which are functionally related to the pressure pulse in the exhaust tract, which will make it possible to predict the operational characteristics of the turbine operating in conjunction with the combined engine.

Evaluating UKCP18-Based weather files for overheating assessment using building simulation: A case study for a flat in london

Global warming and net zero transition are the two biggest challenges currently faced by the building industry in the UK. While the net zero transition primarily focuses on the problems of energy efficiency and heat decarbonization, the rise of global temperature imposes a significant threat to the health and wellbeing of occupants and the industry is obliged to make buildings climate-resilient by testing their designs using future weather files. To improve the quality of the current weather files, a new project has been commissioned by CIBSE to revisit the data and the methodology employed for creating future weather files and produce new CIBSE weather files using the latest UK Climate Projections released in 2018 (UKCP18). In this study, we evaluate the newly produced weather files for overheating risk using building simulation. Two different batches of weather files were curated. The first batch was produced primarily using the existing methodology for creating the UKCP09 based weather files, with an adjustment to accommodate new features of the UKCP18 and an improved procedure for morphing the solar radiation data. The second batch was created through an improved morphing process to better emulate the characteristics of distributions of climatic variables. The differences between the existing UKCP09 and new UCKP18 based weather files are compared by evaluating overheating metrics. The new weather files enable robust building performance assessment against future climate conditions under different scenarios and will play an important role in designing climate-resilient buildings and delivering a net zero built environment. Practical applications As the extreme weather events resulting from climate change become more frequent and intense, they pose significant challenges to the resilience of the built environment and severe threats to the health and wellbeing of the occupants. Climate data, which serves as the foundation for climate risk assessment, plays a critical role in helping the building sector to achieve climate resilience through the means of performance assessment and the channel of regulatory compliance. In this study, the revised future weather files created using the latest UKCP18 climate projections are presented and evaluated using building simulation, as part of the weather file testing programme for quality assurance. The revision of the CIBSE weather files according to the latest climate science, i.e. UKCP18, will enable the building industry to quantify overheating risks with more accurate climate assumptions and better inform decision making about risk mitigation and climate adaptation.

Design and Implementation of Energy-Aware Integration Mechanisms for IoT-Cloud Architectures: Enhancing Efficiency in Resource-Constrained Environments

This study paper suggests a way for the Internet of Things (IoT) and Cloud computing to work together that is smart about energy use. The goal is to solve the problem of IoT-Cloud integration's energy efficiency, which is important for making sensor nodes last longer and making sure that data transfer continues over time. The first step in the process is to plan the IoT nodes and give each sensor node a unique ID and a starting energy level. To make data safer, a homomorphic encryption method is used to make public and private keys. The integration process uses a good Cluster Head Selection Technique that has Random, Energy-Based, Distance-Based, and Density-Based methods to make sure that the sensor nodes are grouped together in the best way possible. The sensor nodes send data to the base station through cluster heads, which use homomorphic encryption to make the connection safe. The public key is used to hash each data packet before it is sent to the cluster head. The cluster head then sends the packets to the base station through the Cloud. At the base station, the data hash is checked one at a time, and then the data is decrypted. This makes sure that the data is correct and safe while it is being sent. Comparing time and energy use across different systems and node numbers is part of the performance assessment. The results show that System 4 did better than the others in terms of how much energy it used and how efficiently it transferred data. This shows that the proposed system can effectively handle IoT-Cloud integration. System 4 kept 28,848 units of energy after starting with 29,442 units, showing that it was much more energy efficient. The results show that using techniques that are aware of energy in IoT-Cloud systems can greatly improve performance. This study adds to the growing body of research on integrating IoT and the cloud by showing a safe, effective, and energy-conscious method that sends data while using the least amount of energy possible.

ENERGY EFFICIENCY AND ALTERNATIVE ENERGY SOURCES AS BASIS OF ENERGY SECURITY IN THE LEADING COUNTRIES OF THE WORLD

The article provides an analysis of the political goals of the leading countries of the world in terms of energy efficiency and the transition to alternative energy sources, and concludes that energy efficiency is in the focus of policy not because of environmental factors, but due to the strengthening of energy security in certain Western countries. The priority of energy efficiency as the basis of energy security leads to a situation when cheap energy resources of the exporting country are not considered a competitive advantage. An environment where not only economic (economic expediency), but also political choice (the search for new spheres of influence) is crucial, is emerging. Solving energy problems goes beyond the limits of standard economic tasks and is impossible without political goal-setting and will. Improving energy efficiency can create new competitive advantages for the state, such as universal access to energy. It is not possible to make a rapid transition to alternative energy sources, but in the long term, an active policy on energy efficiency and the use of alternative sources can yield high results in the energy sector. Competition in the world in the field of non-renewable energy sources will increase in the future, therefore, solving the problem of energy efficiency should be a top priority in order to prevent public issues such as the energy security of future generations. In this regard, it is important to identify the relationship between energy efficiency, the use of alternative energy sources and energy security in Russia's economic policy and to approve the priority of energy efficiency at all levels: national, regional and municipal one.

Optimization of Non-Linear Problems Using Salp Swarm Algorithm and Solving the Energy Efficiency Problem of Buildings with Salp Swarm Algorithm-based Multi-Layer Perceptron Algorithm

Optimization of Non-Linear Problems Using Salp Swarm Algorithm and Solving the Energy Efficiency Problem of Buildings with Salp Swarm Algorithm-based Multi-Layer Perceptron Algorithm

CO2-Emissions as a Measure of Energy Efficiency in the Production and Application of Fertilizers

Taking into account the huge amount of data accumulated in recent years on greenhouse gas emissions (primarily CO2, methane, or greenhouse gases (GHGs)), it is possible to consider the problem of energy efficiency (carbon dioxide emissions occur primarily during fuel combustion, as well as methane and CO2 as precursors for nitrogen fertilizers) in the chain from the production of fertilizers to their logistics, application, production and waste disposal. At the same time, GHGs emissions can be considered as a measure of energy efficiency in assessing the life cycle of mineral fertilizers. Relevant examples are provided in the review.

System for monitoring building heat consumption

Relevance. Energy consumption and efficient use of district heating networks affect the environment, society and the economy. Solutions are needed that can significantly reduce specific thermal energy losses. Using a technically and economically feasible way to assess energy efficiency allows these decisions to be made. Currently, assessing the energy efficiency of buildings raises significant questions among specialists. There is not much modern specialized literature in this area. The problem of energy efficiency requires more rigorous attention to urban planning issues. Thus, refined methods for assessing the energy efficiency of buildings make it possible to simultaneously save capital investments and ensure efficient consumption of thermal energy. Aim. To develop a system for assessing the real heat consumption of buildings to ensure optimization of dispatching of centralized heat supply systems in real time. Methods. Computer modeling of the state of heat consumption of buildings with various characteristics and schemes for their connection to centralized heat supply networks; methods of geographic information analysis. Results. The authors have proposed the system for monitoring the heat consumption of buildings. This system allows assessing the energy efficiency of buildings through the maximum use of computer and software technologies. It is shown that the calculated heat flows of buildings used to predict savings when modernizing buildings do not always correspond to the actual heat loads, which can lead to an incorrect assessment of investment projects. The authors obtained graphical dependences of the quantities influencing specific heat losses on various primary independent factors. Conclusions. The constructed system for monitoring the heat consumption of buildings allows, together with the use of geoinformation analysis methods, obtaining a fairly complete picture of the state of heat consumption for city areas and an assessment of the energy characteristics of buildings.

A Pareto-optimality based black widow spider algorithm for energy efficient flexible job shop scheduling problem considering new job insertion

The utilization of flexible job shops is on the rise, driven by the decreasing life cycle of consumer products. In dynamic flexible job shops, the occurrence of disruptive events like machine breakdown, tool wear, and new job arrivals is common, emphasizing the critical need for efficient scheduling to achieve productivity and cost-effectiveness. Additionally with the growing concerns about energy consumption and global warming, the imperative to contemplate workshops with lower energy usage is becoming increasingly significant. Therefore, in this study a multi-objective dynamic flexible job shop scheduling problem (MODFJSP) with insertion of new jobs for optimization objectives: makespan, total energy consumption and schedule instability is addressed. A novel multi-objective black widow spider algorithm (MOBWSA), inspired by the mating behavior of black widow spiders, is proposed. The MOBWSA ensures an optimal balance between minimizing makespan and energy consumption through its superior evolutionary processes of procreation, mutation and cannibalism. Furthermore, a strategic on/off strategy is implemented to enhance energy efficiency. The disruptions in schedule at rescheduling stage are addressed through the proposed sigmoidal weighted instability function. To handle the multi-objective nature of the problem this work incorporates Pareto-optimality approach in combination with novel hybrid crowding distance metric. The optimization is further aided by exploitation of search space through an ensemble of local search operators. Testing and evaluation of the MOBWSA with 30 benchmark problems is conducted, and its performance for multiple metrics is compared with recently published state-of-the-art algorithms. The results establish the effectiveness and efficiency of the proposed algorithm.

Analysis of the regulatory and legislative base of Ukraine and the European experience in conducting energy audits of buildings

The article analyzes the regulatory and legislative base for the energy efficiency of buildings. It identifies the main areas for improving energy efficiency by improving the process of energy audit, as well as improving the system of indicators that determine the airtightness of the building and preservation of comfortable conditions for human stay in the room. The relevance of the work is determined by the problem of low energy efficiency of the housing stock of Ukraine, which affects the rational consumption of energy, necessitates the introduction of various measures aimed at rationalizing energy use in general and buildings in particular, setting maximum permissible energy consumption rates for buildings and strengthening relevant control. The imperfection of the regulatory and legislative base in the field of energy efficiency, the need to develop a state standard for the design of buildings with increased air permeability, the development of a methodology for determining the air permeability of a building, the legislative establishment of minimum requirements for building airtightness, the development of a methodology for testing buildings for airtightness, and the imperfection of the methodology for conducting an energy audit of a building form the basis for further research. To improve the energy management of buildings, it is proposed to introduce mandatory testing of the building for airtightness, which will standardize approaches to energy management and compliance with the relevant requirements for building airtightness will lead to an increase in the energy efficiency class of buildings. Keywords: energy efficiency, energy audit, air permeability, airtightness.

Review of Ti3C2Tx MXene Nanofluids: Synthesis, Characterization, and Applications

MXene-based nanofluids are important because of their thermal and rheological properties, influencing scientific and industrial applications. MXenes, made of titanium carbides and nitrides, are investigated for nanofluid enhancement. This review covers MXene nanofluid creation, characterization, and application. To produce nanoscale MXene particles, two-dimensional materials are dissolved and dispersed in a base fluid. The stability and efficacy of MXene nanofluids depend on production methods, such as chemical exfoliation, electrochemical etching, and mechanical delamination. Improved heat transfer coefficients and thermal conductivity from MXene nanofluids help resolve heat transfer, energy efficiency, and thermal control problems. This extensive review also addresses long-term safety and the necessity for standardized characterization methodologies, helping researchers optimize MXene-based nanofluids in many technological fields

Increasing Energy Efficiency of Autonomous Indication and Lighting Systems for Unregulated Ground Pedestrian Crossings

The work deals with the problem of energy efficiency of autonomous indication and lighting systems for unregulated ground pedestrian crossings equipped with a solar panel being significantly important in conditions of insufficient insolation and low temperatures. The scientific objectives of the work are considered to be as follows: analysis of the conditions affecting the uninterrupted functioning of autonomous indication and lighting systems of unregulated ground pedestrian crossings equipped with a solar panel; selection and justification of objective factors, considering which allow the implementation of battery charge saving modes by optimizing the functioning algorithm of autonomous indication and lighting systems for unregulated ground pedestrian crossings equipped with a solar panel. The work presents the directions for possible technical implementation of increasing the energy efficiency of autonomous indication and lighting systems for ground pedestrian crossings equipped with a solar panel, based on obtaining optical information about vehicles moving in the direction of the pedestrian crossing and stabilizing the brightness contrast of the traffic light signal and the background where it is observed by vehicle drivers.

A Review of Cooling and Heating Loads Predictions of Residential Buildings Using Data-Driven Techniques

Energy efficiency is currently a hot topic in engineering due to the monetary and environmental benefits it brings. One aspect of energy efficiency in particular, the prediction of thermal loads (specifically heating and cooling), plays a significant role in reducing the costs associated with energy use and in minimising the risks associated with climate change. Recently, data-driven approaches, such as artificial intelligence (AI) and machine learning (ML) techniques, have provided cost-effective and high-quality solutions for solving energy efficiency problems. This research investigates various ML methods for predicting energy efficiency in buildings, with a particular emphasis on heating and cooling loads. The review includes many ML techniques, including ensemble learning, support vector machines (SVM), artificial neural networks (ANN), statistical models, and probabilistic models. Existing studies are analysed and compared in terms of new criteria, including the datasets used, the associated platforms, and, more importantly, the interpretability of the models generated. The results show that, despite the problem under investigation being studied using a range of ML techniques, few have focused on developing interpretable classifiers that can be exploited by stakeholders to support the design of energy-efficient residential buildings for climate impact minimisation. Further research in this area is required.

ЭМИССИЯ ПАРНИКОВЫХ ГАЗОВ КАК МЕРА ЭНЕРГОЭФФЕКТИВНОСТИ ПРИ ОЦЕНКЕ ЖИЗНЕННОГО ЦИКЛА УДОБРЕНИЙ

The article examines the problem of energy efficiency in the chain from the production of fertilizers to their logistics, application, and waste production and disposal based on the huge amount of data accumulated in recent years on greenhouse gas (GHG) emissions (primarily CO2 and methane). Carbon dioxide emissions are shown to occur primarily from fuel combustion, as well as from the use of methane and CO2 as precursors for nitrogen fertilizers. GHG emissions can be considered as a measure of energy efficiency when assessing the life cycle of mineral fertilizers. Relevant examples are given

VO2 memristor-based frequency converter with in-situ synthesize and mix for wireless internet-of-things

Wireless internet-of-things (WIoT) with data acquisition sensors are evolving rapidly and the demand for transmission efficiency is growing rapidly. Frequency converter that synthesizes signals at different frequencies and mixes them with sensor datastreams is a key component for efficient wireless transmission. However, existing frequency converters employ separate synthesize and mix circuits with complex digital and analog circuits using complementary metal-oxide semiconductor (CMOS) devices, naturally incurring excessive latency and energy consumption. Here we report a highly uniform and calibratable VO2 memristor oscillator, based on which we build memristor-based frequency converter using 8×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document}8 VO2 array that can realize in-situ frequency synthesize and mix with help of compact periphery circuits. We investigate the self-oscillation based on negative differential resistance of VO2 memristors and the programmability with different driving currents and calibration resistances, demonstrating capabilities of such frequency converter for in-situ frequency synthesize and mix for 2 ~ 8 channels with frequencies up to 48 kHz for low frequency transmission link. When transmitting classical sensor data (acoustic, vision and spatial) in an end-to-end WIoT experimental setup, our VO2-based memristive frequency converter presents up to 1.45× ~ 1.94× power enhancement with only 0.02 ~ 0.21 dB performance degradations compared with conventional CMOS-based frequency converter. This work highlights the potential in solving frequency converter’s speed and energy efficiency problems in WIoT using high crystalline quality epitaxially grown VO2 and calibratable VO2-based oscillator array, revealing a promising direction for next-generation WIoT system design.

Application of Hydraulic Energy-Saving Technology in the Teaching, Research, and Practice of Mechanical Engineering

To cope with the current resource, energy, and environmental problems faced by the manufacturing industry, energy conservation has become a long-term national development strategic policy. Specifically, the problems of high energy consumption and low energy efficiency in hydraulic systems have received considerable attention. Based on previous research on hydraulic energy-saving technology, this paper discusses the problems and challenges faced by such technology in higher education, the methods of integrating this technology into the curricula of mechanical majors, and the implementation of teaching reform. In the selected case study, hydraulic energy-saving technology was incorporated into the hydraulic experiment and practical training course of our school, focusing on the integration of energy-saving and emission-reduction concepts in the field of mechanical engineering teaching and research. Integrating hydraulic energy-saving technology into teaching and research not only enriches the content of mechanical engineering degree courses but also integrates professional knowledge with future work practice, provides methods and technical support for future research by teachers and students, and stimulates new ideas for the teaching reform and talent cultivation of mechanical engineering majors.

New trends in datacenter energy efficiency: beyond PUE

The energy efficiency is one of the great challenges of the IT industry. This challenge is even greater for supercomputing centers, since they are very intensive in energy consumption. The FCSCL is a center that was born in 2008 and its infrastructures were designed to achieve higher energy efficiency. In addition, energy efficiency is the priority line of research in FCSCL. To solve the problem of energy efficiency it is necessary to establish metrics, and organizations as The Green Grid PUE has established the PUE as the primary measure of energy efficiency. The FCSCL has developed the MONICA project in collaboration with the company Caton S. L. and the University Jaume I, and the first objective of the project has been active PUE monitoring. The PUE is the main indicator of the energy balance of a datacenter, and it is obvious that the first thing to do is monitor it to keep it under control But the analysis of the data acquired in MONICA project has shown that taking measures to improve the PUE can worsen the overall efficiency of the datacenter and IT equipment, as will be demonstrated in the article.

Reconfigurable Intelligent Surface-Assisted Secure Communication in Cognitive Radio Systems

A reconfigurable intelligent reflective surface (RIS)-assisted cognitive radio (CR) multiple-input multiple-output (MIMO) secure communication system is considered. In the presence of an eavesdropper, a primary base station (PBS) and a cognitive base station (CBS) equipped with multiple antennas communicate to a primary user (PU) and a secondary user (SU), respectively. In order to maximize the achievable secrecy rate of the system, the secrecy rate maximization problem is first transformed into a secure energy efficiency (SEE) problem using an objective function. Then, the security energy efficiency of the system is maximized by jointly optimizing the transmit beam formation of the base station and the reflected beam formation of the smart reflecting surface under the conditions that the total transmitted power constraint and the interference power constraint are satisfied. To address the difficulty in solving the resulting optimization problem, we apply an algorithm based on alternating optimization and semidefinite relaxation, as well as Dinklbach’s algorithm, to solve the problem. Simulation results show that this method can significantly improve the safety energy efficiency of the system.

Energy efficiency analysis of energy facilities using ranking methods

RELEVANCE. Increasing energy efficiency is one of the necessary conditions for modernizing the Russian economy. High energy intensity and energy efficiency analysis are due to the combined influence of a number of factors, both global and private. Thus, for electric grid organizations the problem of energy efficiency is a priority. Having at their disposal electrical grid facilities, including points of reception and transmission of electrical energy, electrical equipment and power transmission lines, electrical grid organizations incur huge losses caused by losses during the transmission of electrical energy, losses associated with the unaccounted share of electricity, as well as third-party factors. OBJECT. Conduct an analysis of the energy efficiency of an electric grid organization that has 10 branches. Form a hierarchy of energy efficiency indicators, determine the impact of each indicator on the integral indicator that reflects the energy efficiency of the facility. Conduct benchmarking, identify leaders and outsiders among power grid organizations. METHODS. To calculate the weight coefficients, the method of analysis of hierarchies in the classical and fuzzy formulations was used. Energy efficiency benchmarking was carried out by ranking power grid organizations according to the integral indicator of energy efficiency. RESULTS. A three-level hierarchy of energy efficiency indicators has been formed. A decision-making algorithm is presented when analyzing the energy efficiency of energy industry facilities. The weight coefficients of indicators and integral values of energy efficiency of organizations are calculated. The indicators that have the greatest impact on the overall efficiency of the facility were identified. A summary diagram of comparison of all branches has been formed, the most and least successful organizations have been identified. CONCLUSIONS. The analysis of energy efficiency, carried out using two methods of analysis of hierarchies, made it possible to identify the advantages and disadvantages of the classical representation of the method. Determination of leaders within the branch structure of the electric grid organization allows us to analyze the methods used to improve energy efficiency, as well as to introduce them in the future to less successful branches.

An explainable multi-agent recommendation system for energy-efficient decision support in smart homes

Abstract Transparent, understandable, and persuasive recommendations support the electricity consumers’ behavioral change to tackle the energy efficiency problem. This paper proposes an explainable multi-agent recommendation system for load shifting for household appliances. First, we extend a novel multi-agent approach by designing and implementing an Explainability Agent that provides explainable recommendations for optimal appliance scheduling in a textual and visual manner. Second, we enhance the predictive capacity of other agents by including weather data and applying state-of-the-art models (i.e., k-nearest-neighbors, extreme gradient boosting, adaptive boosting, Random Forest, logistic regression, and explainable boosting machines). Since we want to help the user understand a single recommendation, we focus on local explainability approaches. In particular, we apply post-model approaches local, interpretable, model-agnostic explanation and SHapley Additive exPlanations as model-agnostic tools that can explain the predictions of the chosen classifiers. We further provide an overview of the predictive and explainability performance. Our results show a substantial improvement in the performance of the multi-agent system while at the same time opening up the “black box” of recommendations.

تحسين استهلاك الطاقة لشبكات الهاتف الخلوي ذات الجيل الخامس باستخدام خوارزمية تحسين مدمجة

The 5G network technology is a promising technology that can successfully meet the demand for network capacity growth, due to its high-speed, low-latency, and wide connectivity capabilities. Adapting 5G will increase the energy consumption and CO2 emissions caused by this high consumption. Base stations (BSs) consume the most power in mobile networks accounting for approximately 57% of total energy consumption. This study proposes an integrated meta-heuristic optimization algorithm that combines the Arithmetic Optimization Algorithm (AOA) and the Particle Swarm Optimization (PSO) method. This combination aims to leverage the strengths of both approaches improving the speed and accuracy of the optimization process, to achieve better energy efficiency (EE) in 5G network technology. The proposed algorithm performance is evaluated based on a set of benchmarks functions and compared with other optimization methods. And to demonstrate the applicability of the proposed algorithm in terms of network energy efficiency problem, it was tested against a real-world case study involving power allocation in 5G, the results showed that the proposed algorithm outperforms more recent meta-heuristics state-of-the-art methods in solving a wide range of benchmark functions and obtaining a fair power allocation for multiple users in 5G network. Moreover, it maximizes energy efficiency while maintaining users service quality and availability and reducing total network energy consumption.