Template-Type: ReDIF-Article 1.0 Author-Name: Jun Du Author-X-Name-First: Jun Author-X-Name-Last: Du Author-Name: Menghan Li Author-X-Name-First: Menghan Author-X-Name-Last: Li Author-Name: Fan Ren Author-X-Name-First: Fan Author-X-Name-Last: Ren Title: Study of solidification performance of PCM in a triplex-tube thermal energy storage system with double Y-shaped fins 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 mm 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 mm 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. Journal: Int. J. of Global Energy Issues Pages: 543-566 Issue: 6 Volume: 46 Year: 2024 Keywords: double Y-shaped fin; triplex-tube thermal energy storage system; numerical simulation; solidification. File-URL: http://www.inderscience.com/link.php?id=141895 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:543-566 Template-Type: ReDIF-Article 1.0 Author-Name: Salma Khatoon Author-X-Name-First: Salma Author-X-Name-Last: Khatoon Author-Name: Munawar Nawab Karimi Author-X-Name-First: Munawar Nawab Author-X-Name-Last: Karimi Title: Thermodynamic and carbon emission analysis with low GWP refrigerants in automobile air conditioning system 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 CO<SUB align=right><SMALL>2</SMALL></SUB> per year. Whereas, at normal and high speeds, R161 shows the highest value of 12.38 and 17.33 tons CO<SUB align=right><SMALL>2</SMALL></SUB> per year, respectively. R1243zf, 1234yf, and R450A are the best alternative refrigerants to R134a. Journal: Int. J. of Global Energy Issues Pages: 693-717 Issue: 6 Volume: 46 Year: 2024 Keywords: automobile air conditioners; GWP; refrigerants; energy; exergy; fuel consumption; total equivalent warming impact; carbon emissions; engine speed. File-URL: http://www.inderscience.com/link.php?id=141899 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:693-717 Template-Type: ReDIF-Article 1.0 Author-Name: Chengqing Gong Author-X-Name-First: Chengqing Author-X-Name-Last: Gong Title: Optimisation of computer network reliability based upon sensor technology and genetic algorithm Abstract: In today's 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. Journal: Int. J. of Global Energy Issues Pages: 39-58 Issue: 1/2 Volume: 46 Year: 2024 Keywords: sensor technology; genetic algorithm; computer network; reliability optimisation. File-URL: http://www.inderscience.com/link.php?id=135245 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:39-58 Template-Type: ReDIF-Article 1.0 Author-Name: Ranjit Singh Author-X-Name-First: Ranjit Author-X-Name-Last: Singh Author-Name: L. Ramesh Author-X-Name-First: L. Author-X-Name-Last: Ramesh Title: Comparison between PID and PSO-PID controllers in analysing the load frequency control in interconnected microgrids in a deregulated environment 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 two microgrids, 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 paper's 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 controller's 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. Journal: Int. J. of Global Energy Issues Pages: 112-136 Issue: 1/2 Volume: 46 Year: 2024 Keywords: MGs; microgrids; frequency error; LFC; load frequency control; tie-line power; PID proportional integral derivative; controller; PSO; particle swarm optimisation. File-URL: http://www.inderscience.com/link.php?id=135249 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:112-136 Template-Type: ReDIF-Article 1.0 Author-Name: Swati Paliwal Author-X-Name-First: Swati Author-X-Name-Last: Paliwal Author-Name: Sanjay Kumar Sinha Author-X-Name-First: Sanjay Kumar Author-X-Name-Last: Sinha Author-Name: Yogesh Kumar Chauhan Author-X-Name-First: Yogesh Kumar Author-X-Name-Last: Chauhan Title: Smart plant propagation algorithm for the improvement of self-excited induction generator performance 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 investigates the performance of SEIG in short and long shunt configurations under different loading conditions and at different power factors. This paper employs one of nature's 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. Journal: Int. J. of Global Energy Issues Pages: 137-156 Issue: 1/2 Volume: 46 Year: 2024 Keywords: self-excited induction generator; plant propagation algorithm; Newton Raphson method; loading conditions; simulated annealing; wind energy conversion system; machine flux or voltage. File-URL: http://www.inderscience.com/link.php?id=135250 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:137-156 Template-Type: ReDIF-Article 1.0 Author-Name: Hong Guo Author-X-Name-First: Hong Author-X-Name-Last: Guo Author-Name: Keping Zhai Author-X-Name-First: Keping Author-X-Name-Last: Zhai Author-Name: Shien Liu Author-X-Name-First: Shien Author-X-Name-Last: Liu Author-Name: Xiuhua Shan Author-X-Name-First: Xiuhua Author-X-Name-Last: Shan Title: Design of remote data quantum system for geological oil extraction based on ARM and GPRS 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%. Journal: Int. J. of Global Energy Issues Pages: 18-38 Issue: 1/2 Volume: 46 Year: 2024 Keywords: GPRS mobile communication; Modbus protocol; geological oil extraction; quantum information; quantum system design; remote data collection. File-URL: http://www.inderscience.com/link.php?id=135251 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:18-38 Template-Type: ReDIF-Article 1.0 Author-Name: Wenming Cai Author-X-Name-First: Wenming Author-X-Name-Last: Cai Author-Name: Xin Niu Author-X-Name-First: Xin Author-X-Name-Last: Niu Title: Analysis and research of communication network system based on low power loss routing protocol 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. Journal: Int. J. of Global Energy Issues Pages: 59-68 Issue: 1/2 Volume: 46 Year: 2024 Keywords: LLNs; load balancing; RPL; low power consumption; lossy network; routing protocol. File-URL: http://www.inderscience.com/link.php?id=135252 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:59-68 Template-Type: ReDIF-Article 1.0 Author-Name: Qinghua Feng Author-X-Name-First: Qinghua Author-X-Name-Last: Feng Title: Computer image processing and recognition technology under the background of new energy digitisation Abstract: 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, and 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 noises. 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. Journal: Int. J. of Global Energy Issues Pages: 1-17 Issue: 1/2 Volume: 46 Year: 2024 Keywords: new energy digitisation; computer image; image processing; recognition technology. File-URL: http://www.inderscience.com/link.php?id=135253 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:1-17 Template-Type: ReDIF-Article 1.0 Author-Name: Lei Gu Author-X-Name-First: Lei Author-X-Name-Last: Gu Author-Name: Juan Meng Author-X-Name-First: Juan Author-X-Name-Last: Meng Title: Field information monitoring system for micro-small quadrotor UAV based upon wireless sensor network 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. Journal: Int. J. of Global Energy Issues Pages: 157-175 Issue: 1/2 Volume: 46 Year: 2024 Keywords: wireless sensor network; miniature quadrotor unmanned aerial vehicle; farmland information monitoring system; anti-wind disturbance. File-URL: http://www.inderscience.com/link.php?id=135256 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:157-175 Template-Type: ReDIF-Article 1.0 Author-Name: HaiYang Yu Author-X-Name-First: HaiYang Author-X-Name-Last: Yu Author-Name: Changping Chen Author-X-Name-First: Changping Author-X-Name-Last: Chen Title: Automatic generation of civil engineering structure model based on network virtual reality 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. Journal: Int. J. of Global Energy Issues Pages: 69-89 Issue: 1/2 Volume: 46 Year: 2024 Keywords: network simulation; steel structure; three-dimensional network; cloud platform. File-URL: http://www.inderscience.com/link.php?id=135257 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:69-89 Template-Type: ReDIF-Article 1.0 Author-Name: Yinghan Luo Author-X-Name-First: Yinghan Author-X-Name-Last: Luo Author-Name: Jincai Wu Author-X-Name-First: Jincai Author-X-Name-Last: Wu Author-Name: Yanhong Ma Author-X-Name-First: Yanhong Author-X-Name-Last: Ma Title: Load flexible control method for wind and solar energy storage power plant considering the power side demand 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. Journal: Int. J. of Global Energy Issues Pages: 665-677 Issue: 6 Volume: 46 Year: 2024 Keywords: demand of the power side; wind and solar energy storage power plant; load flexible control; support vector machines. File-URL: http://www.inderscience.com/link.php?id=141914 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:665-677 Template-Type: ReDIF-Article 1.0 Author-Name: Fengxia Zhu Author-X-Name-First: Fengxia Author-X-Name-Last: Zhu Title: Cloud computing load balancing based on improved genetic algorithm 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. Journal: Int. J. of Global Energy Issues Pages: 191-207 Issue: 3/4 Volume: 46 Year: 2024 Keywords: improved genetic algorithm; cloud computing; load balancing; virtualisation technology. File-URL: http://www.inderscience.com/link.php?id=137051 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:191-207 Template-Type: ReDIF-Article 1.0 Author-Name: Riina Syivarulli Author-X-Name-First: Riina Author-X-Name-Last: Syivarulli Author-Name: Nugroho Agung Pambudi Author-X-Name-First: Nugroho Agung Author-X-Name-Last: Pambudi Author-Name: Cucuk Wawan Budiyanto Author-X-Name-First: Cucuk Wawan Author-X-Name-Last: Budiyanto Title: The global mapping of education and public outreach on geothermal energy 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 Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 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. Journal: Int. J. of Global Energy Issues Pages: 176-188 Issue: 1/2 Volume: 46 Year: 2024 Keywords: education and public outreach; geothermal energy; sustainable energy; systematic literature review. File-URL: http://www.inderscience.com/link.php?id=135263 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:176-188 Template-Type: ReDIF-Article 1.0 Author-Name: Bo-Yang Zhang Author-X-Name-First: Bo-Yang Author-X-Name-Last: Zhang Author-Name: Lei Shi Author-X-Name-First: Lei Author-X-Name-Last: Shi Author-Name: Jin-Yu Fan Author-X-Name-First: Jin-Yu Author-X-Name-Last: Fan Title: The power load prediction of green building based on multidimensional data mining Abstract: In order to solve the problems of low recall and precision and high-prediction error in traditional prediction methods, a power load prediction of green building based on multidimensional data mining is proposed. The initial clustering centre and feature weight of fuzzy <em>k</em>-means algorithm (FKM) clustering algorithm are optimised, and the improved FKM clustering algorithm is used to mine multi-dimensional green building power load data. The multi-dimensional data mining results were taken as sample data, and the Least Squares Support Vector Machine (LSSVM) model parameters were optimised by Particle Swarm Optimisation with Extended Memory (PSOEM) algorithm. The sample data were input into the optimised model to obtain the power load prediction results of green buildings. The experimental results show that the average recall rate and precision rate of the proposed method are 96.31% and 96.13%, respectively, and the prediction error rate fluctuates between -2% and 2%, indicating high-prediction accuracy. Journal: Int. J. of Global Energy Issues Pages: 635-650 Issue: 6 Volume: 46 Year: 2024 Keywords: multidimensional data mining; green building; power load prediction; FKM clustering algorithm; PSOEM-LSSVM model. File-URL: http://www.inderscience.com/link.php?id=141919 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:635-650 Template-Type: ReDIF-Article 1.0 Author-Name: Honggang Liu Author-X-Name-First: Honggang Author-X-Name-Last: Liu Author-Name: Peilin Zhang Author-X-Name-First: Peilin Author-X-Name-Last: Zhang Author-Name: Hua Wu Author-X-Name-First: Hua Author-X-Name-Last: Wu Title: Modelling of optimal transportation route selection based on artificial bee colony algorithm 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. Journal: Int. J. of Global Energy Issues Pages: 90-111 Issue: 1/2 Volume: 46 Year: 2024 Keywords: artificial bee colony algorithm; transportation mode; optimal path; selection modelling. File-URL: http://www.inderscience.com/link.php?id=135264 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:1/2:p:90-111 Template-Type: ReDIF-Article 1.0 Author-Name: Junjun Liu Author-X-Name-First: Junjun Author-X-Name-Last: Liu Title: An optimal load distribution method for distributed energy systems based on the improved particle swarm optimisation Abstract: In order to solve the problem of large load variance and high distribution scheme cost after the distributed energy system is integrated into the traditional large power grid, an optimal load distribution method for distributed energy systems based on the improved particle swarm optimisation algorithm is proposed in this paper. Firstly, four output models of the distributed energy system are established. With the minimum cost and the minimum system load variance as the objectives, a multi-objective function model is constructed. Considering the power limit, generation power limit and other restrictions, constraints are constructed to complete the construction of the optimal load distribution model of the distributed energy system. Finally, the PSO algorithm is introduced to update the optimal particles in the solution space through different iterative processes. Combined with quantum theory, the PSO algorithm is optimised to obtain the optimal load distribution scheme. The results show that the cost of the distribution scheme obtained by this method can be reduced by more than 30,000 Yuan, and its load variance value is smaller, so the method has certain research value. Journal: Int. J. of Global Energy Issues Pages: 651-664 Issue: 6 Volume: 46 Year: 2024 Keywords: improved particle swarm optimisation; distributed energy system; output model; multi-objective function; constraints; load distribution. File-URL: http://www.inderscience.com/link.php?id=141920 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:651-664 Template-Type: ReDIF-Article 1.0 Author-Name: Pei Yang Author-X-Name-First: Pei Author-X-Name-Last: Yang Author-Name: Guoqiang You Author-X-Name-First: Guoqiang Author-X-Name-Last: You Title: Secure application-centric service authentication with regression learning for security systems in smart city applications 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 scheme's 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. Journal: Int. J. of Global Energy Issues Pages: 208-230 Issue: 3/4 Volume: 46 Year: 2024 Keywords: blockchain; group key; IoT; Merkle hash. File-URL: http://www.inderscience.com/link.php?id=137057 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:208-230 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaoming Lin Author-X-Name-First: Xiaoming Author-X-Name-Last: Lin Author-Name: Fan Zhang Author-X-Name-First: Fan Author-X-Name-Last: Zhang Author-Name: Mi Zhou Author-X-Name-First: Mi Author-X-Name-Last: Zhou Author-Name: Jianlin Tang Author-X-Name-First: Jianlin Author-X-Name-Last: Tang Author-Name: Bin Qian Author-X-Name-First: Bin Author-X-Name-Last: Qian Author-Name: Wenqian Jiang Author-X-Name-First: Wenqian Author-X-Name-Last: Jiang Title: Power supply reliability evaluation of distribution network based on non-intrusive low-voltage power load identification and time series algorithm Abstract: In order to overcome the problem of low reliability evaluation accuracy existing in traditional power supply reliability evaluation methods, a new power supply reliability evaluation method based on non-invasive low-voltage power load identification and time series algorithm is proposed in this paper. Firstly, a non-invasive low-voltage power load acquisition device is designed, and the adaptive Gauss filtering method is used to denoise. Secondly, the characteristics of low-voltage power load are extracted, and the characteristic parameters are input into the limit learning machine model to complete the identification of low-voltage power load. Finally, the time series algorithm is used to calculate the power supply reliability evaluation index of the distribution network, and the power supply reliability evaluation of the distribution network is completed. The experimental results show that the proposed method has high accuracy of low-voltage power load identification and reliability evaluation, and the highest evaluation accuracy is 97%. Journal: Int. J. of Global Energy Issues Pages: 618-634 Issue: 6 Volume: 46 Year: 2024 Keywords: non-intrusive low-voltage power load identification; timing algorithm; distribution network; power supply reliability; Gaussian filtering. File-URL: http://www.inderscience.com/link.php?id=141921 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:618-634 Template-Type: ReDIF-Article 1.0 Author-Name: Li Zhang Author-X-Name-First: Li Author-X-Name-Last: Zhang Author-Name: Zhiyun Sun Author-X-Name-First: Zhiyun Author-X-Name-Last: Sun Author-Name: Jingjing Huang Author-X-Name-First: Jingjing Author-X-Name-Last: Huang Author-Name: Xiaolong Lu Author-X-Name-First: Xiaolong Author-X-Name-Last: Lu Author-Name: Hewei Chen Author-X-Name-First: Hewei Author-X-Name-Last: Chen Author-Name: Qizhen Wei Author-X-Name-First: Qizhen Author-X-Name-Last: Wei Title: Combined forecasting of terminal load based on grey depth belief network Abstract: In order to improve the prediction accuracy of electric energy consumption of civil aviation airport terminal, a combined prediction model of terminal load based on grey depth belief network is proposed. Firstly, the operation data of the airport is analysed to determine the main factors affecting the power consumption of the airport terminal. Then, the improved grey prediction model is established by using the historical data of electric energy consumption, and the grey prediction results, the characteristics of multidimensional historical power consumption data and the main factors affecting electric energy consumption are taken as the inputs of the deep belief network. Finally, the power consumption of the terminal is predicted based on this model. The experimental results show that the proposed grey depth belief network combination model has low prediction error, and the Mean Square Error (MSE) and Mean Relative Error (MRE) of the proposed model are 0.0988 and 0.0033. Journal: Int. J. of Global Energy Issues Pages: 567-584 Issue: 6 Volume: 46 Year: 2024 Keywords: grey model; deep belief network; urban transportation complex; load combination forecasting; passenger throughput; historical data of energy consumption; renewable energy. File-URL: http://www.inderscience.com/link.php?id=141922 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:567-584 Template-Type: ReDIF-Article 1.0 Author-Name: Jinding He Author-X-Name-First: Jinding Author-X-Name-Last: He Author-Name: Wenchao Qin Author-X-Name-First: Wenchao Author-X-Name-Last: Qin Title: Evaluation method of renewable energy absorptive capacity based on Monte Carlo Abstract: Because the traditional assessment method of renewable energy absorptive capacity has the problems of low assessment accuracy and long assessment time, a Monte Carlo-based assessment method of renewable energy absorptive capacity is proposed. First, build a renewable energy absorptive capacity evaluation system, obtain the evaluation indicators, then analyse the renewable energy wind output characteristics, extract the characteristics of renewable energy absorptive capacity and then set the maximum renewable energy absorptive capacity, the system power balance, the minimum conventional power technology output, and the minimum production cost as the optimisation objectives to establish a multi-objective function for evaluation. Finally, under the constraint conditions, the objective function is solved by Monte Carlo method, and the solution is the evaluation result. The simulation results show that the proposed method has higher accuracy and shorter evaluation time for renewable energy absorptive capacity evaluation. Journal: Int. J. of Global Energy Issues Pages: 603-617 Issue: 6 Volume: 46 Year: 2024 Keywords: Monte Carlo; renewable energy; absorptive capacity; wind output; multi-objective function. File-URL: http://www.inderscience.com/link.php?id=141923 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:603-617 Template-Type: ReDIF-Article 1.0 Author-Name: Wenchao Qin Author-X-Name-First: Wenchao Author-X-Name-Last: Qin Author-Name: Jinding He Author-X-Name-First: Jinding Author-X-Name-Last: He Title: Research on adaptive dispatching of smart grid considering the cost of renewable energy power generation Abstract: In order to overcome the problems of poor convergence, high cost and long completion time of scheduling tasks in traditional methods, an adaptive dispatching method of smart grid considering the cost of renewable energy power generation is proposed. Firstly, the operation cost of smart grid is calculated from the total operation cost of conventional power generation unit, renewable energy power generation unit and energy storage unit. Then, combined with the benefits of flexible load, a smart grid adaptive dispatching model is built. Finally, under various constraints, the distributed reinforcement learning is used to solve the scheduling model and the adaptive scheduling results of smart grid are obtained. The experimental results show that the scheduling model solving algorithm of this method converges in 43 iterations, and the total operation cost of smart grid is 5.68 × 10<SUP align=right><SMALL>7</SMALL></SUP> yuan, and the scheduling task completion time is always less than 0.48 s. Journal: Int. J. of Global Energy Issues Pages: 585-602 Issue: 6 Volume: 46 Year: 2024 Keywords: cost of renewable energy power generation; smart grid; adaptive scheduling; conventional power generation unit; energy storage unit; distributed reinforcement learning. File-URL: http://www.inderscience.com/link.php?id=141924 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:585-602 Template-Type: ReDIF-Article 1.0 Author-Name: Yingjie Zhang Author-X-Name-First: Yingjie Author-X-Name-Last: Zhang Author-Name: Dongyuan Zhao Author-X-Name-First: Dongyuan Author-X-Name-Last: Zhao Title: A prediction method of regional carbon emission peak based on energy consumption elasticity coefficient Abstract: In order to solve the shortcomings of the traditional methods in prediction accuracy and prediction efficiency, this paper proposes a regional carbon emission peak prediction method based on the elastic coefficient of energy consumption. First, carbon emission information is extracted directionally. Then, the elastic coefficient of energy consumption is calculated, and the carbon emissions are preliminarily calculated. After obtaining the carbon emissions in different paths, Lasso regression analysis method is used to analyse the impact of the elastic coefficient of energy consumption on the prediction results. By adjusting the harmonic parameter values to optimise the calculation results, the peak prediction results of carbon emissions are obtained after obtaining significant variables. Experimental results show that the prediction accuracy of this method is high, and the maximum kappa coefficient can reach 0.973. During the experiment, the method can complete 12 predictions, which shows that its prediction efficiency is relatively high. Journal: Int. J. of Global Energy Issues Pages: 678-692 Issue: 6 Volume: 46 Year: 2024 Keywords: industrial carbon emissions; carbon emission performance; information extraction; elasticity coefficient of energy consumption; carbon emissions; lasso regression analysis; peak prediction. File-URL: http://www.inderscience.com/link.php?id=141926 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:6:p:678-692 Template-Type: ReDIF-Article 1.0 Author-Name: Lingyuan Ge Author-X-Name-First: Lingyuan Author-X-Name-Last: Ge Author-Name: Yanni Tan Author-X-Name-First: Yanni Author-X-Name-Last: Tan Author-Name: Jianping Ren Author-X-Name-First: Jianping Author-X-Name-Last: Ren Author-Name: Rong Wei Author-X-Name-First: Rong Author-X-Name-Last: Wei Author-Name: Zhaoli Wang Author-X-Name-First: Zhaoli Author-X-Name-Last: Wang Title: Pricing mechanism and estimation model of integrated energy service products 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 manufacturer's 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 (<em>p</em> < 55), they are more inclined to go for a consistent pricing strategy. Journal: Int. J. of Global Energy Issues Pages: 231-251 Issue: 3/4 Volume: 46 Year: 2024 Keywords: integrated energy services; factor analysis; approximate ideal knot analysis; pricing mechanism. File-URL: http://www.inderscience.com/link.php?id=137076 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:231-251 Template-Type: ReDIF-Article 1.0 Author-Name: Yanni Tan Author-X-Name-First: Yanni Author-X-Name-Last: Tan Author-Name: Lingyuan Ge Author-X-Name-First: Lingyuan Author-X-Name-Last: Ge Author-Name: Jianping Ren Author-X-Name-First: Jianping Author-X-Name-Last: Ren Author-Name: Rong Wei Author-X-Name-First: Rong Author-X-Name-Last: Wei Author-Name: Zhaoli Wang Author-X-Name-First: Zhaoli Author-X-Name-Last: Wang Title: Comprehensive energy service operation mode and benefit evaluation model 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. Journal: Int. J. of Global Energy Issues Pages: 252-273 Issue: 3/4 Volume: 46 Year: 2024 Keywords: integrated energy services; operation mode; cost-benefit model; subject characteristics. File-URL: http://www.inderscience.com/link.php?id=137077 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:252-273 Template-Type: ReDIF-Article 1.0 Author-Name: Wei Yao Author-X-Name-First: Wei Author-X-Name-Last: Yao Author-Name: Wei Han Author-X-Name-First: Wei Author-X-Name-Last: Han Author-Name: Yong Zheng Author-X-Name-First: Yong Author-X-Name-Last: Zheng Author-Name: Songyao Gao Author-X-Name-First: Songyao Author-X-Name-Last: Gao Author-Name: Ran Li Author-X-Name-First: Ran Author-X-Name-Last: Li Title: Comprehensive energy service customer value evaluation model 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. Journal: Int. J. of Global Energy Issues Pages: 274-294 Issue: 3/4 Volume: 46 Year: 2024 Keywords: model study; evaluation model; customer value evaluation; integrated energy service. File-URL: http://www.inderscience.com/link.php?id=137083 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:274-294 Template-Type: ReDIF-Article 1.0 Author-Name: Jinglian Zhen Author-X-Name-First: Jinglian Author-X-Name-Last: Zhen Title: Causes of concrete cracks in the construction of roads and bridges facing intelligent manufacturing technology 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. Journal: Int. J. of Global Energy Issues Pages: 295-309 Issue: 3/4 Volume: 46 Year: 2024 Keywords: intelligent manufacturing technology; road and bridge construction; bridge performance; bridge crack problem. File-URL: http://www.inderscience.com/link.php?id=137084 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:295-309 Template-Type: ReDIF-Article 1.0 Author-Name: Zheng Wang Author-X-Name-First: Zheng Author-X-Name-Last: Wang Author-Name: Xiaoling Zhang Author-X-Name-First: Xiaoling Author-X-Name-Last: Zhang Author-Name: Mingkang Zhang Author-X-Name-First: Mingkang Author-X-Name-Last: Zhang Author-Name: Yang Sun Author-X-Name-First: Yang Author-X-Name-Last: Sun Title: Research of aerodynamic performance of high-speed train crossing canyon with CFD simulation 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 250 km/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 25 m/s. It's dangerous for the train running cross the canyon with speed of 250 km/h. Journal: Int. J. of Global Energy Issues Pages: 310-326 Issue: 3/4 Volume: 46 Year: 2024 Keywords: high-speed trains; aerodynamics characteristics; CFD simulation; cross-wind effects; operation security. File-URL: http://www.inderscience.com/link.php?id=137086 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:310-326 Template-Type: ReDIF-Article 1.0 Author-Name: Yi Wu Author-X-Name-First: Yi Author-X-Name-Last: Wu Title: Indoor environment design of old-age green buildings based on environmental energy efficiency 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. Journal: Int. J. of Global Energy Issues Pages: 327-344 Issue: 3/4 Volume: 46 Year: 2024 Keywords: environmental energy efficiency; factor analysis of old-age buildings; green buildings; interior environment design. File-URL: http://www.inderscience.com/link.php?id=137087 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:327-344 Template-Type: ReDIF-Article 1.0 Author-Name: Qianqian Yu Author-X-Name-First: Qianqian Author-X-Name-Last: Yu Title: Construction and risk prevention of real-time renewable energy internal control management system based on big data 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. Journal: Int. J. of Global Energy Issues Pages: 345-364 Issue: 3/4 Volume: 46 Year: 2024 Keywords: real-time big data; renewable energy; internal control and management system; risk prevention and control. File-URL: http://www.inderscience.com/link.php?id=137090 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:345-364 Template-Type: ReDIF-Article 1.0 Author-Name: Xiang Huang Author-X-Name-First: Xiang Author-X-Name-Last: Huang Author-Name: Huami Yi Author-X-Name-First: Huami Author-X-Name-Last: Yi Author-Name: Min Liu Author-X-Name-First: Min Author-X-Name-Last: Liu Title: Development of a low-carbon economy with the dual transformation of economy and energy structure 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. Journal: Int. J. of Global Energy Issues Pages: 365-388 Issue: 3/4 Volume: 46 Year: 2024 Keywords: carbon emission; GHG; greenhouse gas emissions; IoT; internet of things; low-carbon economy; LCA; life cycle assessment; GEM; GHG emission monitoring. File-URL: http://www.inderscience.com/link.php?id=137091 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:365-388 Template-Type: ReDIF-Article 1.0 Author-Name: Mian Deng Author-X-Name-First: Mian Author-X-Name-Last: Deng Author-Name: Yong Wang Author-X-Name-First: Yong Author-X-Name-Last: Wang Title: Food safety supply chain from perspective of big data algorithm and energy efficiency 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. Journal: Int. J. of Global Energy Issues Pages: 389-405 Issue: 3/4 Volume: 46 Year: 2024 Keywords: supply chain; data dimensionality reduction; principal component; food safety; energy efficiency. File-URL: http://www.inderscience.com/link.php?id=137098 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:389-405 Template-Type: ReDIF-Article 1.0 Author-Name: Auguste Mpacko Priso Author-X-Name-First: Auguste Mpacko Author-X-Name-Last: Priso Author-Name: Souleymane Doumbia Author-X-Name-First: Souleymane Author-X-Name-Last: Doumbia Title: Price and volatility of rare earths 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 for many other applications, including volatility forecasts of rare earths price. This latter can help investors improve their decision-making process. Journal: Int. J. of Global Energy Issues Pages: 436-453 Issue: 5 Volume: 46 Year: 2024 Keywords: metal prices; rare earths; climate change; volatility models; ARCH; GARCH models. File-URL: http://www.inderscience.com/link.php?id=140736 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:436-453 Template-Type: ReDIF-Article 1.0 Author-Name: Donia Aloui Author-X-Name-First: Donia Author-X-Name-Last: Aloui Author-Name: Rafla Hchaichi Author-X-Name-First: Rafla Author-X-Name-Last: Hchaichi Author-Name: Khaled Guesmi Author-X-Name-First: Khaled Author-X-Name-Last: Guesmi Title: Oil market crashes: from the subprime crisis to the COVID-19 pandemic 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 behaviour 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. Journal: Int. J. of Global Energy Issues Pages: 419-435 Issue: 5 Volume: 46 Year: 2024 Keywords: COVID-19; subprime crisis; oil price war; negative WTI oil price; natural gas; TVP-BVAR-SV model; stochastic volatility; forecasting. File-URL: http://www.inderscience.com/link.php?id=140746 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:419-435 Template-Type: ReDIF-Article 1.0 Author-Name: Huifang Qian Author-X-Name-First: Huifang Author-X-Name-Last: Qian Author-Name: Yunhao Luo Author-X-Name-First: Yunhao Author-X-Name-Last: Luo Author-Name: Xuan Zhou Author-X-Name-First: Xuan Author-X-Name-Last: Zhou Author-Name: Ren-Ying Li Author-X-Name-First: Ren-Ying Author-X-Name-Last: Li Author-Name: Jiahao Guo Author-X-Name-First: Jiahao Author-X-Name-Last: Guo Title: Ultra short-term wind power prediction based on lightweight learning machine with error compensation Abstract: The wind power prediction model has been improved in order to obtain higher prediction accuracy, but this model structure then becoming complicated and the training time is prolonged. Therefore, this paper proposes a Lightweight Learning Machine with Error Compensation (LLM-EC), which consists of two parts: prediction and error compensation. The Lightweight Learning Machine (LLM) accomplishes the prediction part by learning the historical patterns of wind energy and related factors. To improve prediction accuracy, this paper incorporates an Improved Temporal Attention Mechanism (ITAM) into LLM. In the error compensation part, the prediction results of the LLM are re-compensated using the Error Compensation Machine (ECM) to reduce the error accumulation during the rolling prediction process. Finally, a comparison of the benchmark model with LLM-EC in terms of prediction accuracy, training time, and memory usage reveals that LLM-EC has significantly less prediction error; less training time; and less memory occupied by the model. Journal: Int. J. of Global Energy Issues Pages: 463-482 Issue: 5 Volume: 46 Year: 2024 Keywords: ultra short-term wind power; lightweight construction; attention mechanism; error compensation. File-URL: http://www.inderscience.com/link.php?id=140764 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:463-482 Template-Type: ReDIF-Article 1.0 Author-Name: Ryan Holmes Author-X-Name-First: Ryan Author-X-Name-Last: Holmes Author-Name: Darren McCauley Author-X-Name-First: Darren Author-X-Name-Last: McCauley Author-Name: Thomas Muinzer Author-X-Name-First: Thomas Author-X-Name-Last: Muinzer Title: Reassessing fossil fuels in a time of disruption: hydrogen, natural gas and future possibilities Abstract: Energy governance is undergoing a period of uncertainty as a result of climate related challenges and these uncertainties have been profoundly exacerbated by the COVID-19 pandemic. The stage of uncertainty energy governance is experiencing can be characterised as one of disruption. This study reassesses the condition of energy governance in the context of disruption with particular reference to the role that hydrogen and natural gas might play in going forward. In doing so, it places an emphasis on the protracted impact of disruption occasioned by climate change regulation. Greater understanding of the strengths and weaknesses that stabilising options provide, and of their relationship to the broader complex disruptive forces that they interact with, will assist in better illuminating present and future challenges underlying the governance of energy. Journal: Int. J. of Global Energy Issues Pages: 454-462 Issue: 5 Volume: 46 Year: 2024 Keywords: energy governance; energy transition; just transition; hydrogen; natural gas. File-URL: http://www.inderscience.com/link.php?id=140766 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:454-462 Template-Type: ReDIF-Article 1.0 Author-Name: Ermanno Affuso Author-X-Name-First: Ermanno Author-X-Name-Last: Affuso Author-Name: Alex Sharland Author-X-Name-First: Alex Author-X-Name-Last: Sharland Title: Energy consumption, income and carbon emissions in the Caribbean community Abstract: This original research uses a panel vector autoregressive model to study the relationship between energy consumption, carbon emissions and the macroeconomic dynamics of 14 economies between 1960 and 2017; all full members of the Caribbean Community (CARICOM). The model is calibrated using economic and environmental public data from the World Development Indicators repository, the Climate Research Unit of the University of East Anglia and the FRED repository of the St. Louis Federal Reserve Bank. The study finds evidence of (i) positive unidirectional causality from energy consumption to economic growth, (ii) positive bidirectional causality between energy consumption and growth in carbon emissions and (iii) negative bidirectional causality between economic growth and carbon emission growth. Implications are discussed. Journal: Int. J. of Global Energy Issues Pages: 407-418 Issue: 5 Volume: 46 Year: 2024 Keywords: energy economics; development economics; macroeconomic dynamics; Caribbean; panel data. File-URL: http://www.inderscience.com/link.php?id=140768 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:407-418 Template-Type: ReDIF-Article 1.0 Author-Name: Aryan Tabrizi Author-X-Name-First: Aryan Author-X-Name-Last: Tabrizi Author-Name: Mohammad Sarvi Author-X-Name-First: Mohammad Author-X-Name-Last: Sarvi Title: Reliability evaluation, lifetime prediction and failure rate assessment of Li-ion batteries Abstract: Recently, rechargeable lithium-ion batteries (Li-ion) have been used as a suitable energy storage source in many applications due to their advantages. Reliability is a key factor in battery utilisation, same as any other process. It is essential to know how reliable a battery cell or pack is. Hence, it could be more precise to predict the failure time of the battery. The main multiple purposes of this paper are to assess the reliability of the typical battery packs/cells, to estimate their failure rate and to evaluate their lifetime by some probability distribution function. In each case, the proper approach is determined and the reliability of the battery alongside its predicted failure time is estimated. Also, it can be estimated what percentage of batteries (in stationary energy storage) are going to fail in a desirable operating time. Reliability calculations are performed within the Minitab software. Journal: Int. J. of Global Energy Issues Pages: 483-499 Issue: 5 Volume: 46 Year: 2024 Keywords: Li-ion battery; reliability; Weibull; failure rate; predicted lifetime. File-URL: http://www.inderscience.com/link.php?id=140769 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:483-499 Template-Type: ReDIF-Article 1.0 Author-Name: Anlin Li Author-X-Name-First: Anlin Author-X-Name-Last: Li Author-Name: Lede Niu Author-X-Name-First: Lede Author-X-Name-Last: Niu Author-Name: Yan Zhou Author-X-Name-First: Yan Author-X-Name-Last: Zhou Author-Name: Jingzhi Lin Author-X-Name-First: Jingzhi Author-X-Name-Last: Lin Title: Study on coupling coordination between ecosystem service value and carbon reserve based on land use change - taking Chengdu-Chongqing economic circle as an example Abstract: Taking the Chengdu Chongqing Economic Circle as an example, this study calculates its ecosystem service value, carbon storage, and coordinated development level. The conclusion is as follows: (1) from 2000 to 2010, land use was transformed into forest land>construction land>cultivated land>other land>water bodies>grasslands; from 2010 to 2020, construction land>water body>other land>forest land>grassland>cultivated land. (2) The ecosystem service values from 2000 to 2020 were 2842.78 × 108, 3114.35 × 108, and 2780.50 × 108 yuan, showing an inverted 'U' shape with a spatial distribution of 'high on the periphery and low on the interior'; from 2000 to 2020, the carbon storage was 57.87 × 108 t, 58.28 × 108 t, and 58.21 × 108 t, presenting a low value urban 'bipolar' pattern. (3) The relationship between ecosystem service value and carbon storage is clearly non coordinated, and there is no positive interaction between the two, resulting in weak coordination ability. Journal: Int. J. of Global Energy Issues Pages: 522-541 Issue: 5 Volume: 46 Year: 2024 Keywords: land use; ecosystem service value; carbon stock; coupled coordination; Chengdu-Chongqing area; twin-city economic circle. File-URL: http://www.inderscience.com/link.php?id=140778 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:522-541 Template-Type: ReDIF-Article 1.0 Author-Name: Zehao Li Author-X-Name-First: Zehao Author-X-Name-Last: Li Author-Name: Wenhui Liu Author-X-Name-First: Wenhui Author-X-Name-Last: Liu Author-Name: Minji Hu Author-X-Name-First: Minji Author-X-Name-Last: Hu Author-Name: Zongwen Zuo Author-X-Name-First: Zongwen Author-X-Name-Last: Zuo Title: Outward foreign direct investment and carbon emissions in the home country: evidence from China Abstract: The objective of this study is to investigate the impact and operational mechanism of Outward Foreign Direct Investment (OFDI) on domestic carbon emissions. We utilise panel data collected from 30 provinces spanning the period between 2004 and 2017 for our analysis. The results show that OFDI has a significant inverse U-curve relationship to carbon emissions. After the robustness test, the results still hold. Heterogeneity analysis shows that in eastern China and economically developed regions, OFDI and carbon emissions show a significant <em>U</em>-shaped reversal. The analysis of mechanisms reveals that there exists a threshold effect in the impact process of OFDI on regional carbon emissions, particularly influenced by the share of the tertiary sector. When the tertiary sector share is higher than 73.2%, that is, when the industrial structure tends to be highly developed, the improvement of OFDI will reach the goal of carbon emission reduction. This paper offers policy recommendations for China, aiming to facilitate the expansion of OFDI, drive the enhancement of regional industrial structure and ultimately work towards achieving the objective of 'attaining carbon peak and carbon neutrality'. Journal: Int. J. of Global Energy Issues Pages: 500-521 Issue: 5 Volume: 46 Year: 2024 Keywords: OFDI; carbon emission reduction; industrial structure; the goal of carbon peak; carbon neutrality. File-URL: http://www.inderscience.com/link.php?id=140779 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:46:y:2024:i:5:p:500-521