Forthcoming and Online First Articles

International Journal of Energy Technology and Policy

International Journal of Energy Technology and Policy (IJETP)

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International Journal of Energy Technology and Policy (6 papers in press)

Regular Issues

  • Recent technological advances in the production of green hydrogen: a review   Order a copy of this article
    by Alvaro Ferney Algarra Rincon, Samuel Alberto Ouana, Tania Cristina De Souza, Daniel Azevedo Vieira, Jéssica De Oliveira Notório Ribeiro 
    Abstract: Hydrogen is recognised as the fuel of the future and a key component for sustainable energy transition in all spaces that currently use fossil fuels, such as the electricity, transport, and industrial sector. The most widely used hydrogen production process is water electrolysis and often requires large amounts of energy. However, to obtain clean hydrogen, it is essential that it comes from renewable and sustainable sources. Therefore, this article reviews the most recent advances in green hydrogen production technologies published during the 2019-2023 period. A global overview of green hydrogen production is compiled in this article, and studies on the mechanisms of electrolysis, photocatalysis and thermochemical cycles for water decomposition are also presented, as are new strategies for integrating technologies and efforts designed to make production more sustainable and competitive with conventional methods. Thermochemical cycle technology, it was identified as one of the most promising to produce green hydrogen.
    Keywords: energy transition; green hydrogen; production technologies.
    DOI: 10.1504/IJETP.2024.10063697
  • Underlying the impact of information communication technology and renewable-non-renewable energy on environmental sustainability under the shadow of industrial waste management a fresh insight from China   Order a copy of this article
    by Kiran Jameel, Saima Tabassum, Atteeq Razzak, Laeeq Janjua, Shaher Bano 
    Abstract: Due to rapid economic growth and a high population, China is the largest energy user and CO2 emitter. This research examines China's renewable energy (RE) use and its relationship to CO2 emissions, industrial waste (IW), NRE, and ICT consumption. ARDL estimation was used to determine the long-term co-integration of variables for the data from 2000 to 2022 of China. The study output shows that ICT and NRE have a significant negative relationship with REC, and a 1% increase in ICT and NRE will respond to a decrease of 1.18% and 1.005% in REC. Furthermore, CO2 has a positive relation with REC, and a 1% increase in CO2 will result in an upsurge of 2.98% in REC. According to robustness check through (FMOLS) and (DOLS) estimators; empirical evidence shows there is a significant effect at a 5% level of significance of the variables NRE, IW, ICT CO2 on REC in China in the long run.
    Keywords: renewable energy consumption; environment degradation; CO2 emission; industrial waste; information communication technology; non-renewable energy consumption; ARDL; China.
    DOI: 10.1504/IJETP.2024.10064297
  • A multi-objective optimisation of relay protection settings in distribution networks based on improved grey wolf algorithm   Order a copy of this article
    by Haicheng Zhou, Hengchu Shi, Qiutao Chen, Penghui Yang, Xi Zhang 
    Abstract: In order to overcome the problems of high data mining accuracy, poor effectiveness, and long relay protection action time in traditional methods, a multi-objective optimisation method of relay protection settings in distribution networks based on improved grey wolf algorithm is proposed. Random forest algorithms is used for mining relay protection data in distribution networks. Taking the relay protection settings as the parameters to be optimised, a multi-objective optimisation function for relay protection settings is constructed using parameters such as relay protection action time, transmission line weight coefficient, and weight factors of vulnerability and sensitivity constraints. The improved grey wolf algorithm is used to solve the objective function and obtain relevant results. According to the analysis of relevant test results, the maximum data mining accuracy of the proposed method is 98.75%, good optimisation effect, and a maximum relay protection action time of 0.87 s.
    Keywords: improved grey wolf algorithm; distribution network; relay protection settings; multi-objective optimisation; random forest algorithms; objective function.
    DOI: 10.1504/IJETP.2024.10064333
  • A method for power equipment condition monitoring and fault location based on improved ant colony algorithm   Order a copy of this article
    by Wei Tong, Qi-ping Huang 
    Abstract: Different malfunctions may arise during the operation of power equipment, impacting the quality and dependability of the power supply. Conventional monitoring techniques face challenges, prompting the introduction of a novel power equipment monitoring and fault localisation method based on an enhanced ant colony algorithm. This approach entails gathering operational signals from the power equipment and amalgamating singular value decomposition with particle filtering methods to oversee the equipment’s condition. Through enhancements to the pheromone configuration and update approach of the ant colony algorithm, a fault localisation assessment function is formulated to achieve precise fault localisation. Empirical findings have illustrated that this method has the capability to promptly monitor equipment status and attain fault localisation accuracy surpassing 90%.
    Keywords: improving ant colony algorithm; electrical equipment; condition monitoring; fault location.
    DOI: 10.1504/IJETP.2024.10064334
  • Detection method of icing thickness of overhead transmission lines based on canny algorithm   Order a copy of this article
    by Yang Yang, Shenbing Hua, Hongxia Wang, Meng Li, Qifei He, Minguan Zhao, Yuanhao Wan, Shuyang Ma 
    Abstract: Proposing a novel detection approach utilising the canny algorithm to address the low accuracy issues in traditional icing thickness detection on overhead transmission lines. Employing an unmanned aerial vehicle equipped with a camera for collecting icing images, noise interference is mitigated via compressive sensing theory. Converting the images into greyscale to enable edge detection using the canny algorithm. Utilising random Hough transform for extracting edge lines, which are then fused with edge images for subsequent processing and ice thickness calculation. Experimental results validate the substantial enhancement in detection accuracy and efficiency for icing thickness detection on overhead transmission lines with the application of this method.
    Keywords: canny algorithm; overhead transmission lines; thickness of ice cover; test method.
    DOI: 10.1504/IJETP.2024.10064335
  • Carbon emissions prediction method of industrial parks based on NSGA-II multi objective genetic algorithm   Order a copy of this article
    by Peidong He, Xiaojun Li, Shuyu Deng, Yaxin Tu, Wenqi Shen 
    Abstract: In order to address the significant discrepancies between the predicted results of existing industrial carbon emission forecasting methods and the actual results, this study investigates the prediction method of carbon emissions in industrial parks based on the NSGA-II multi-objective genetic algorithm. Firstly, the carbon emission prediction indicators are determined. Then, the normalisation method is applied to preprocess the indicator sample data and calculate the carbon emission prediction indicators for nine industrial parks. Lastly, based on the NSGA-II multi-objective genetic algorithm, non-dominated sorting and crowding distance are calculated to solve the objective function and achieve the prediction of carbon emissions in industrial parks. Through experimental verification, it has been demonstrated that the average absolute error of the prediction results in this study does not exceed 0.15, and the root mean square error remains below 0.10. This indicates that using the proposed method in this study can effectively reduce errors in carbon emission prediction for the industrial parks, resulting in good prediction performance.
    Keywords: industrial park; prediction of carbon emissions; NSGA-II multi-objective genetic algorithm; fitness function.
    DOI: 10.1504/IJETP.2024.10064337