International Journal of Global Energy Issues (32 papers in press)

Regular Issues

• Price and volatility of rare earths  
  by Auguste Mpacko Priso, Souleymane Doumbia 
  Abstract: The purpose of this paper is to discuss results of a statistical model for volatility of rare earths prices traded at the London Stock Exchange and compare it to the volatility of other metals prices as well as that of other stock prices. Although known for centuries, rare earths have drawn particular attention interest over recent years due to their potential solution to mitigate climate change effects. These metals with exceptional characteristics are used in high-tech product manufacturing, especially those seen as alternative to the consumption of fossil fuels like car batteries. We show that the volatility of all three indexes is persistent. The volatility model which best fits the rare earths prices is a gjrGARCH(1,1) model. This is to our knowledge the first time the persistent volatility framework is applied to price of rare earths. Our work paves the way to many other applications, including volatility forecasts of rare earths price. This latter can help investors improve their decision-making process.
  Keywords: metal prices; rare earths; climate change; volatility models; ARCH; GARCH models.
  DOI: 10.1504/IJGEI.2023.10056317
   
  
• Oil market crashes: from the subprime crisis to the COVID-19 pandemic  
  by Donia Aloui, Rafla Hchaichi, Khaled Guesmi 
  Abstract: This paper aims to examine whether and how the COVID-19 crisis is similar to previous economic crises. Using a TVP-BVAR-SV model, we compare the responses of WTI-oil and Natural Gas prices in the face of the COVID-19 crisis to that of the 2008 global economic crisis and the 2014 Asian crisis. The findings confirm a remarkable similarity of WTI-oil prices behavior between 2008 and 2020 in terms of volatility and responses to the petroleum consumption shocks. However, the Natural gas market remains relatively stable during COVID-19 with modest responses to the shocks. The predictive probability density shows a high predictive variance indicating extreme uncertainty surrounding the COVID-19 period.
  Keywords: COVID-19; subprime crisis; oil price war; negative WTI oil price; natural gas; TVP-BVAR-SV model; stochastic volatility; forecasting.
  DOI: 10.1504/IJGEI.2023.10057452
   
  

Special Issue on: Intelligent Expert System in Non-Conventional Energy Systems Part 1

• Application of blockchain-based data pre-processing algorithm in motion analysis system  
  by Ting Wang 
  Abstract: Databases and data warehouses are very susceptible to the intrusion of noisy data. The existence of noisy data has a great impact on the speed and quality of data information mining. This article aims to study a motion analysis system based on blockchain-based data pre-processing algorithms, and proposes the application method of data pre-processing algorithms in motion analysis training. This article analyses related content such as data pre-processing algorithms, sports training, and motion analysis systems, and conducts experiments on a motion analysis system based on blockchain-based data pre-processing algorithms. The experimental results show that the sports analysis system based on the data pre-processing algorithm can analyse the various states of the athletes during the exercise, and can effectively point out some deficiencies in the training process, which is beneficial to improve the training effect of the athletes, especially it is a 7% increase in improving the athlete's maximum physical state value.
  Keywords: blockchain technology; data pre-processing; sports analysis system; sports training; data noise reduction.
  DOI: 10.1504/IJGEI.2023.10055440
   
  
• Fusion analysis of sports data based on smart sensors and blockchain technology  
  by Yujia Wang 
  Abstract: Smart sensors are sensors with data processing functions. They are equipped with microprocessors capable of collecting, processing and exchanging data, and are the product of the integration of sensors and microprocessors. This article aims to study the impact of smart sensors and blockchain technology on sports data fusion, and introduces a hierarchical model of sports athletes corresponding to the motion capture data. A human motion coordination system and reliable construction algorithm based on reliability and probability are proposed. This paper also proposes a data integration algorithm that enables applications in blockchain technology to run at a high speed, which extends the life cycle of network sensors to a certain extent. Blockchain technology is to use blockchain data structure to verify and store data, use distributed node consensus algorithm to generate and update data, use cryptography to ensure the security of data transmission and access, and use smart contracts composed of automated script codes. The experimental results of this article show that through the dynamic analysis algorithm of the smart sensor, it can be obtained that the visual range of the motion data is 22.5, and the network space value is 200. At the same time, it also shows that the use of distributed compressed sensing technology in blockchain technology can reduce the amount of information transmission in some aspects, and improve the speed and accuracy of data fusion.
  Keywords: smart sensors; blockchain technology; data fusion; sports data.
  DOI: 10.1504/IJGEI.2023.10055439
   
  
• Distributed energy system based on comprehensive utilisation of solar energy and biomass energy  
  by Dexia Kong, Zhiqiang Yao, Yihao Duan, Yulei Zhao 
  Abstract: Traditional energy is mostly non-renewable energy. The main advantage of distributed energy system is to use it in cogeneration of cooling, heating and power. Distributed energy takes into account the two factors of energy saving and environmental protection. Breaking the traditional single power supply, heating or cooling method has become the best way to adjust the energy structure, and has broad market application prospects. In order to understand the utilisation of solar energy and bio-intelligence, this paper collects a large number of scattered energy data information on site in real time, uses high-speed communication network to transmit data, relies on real-time database technology to process the measured data, and uses visual programming configuration tools to quickly, accurately and reliably obtain energy management information. The dimensional division and system configuration of energy management are classified in detail, and the design and development of system functions such as data collection and storage, data statistics and analysis, status monitoring and alarms have been completed. The results of the study found that, based on solar energy and biomass, the cooling time of internal combustion engines and gas turbines is basically the same, but the energy consumed by internal combustion engines is about 10% higher than that of gas turbines.
  Keywords: solar energy; biological intelligence; comprehensive utilisation; distributed energy system.
  DOI: 10.1504/IJGEI.2023.10054750
   
  
• Smart city traffic evaluation system based on neural network model  
  by Mingyue Wang 
  Abstract: Based on the basic connotation of green transportation and reorganisation and the five-in-one theory of green transportation, the article constructs an evaluation index system for urban green transportation, proposes an evaluation model based on BP neural network, and tests it. The article verifies the efficiency and rationality of this method, determines the number of network layers, transfer function, training function, hidden layer neurons, and provides a feasible evaluation program, uses MATLAB Neural Network Toolbox (NNT) to design the calculation network, and uses sample training for simulation testing. From the results, it can be seen that the accuracy of the urban ecological transportation BP neural network evaluation model is relatively high. The training accuracy can reach 3.4*10⁻³ magnitude, the output accuracy can reach 10⁻⁴ magnitude, and the error of the model is within a predetermined range. The strategic measures for the development of urban ecological transportation are proposed.
  Keywords: urban ecological transport; ecological transport evaluation; index system; neural network model.
  DOI: 10.1504/IJGEI.2023.10056390
   
  
• A Monte Carlo simulation for electron scattering and collision for electron transport in low-temperature plasmas  
  by Rawaa A. Abdul-Nabi 
  Abstract: Owing to the lack of equilibrium between electrons and neutral species and ions and the electrons themselves, the electron velocity distribution function in partially ionised plasmas deviates substantially from a Maxwellian value. Electrons are also out of thermal equilibrium with one another and with neutral species and ions. Low-temperature non-equilibrium plasma technology is now widely used. The employment of plasma modelling considerably improves their understanding, progress, or optimisation. To successfully portray plasma characteristics as a function of external influences, electron and ion collisions and transmissions with neutral substances must be well described. We provide free MATLAB code for modelling electron transport in a uniform electric field in any gas combination. The program gives a coefficient, reaction rate, or electron energy division function for steady-state electron transmission. The program is compatible with electron cross-sectional files generated using the Monte Carlo method. The program uses well-known Monte Carlo methods and works with open-access electron scattering cross-sections. The LXCat Plasma Data Share Project aims to exchange plasma data.
  Keywords: electrons; electron scattering; Monte Carlo simulation; gas; collision; LXCat; Plasma Data Share Project.
  DOI: 10.1504/IJGEI.2023.10055834
   
  
• Voiceprint recognition and cloud computing data network security based on scheduling joint optimisation algorithm  
  by Yinhui Ma 
  Abstract: Cloud computing is an upcoming revolution in the information technology industry due to its performance, accessibility, low cost, and many other luxury items. This is a way to maximise capacity without investing in new infrastructure, training new personnel, or licensing new software, for it provides customers with huge data storage and faster calculation speed through the internet. With the popularity of cloud computing, users store and share confidential data in the cloud, and this approach makes data security an important and difficult issue. In order to ensure data security, cloud service providers must provide efficient and feasible mechanisms to provide reliable encryption methods and appropriate access control systems. This paper takes this as the main research content, focusing on the resource scheduling algorithm and its performance optimisation, voiceprint recognition technology and its optimisation, and the joint optimisation scheduling algorithm for the cloud data network security centre. The research proves that the performance of the voiceprint recognition and cloud computing data network system based on the genetic quantum particle optimisation joint scheduling algorithm proposed in this paper has been improved. It takes the system's network convergence speed as an index, and when the path scheme reuse rate is 30%, the network convergence speed is the fastest, and the convergence time is only 0.72 s.
  Keywords: scheduling joint optimisation algorithm; voiceprint recognition; cloud computing; data network security.
  DOI: 10.1504/IJGEI.2023.10054938
   
  

Special Issue on: Challenges and Sustainable in Energy

• Study of solidification performance of PCM in a triplex-tube thermal energy storage system with double Y-shaped fins  
  by Jun Du, Menghan Li, Fan Ren 
  Abstract: In this study, the phase change material is RT82, it has the disadvantages of low thermal conductivity, the Triplex-Tube Thermal Energy Storage System (TTESS) with double Y shaped fin is used to enhance heat conduction. In this paper, we used the commercial software FLUENT to study the influence of heat transfer fluid, fin material and fin structure parameters on the solidification process by evaluation indexes solidification time, heat release and PCM average temperature. The results show that when the fin length increases from 4 to 8 mm, the solidification time is reduced by 38.03%, the heat release in 180 s is increased by 4.21%, The fin width increased from 0.5 to 1.5 mm, the heat release in 180 s decreased by 5.03% and the solidification time of PCM decreased by 7.27%. Reasonable fin angle, HTF temperature and high-thermal conductivity fin material can also improve the heat transfer of the solidification process.
  Keywords: double Y-shaped fin; triplex-tube thermal energy storage system; numerical simulation; solidification.
  DOI: 10.1504/IJGEI.2023.10054591
   
  
• Thermodynamic and carbon emission analysis with low GWP refrigerants in automobile air conditioning system  
  by Salma Khatoon, Munawwar Nawab Karimi 
  Abstract: Automotive air conditioning systems negatively impact the environment through emissions. These emissions are impacted by ambient temperature and engine speed. Hence, this paper compares thermodynamic performance and carbon emissions of the low GWP refrigerants such as R1234yf, R1243zf, R450A, R143m, and R161 against R134a at different evaporator, condenser, and ambient temperatures and engine speeds. It is found that higher ambient temperatures lead to higher work consumption. Also, Indirect emissions have a positive correlation with engine speed. After R161, refrigerant R134a has the highest input power, total exergy destruction, and cooling capacity. R1243zf, R143m, and R450A show approximately similar cooling capacities. Furthermore, at idle speed, R134a indicates the highest Total Equivalent Warming Impact (TEWI) of 7.65 tons CO2 per year. Whereas, at normal and high speeds, R161 shows the highest value of 12.38 and 17.33tons CO2 per year, respectively. R1243zf, 1234yf, and R450A are the best alternative refrigerants to R134a.
  Keywords: Automobile air conditioners; GWP; refrigerants; energy; exergy; fuel consumption; Total Equivalent Warming Impact; carbon emissions; engine speed.
  DOI: 10.1504/IJGEI.2023.10056811
   
  
• Load flexible control method for wind and solar energy storage power plant considering the power side demand  
  by Yinghan Luo, Jincai Wu, Yanhong Ma 
  Abstract: In order to improve the accuracy of load flexible control and shorten the control time, a load flexible control method for wind and solar energy storage power plant considering the demand of the power side is proposed. Firstly, the data on the power side is cleaned and normalised according to the clustering results of Euclidean distance. Secondly, the normalised power side data is input into the support vector machine classification to complete the calculation of power side demand. Finally, the expected control quantity of wind turbine generator set is taken as the objective function of load flexible control, and the objective function is solved by particle swarm optimisation algorithm to complete the load flexible control of wind turbine storage power plant. The experimental results show that this method can improve the control accuracy, the maximum accuracy reaches 96%, and the maximum time consuming control does not exceed 3 minutes.
  Keywords: demand of the power side; wind and solar energy storage power plant; load flexible control; support vector machines.
  DOI: 10.1504/IJGEI.2023.10058732
   
  

Special Issue on: Intelligent Expert System in Non Conventional Energy Systems

• Smart plant propagation algorithm for the improvement of self-excited induction generator performance  
  by Swati Paliwal, Sanjay Kumar Sinha, Yogesh Kumar Chauhan 
  Abstract: India has taken effective initiatives to generate a massive amount of electrical power from wind energy. In order to strengthen the development of offshore wind power, self-excited induction generators (SEIG) have proven to be the best choice. But the global acceptance of this machine depends on its improved voltage and frequency regulation. Therefore, this work investigated the performance of SEIG in short and long shunt configurations under different loading conditions and at different power factors. This paper employs one of natures most unique and inspired techniques, Plant Propagation Algorithm (PPA), to improve machine performance in terms of flux or voltage. The PPA is based on the propagation strategy of the strawberry plant, which has the potential to colonise new areas in pursuit of better survival chances. From simulated results, it has been observed that the short shunt configuration requires lower shunt and series capacitance in order to improve SEIG performance.
  Keywords: self-excited induction generator; plant propagation algorithm; Newton Raphson method; loading conditions; simulated annealing; wind energy conversion system; machine flux or voltage.
  DOI: 10.1504/IJGEI.2023.10053981
   
  

Special Issue on: Intelligent Expert System in Non-Conventional Energy Systems

• Optimisation of computer network reliability based upon sensor technology and genetic algorithm  
  by Chengqing Gong 
  Abstract: In todays society, there has been a trend towards high digitisation, which means that the importance of computer networks is also increasing. Computer network reliability is the concept of measuring the security and stability of computer network system based on its importance. Nowadays, network reliability detection systems at home and abroad have their own standards. It is not conducive to the measurement between different system networks. This article is dedicated to optimising the reliability of the computer network, making it more convenient, quick and easy to operate. For this reason, this paper proposes a network reliability analysis algorithm based on sensor technology, and then uses genetic algorithm to optimise it. The proposed optimisation algorithm is to solve the problems of high algorithm complexity and low-computational efficiency. In the experiment, the original algorithm was compared with the optimised algorithm. A number of tests have also been conducted for network reliability analysis. Experimental results show that the optimised algorithm can increase the accuracy rate to more than 90%, and can recall a high percentage of correct matching pairs. The average time overhead is also around 300 ms.
  Keywords: sensor technology; genetic algorithm; computer network; reliability optimisation.
  DOI: 10.1504/IJGEI.2022.10052597
   
  
• Comparison between PID and PSO-PID controllers in analysing the load frequency control in interconnected microgrids in a deregulated environment  
  by Ranjit Singh, L. Ramesh 
  Abstract: This paper focuses on analysing the frequency error in interconnected microgrids and reducing the generation cost, which is considered one of the objective functions. The Simulink model shows the connection between 2microgrids, i.e., microgrid 1 comprises thermal, hydro and gas power plants, whereas microgrid 2 comprises thermal, nuclear and gas power plants. The change in the tie-line power is also considered while simulating the model. The papers main aim is to reduce the variations in frequency in each microgrid to ensure the steady flow of power among the connected microgrids along with the tie-line power. Also, the robustness of PID and PSO-PID Controllers are compared and analysed. The Particle swarm optimisation Algorithm codes tune the controllers gains in MATLAB. The model is simulated using MATLAB 2014b, and necessary graphs are obtained, which show the frequency error reduction time in both the microgrids.
  Keywords: MGs; microgrids; frequency error; LFC; load frequency control; tie line power; PID proportional integral derivative; controller; PSO; particle swarm optimisation.
  DOI: 10.1504/IJGEI.2023.10053492
   
  
• Design of remote data quantum system for geological oil extraction based on ARM and GPRS  
  by Hong Guo, Keping Zhai, Shien Liu, Xiuhua Shan 
  Abstract: With the rapid development of industrial automation, the control accuracy in industrial production has gradually improved and the control process has become more and more complex. Since then, the requirements for the security and real-time performance of the data collected on site have also been continuously improved, and high-quality, strong real-time data has played an important role in the entire control process. This article aims to study the design of a remote data quantum system for geological oil extraction based on ARM and GPRS, and put forward some related methods about quantum information and GPRS technology. In addition, experiments were conducted on a quantum system based on ARM and GPRS for remote data extraction of geological oil. The experimental results of this paper show that the remote data quantum system for geological oil extraction based on ARM and GPRS can detect the flow information of oil and water in the process of oil production in real-time. Moreover, it has played a great protective role in the remote transmission of data, and the security protection of data has been improved by 10%.
  Keywords: GPRS mobile communication; Modbus protocol; geological oil extraction; quantum information; quantum system design; remote data collection.
  DOI: 10.1504/IJGEI.2023.10054747
   
  
• Analysis and research of communication network system based on low power loss routing protocol  
  by Wenming Cai, Xin Niu 
  Abstract: In view of LLN communication network system has broad prospects for development. In this paper, the RPL routing protocol in the LLN communication network system is the main research content. Aiming at the deficiency of RPL routing protocol in high load communication network, a low power loss routing protocol based on load balancing LLN is proposed in this paper. This protocol can increase the connectivity and coverage of the communication network system, and can balance the data load of the network system effectively, improve the overall throughput of the communication network, further prolong the life cycle of the communication network system and ensure the normal communication work of the communication network system through the low power dissipation network routing protocol based on load balance LLN.
  Keywords: LLNs; load balancing; RPL; low power consumption; lossy network; routing protocol.
  DOI: 10.1504/IJGEI.2023.10055833
   
  
• Computer image processing and recognition technology under the background of new energy digitisation  
  by Qinghua Feng 
  Abstract: Threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and specific theory-based segmentation methods, etc. From a mathematical point of view, image segmentation is the process of dividing a digital image into mutually disjoint regions. Nowadays, the development of new energy has become an indispensable part. Therefore, it is of great significance to study computer image processing and recognition technology under the background of new energy digitisation. This paper introduces the theoretical knowledge of computer graphics, computer science and other related disciplines commonly used in computer vision algorithm, analyses some problems and defects in its practical application, and how to better solve these defects, and puts forward corresponding solutions to improve the reference value of new energy digital informatisation, provide some help for environment-friendly development. Then this paper introduces the processing methods of computer image processing and recognition technology. According to the application of the algorithm, this paper uses denoising and recognition technology to test the corresponding performance for the image blur caused by different noise. Finally, the test results show that the gray transformation can filter out the image noise and better maintain the edge definition and contour information of the image. The restoration results obtained by wavelet transform method are excellent. Denoising the observation data first and then constructing the weight matrix can get better denoising effect.
  Keywords: new energy digitisation; computer image; image processing; recognition technology.
  DOI: 10.1504/IJGEI.2023.10056062
   
  
• Field information monitoring system for micro-small quadrotor UAV based upon wireless sensor network  
  by Lei Gu, Juan Meng 
  Abstract: At present, information wireless sensor is a research hotspot. The wireless sensor network for drones provides a management method that can monitor farmland data. Farmland information collection is the research base of modern agriculture and digital agriculture. Its main content is to realise the dynamic, accurate and real-time monitoring of farmland geographical environment, soil structure, climate parameters, crop growth status and other information. Quadrotor drones are widely used in military, civilian, scientific research and education fields, and have the advantages of light weight, simple structure, low cost, and strong mobility. The influence of natural wind on quadrotor drones cannot be ignored, and it is one of the main reasons restricting the use of quadrotor drones. This paper takes quadrotor UAV as the research object, and studies a quadrotor UAV control system suitable for farmland data collection.
  Keywords: wireless sensor network; miniature quadrotor unmanned aerial vehicle; farmland information monitoring system; anti-wind disturbance.
  DOI: 10.1504/IJGEI.2023.10056389
   
  
• Automatic generation of civil engineering structure model based on network virtual reality  
  by HaiYang Yu, Changping Chen 
  Abstract: The rapid development of the data age makes it closely related to research work in various fields of life. This paper uses virtual reality technology to study the automation design of civil engineering process design. Based on the traditional AR technology framework, this article combines cloud platform technology to specialise in civil engineering firmware systems. By analysing the authenticity, flexibility, regionality and high-security requirements of the fusion of virtual reality and real-time network simulation, virtual reality technology analyses the simulation network based on the cloud platform and this paper further studies the support of multiple video stream node test sites. By providing virtual reality imaging technology and actual internet connection methods, it is found that when the transmission bandwidth is between 400 Mb/s and 800 Mb/s, the packet loss rate does not exceed 0.01%. This small packet loss has almost no effect on normal network communication.
  Keywords: network simulation; steel structure; three-dimensional network; cloud platform.
  DOI: 10.1504/IJGEI.2023.10056391
   
  
• The global mapping of education and public outreach on geothermal energy  
  by Riina Syivarulli, Nugroho Agung Pambudi, Cucuk Wawan Budiyanto 
  Abstract: There is currently a global discussion related to education and public outreach on geothermal energy due to the wide application of this energy source in several fields. Moreover, people with high knowledge and trust have been observed to play a significant role in developing world energy infrastructure. This research aimed to provide an overview of the education and public outreach distribution of geothermal energy in different countries of the world. A systematic literature review was used through the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) method. The findings showed that the European continent has the highest number of articles, 48%, related to education and public outreach on geothermal energy due to its high energy development effort, followed by the USA with 21%, while Asia, Oceania, and Africa with 19%, 4%, and 8% respectively have not implemented geothermal energy.
  Keywords: education and public outreach; geothermal energy; sustainable energy; systematic literature review.
  DOI: 10.1504/IJGEI.2023.10056812
   
  
• Modelling of optimal transportation route selection based on artificial bee colony algorithm  
  by Honggang Liu, Peilin Zhang, Hua Wu 
  Abstract: Optimising enterprise management and reducing logistics costs have become the common focus of Chinese logistics companies. This study mainly discusses the modelling of optimal transportation route selection based on artificial bee colony algorithm. In this paper, the designed bee colony algorithm is used to solve the cross-dock vehicle scheduling part in the mathematical model, and the cross-dock gate allocation and vehicle parking sequence scheduling schemes are obtained. Then, the scheduling scheme is used as the known condition of the path optimisation part, and the vehicle transportation path is optimised by using the bee colony algorithm, and the total cost is minimised in the process of mutual iteration. The research results show that the proportion of leading bees is 70% when the best calculated average value is obtained, and 90% when the variance of the calculated results is the smallest.
  Keywords: artificial bee colony algorithm; transportation mode; optimal path; selection modelling.
  DOI: 10.1504/IJGEI.2023.10056904
   
  

Special Issue on: Smart Energy Infrastructures for Smart Cities

• Cloud computing load balancing based on improved genetic algorithm  
  by Fengxia Zhu 
  Abstract: In the cloud computing environment, when most users request services, how to quickly and reasonably allocate a large number of tasks to a single virtual resource node and achieve parallelism is one of the research topics of current researchers. The key to this method in load balancing technology is load programming, whose quality directly affects the performance of the equalisation system. Therefore, this paper starts with distributed cloud computing technology and virtualisation technology, reveals the concept and method of load balancing implementation, and proposes an improved genetic load balancing algorithm. Traditional genetic algorithms can be used as meta-heuristic algorithms with slow convergence problems. We used the Cloudsim open source cloud simulation platform for simulation. The results show that compared with the traditional genetic algorithm, the improved genetic algorithm can better adapt to the load balancing requirements in the cloud computing environment and improve the balance and efficiency of resource utilisation.
  Keywords: improved genetic algorithm; cloud computing; load balancing; virtualisation technology.
  DOI: 10.1504/IJGEI.2023.10054590
   
  
• Secure application-centric service authentication with regression learning for security systems in smart city applications  
  by Pei Yang, Guoqiang You 
  Abstract: Smart city applications rely on different security paradigms for meeting the user demands and authenticated service disseminations. Diverse applications require different security modifications for improving the smart city contract-level application support. The challenging task is security adaptability and its improvements for smart city scenarios. In this article, a Secure Application-Centric Service Authentication (SACSA) is introduced for leveraging end-to-end authentication. This scheme introduces group key-based authentication for securing services in an end-to-end manner. The proposed scheme administers security using batch keys to improve the sharing efficiency of different services. The security and service time rely on the application type and distinct intervals, providing less complex and time-consuming security. In this process, blockchain is applied to perform the grouping, key generation and authentication recommendation in collaboration with the regression learning. Through this learning, batch consecutiveness is identified for improving application security. In the proposed scheme, authentication and key generation are performed using the Merkle Hash tree to prevent replication and decrease distribution. The proposed schemes performance is analysed using the metrics authentication time, complexity, service failure, and service latency. Thus, the SACSA system maintains system security with minimum authentication time, complexity, service failure, and latency of 9.45%, 7.75%, 9.2%, and 9.39%, respectively.
  Keywords: blockchain; group key; IoT; Merkle hash.
  DOI: 10.1504/IJGEI.2023.10055115
   
  
• Pricing mechanism and estimation model of integrated energy service products  
  by Lingyuan Ge, Yanni Tan, Jianping Ren, Rong Wei, Zhaoli Wang 
  Abstract: In the context of energy shortage, the concepts of energy revolution and supply-side reform and development require the energy sector, to further promote the energy revolution, strive to promote the transformation of energy production and development, optimise the energy supply structure, improve energy efficiency, build a clean, low-carbon, safe and efficient modern energy system, and maintain national energy security. The current research on the pricing mechanism and estimation model of integrated energy services is not thorough enough. In this paper, we introduce a consistent pricing strategy and analyse the optimal decision and profit situation of manufacturers and retailers within the framework of this pricing strategy. It is found that the differentiated pricing strategy outperforms the unified pricing strategy in most cases for manufacturers and the entire supply chain. When consumers have moderate preferences for the online channel, a manufacturers choice of a uniform pricing strategy can make it more affordable for manufacturers and suppliers, with less lost profit for the entire chain. In addition, when manufacturers have low pricing power (p < 55), they are more inclined to go for a consistent pricing strategy.
  Keywords: integrated energy services; factor analysis; approximate ideal knot analysis; pricing mechanism.
  DOI: 10.1504/IJGEI.2023.10056259
   
  
• Comprehensive energy service operation mode and benefit evaluation model  
  by Yanni Tan, Lingyuan Ge, Jianping Ren, Rong Wei, Zhaoli Wang 
  Abstract: This paper mainly studies the benefits of integrated energy services under the modes of independent investment and operation, independent investment and entrusted operation, cooperative investment and operation, and cooperative investment and entrusted operation. It also constructs a corresponding model for benefit evaluation and analysis by means of the subject feature method. This paper selects the integrated energy system of an industrial park in Southwest China as the research object. By analysing the operation modes of three different participating entities, this paper analyses their benefits by combining the cost-benefit model, and concludes that the State Grid Corporation has the greatest benefit under the independent investment and operation mode. The research results of this paper have certain practical guiding significance for the operation mode and benefit maximisation of integrated energy services.
  Keywords: integrated energy services; operation mode; cost-benefit model; subject characteristics.
  DOI: 10.1504/IJGEI.2023.10056260
   
  
• Comprehensive energy service customer value evaluation model  
  by Wei Yao, Wei Han, Yong Zheng, Songyao Gao, Ran Li 
  Abstract: At present, there are a series of energy supply and consumption problems in society. The maintenance costs of heat, gas, electricity and other energy sources are high. The integrated energy system effectively reduces the contradiction between energy supply and demand and improves the comprehensive utilisation efficiency of energy through scientific and logical multi-source interconnection awareness. Based on the customer segmentation and customer value theory in the integrated energy field, this paper considers the current and potential costs of customers, and forms a comprehensive customer energy value estimation system. The combined weighting method based on the AHP-entropy weighting method weights the customer value evaluation index and establishes a density peak clustering algorithm based on the improved artificial bee colony. On this basis, a customer value evaluation model is established. The comprehensive energy customer value is collected, and the comprehensive energy adaptive service model of the integrated energy system is analysed.
  Keywords: model study; evaluation model; customer value evaluation; integrated energy service.
  DOI: 10.1504/IJGEI.2023.10056905
   
  
• Causes of concrete cracks in the construction of roads and bridges facing intelligent manufacturing technology  
  by Jinglian Zhen 
  Abstract: This paper takes concrete cracks in road and bridge construction as the research object, and realises intelligent activities such as analysis, reasoning, judgement, conception and decision-making in the manufacturing process through intelligent manufacturing. First, the basic characteristics of intelligent manufacturing technology are analysed, the apparent shape and characteristics of bridge deck cracks are introduced and the bridge deck paving structure with several typical cracks is numerically simulated using finite element software, and the theory of fracture mechanics is used to study the mechanical behaviour of bridge deck pavement working with cracks includes temperature stress, load stress and additional stress caused by differential settlement of the main beam. Finally, the influence of the pavement thickness, modulus, cement concrete cushion thickness and other parameters on the force of the pavement layer is analysed, and the sensitivity analysis of the pavement layer force is carried out.
  Keywords: intelligent manufacturing technology; road and bridge construction; bridge performance; bridge crack problem.
  DOI: 10.1504/IJGEI.2023.10057071
   
  
• Research of aerodynamic performance of high-speed train crossing canyon with CFD simulation  
  by Zheng Wang, Xiaoling Zhang, Mingkang Zhang, Yang Sun 
  Abstract: Based on computational fluid dynamics, the aerodynamic performance and safety of a train running in a typical canyon terrain are simulated by numerical simulation. By comparing the variation law of surface pressure and aerodynamic characteristics of the train with speed of 250km/h under the action of the canyon wind field at different speeds, under the action of different canyon wind speeds, the variation law of the surface pressure and aerodynamic load of the train at different positions is consistent; with the increase of wind speed, its aerodynamic The load increases sharply, and the tunnel environment at both ends of the canyon will have a corresponding impact on the train operation; when the speed of crosswind increases to 25m/s, its dangerous for the train running cross the canyon with speed of 250km/h.
  Keywords: high-speed trains; aerodynamics characteristics; CFD simulation; cross-wind effects; operation security.
  DOI: 10.1504/IJGEI.2023.10057235
   
  
• Indoor environment design of old-age green buildings based on environmental energy efficiency  
  by Yi Wu 
  Abstract: With the development of population ageing and the intensification of environmental pollution, the development of elderly care buildings suitable for the elderly population is also facing severe challenges. This paper aims to carry out the interior environment design of green senior care buildings based on environmental energy efficiency. This paper reversely adjusted the number and proportion of the population over 60 years old in China, and tested and compared the noise level of each measuring point. The experimental data shows that from the national annual average level, TECH and EFFCH have increased by 1.022 and 1.010, respectively, indicating that the total factor energy efficiency has been improved and increased. The value of TECH is greater than that of EFFCH, indicating that technological progress has a greater impact and can be done better.
  Keywords: environmental energy efficiency; factor analysis of old-age buildings; green buildings; interior environment design.
  DOI: 10.1504/IJGEI.2023.10057301
   
  
• Construction and risk prevention of real-time renewable energy internal control management system based on big data  
  by Qianqian Yu 
  Abstract: With the advent of the era of big data, more and more industries have opened a new management era. This paper aims to study the related systems of real-time renewable energy in the era of big data. Designs a real-time renewable energy internal control management system based on big data. It carries out risk prevention for the renewable energy management system. By testing the actual operation performance of the system, the results show that the information response and receiving ratio of the system is at least about 85%, and the highest is more than 99%, which can meet the basic requirements. In addition, even in the case of the data volume of 5000 KB per second, the system running space does not exceed 90% and there is enough running space. Therefore, the renewable energy internal control management system designed in this paper has certain feasibility and system stability.
  Keywords: real-time big data; renewable energy; internal control and management system; risk prevention and control.
  DOI: 10.1504/IJGEI.2023.10057390
   
  
• Development of a low-carbon economy with the dual transformation of economy and energy structure  
  by Xiang Huang, Huami Yi, Min Liu 
  Abstract: This article investigates the industry 4.0 recent shift toward a more environmentally responsible way of operation. Life Cycle Assessment (LCA) is used in this article to measure carbon emissions throughout the product development life cycle. An accurate accounting of carbon emissions must first be completed for this to work. Consequently, IoT technologies have been used to collect real-time data with confidence to monitor the environmental consequences of products throughout the life cycle. Energy efficiency, energy structure optimisation and market-based economic measures such as energy/carbon taxes have minimised energy consumption and carbon emissions under a long-term low-carbon strategy. The proposed method shows less-energy conservation rate of 15.6%, an emission rate of 11.8%, a high-energy efficiency rate of 94.5%, a production rate of 90.8% and a sensitivity rate of 97.6% compared to other methods.
  Keywords: carbon emission; GHG; greenhouse gas emissions; IoT; internet of things; low-carbon economy; LCA; life cycle assessment; GEM; GHG emission monitoring.
  DOI: 10.1504/IJGEI.2023.10057391
   
  
• Food safety supply chain from perspective of big data algorithm and energy efficiency  
  by Mian Deng, Yong Wang 
  Abstract: At present, food safety incidents emerge in an endless stream, so the relevant fields related to food safety issues have become a research hotspot. In order to effectively ensure food safety, it is necessary to control all aspects of the supply chain. In order to test the effect of Principal Component Analysis (PCA) and mutual Information Principal Component Analysis (MI-PCA) on the data set, the loss value and the predicted value of the data set were compared. The results show that the predicted value of PCA algorithm fluctuates obviously, while the predicted value of MI-PCA algorithm tends to be stable after 100 iterations. The prediction accuracy is also greater than 95%, and the prediction effect is good.
  Keywords: supply chain; data dimensionality reduction; principal component; food safety; energy efficiency.
  DOI: 10.1504/IJGEI.2023.10058831