International Journal of Energy Technology and Policy (9 papers in press)

Special Issue on: OA Multiscale Energy Systems for Renewable Energy Storage Part Two

• Open Access

  Analysis on the development path of rural energy digital economy from the perspective of artificial intelligence ( Free Full-text Access )

  by Lu Chen 
  Abstract: This paper aims to explore the development path of the energy digital economy from the perspective of artificial intelligence and predict its future development trends. This paper selects Tangsteel Group as the research object, and divides the energy digital economy construction with and without artificial intelligence technology into Group A and Group B respectively, and conducts a comparative analysis of Group A and Group B from four aspects: efficiency, safety, cost and accuracy. The experimental results show that: the efficiency of Group A enterprises can reach up to 91.35%; the overall security level of Group A enterprises is greater than 82%; there is no significant difference in cost between Group A and Group B, but Group A can reduce costs through optimisation. Therefore, the popularisation and widespread application of AI technology in the energy sector can greatly promote the digitalisation and intelligentisation of the entire industry.
  Keywords: digital economy; energy development; artificial intelligence; path analysis; Tangshan Steel.
  DOI: 10.1504/IJETP.2025.10074603
   
  

• Open Access

  Quality inspection of power transmission towers based on point cloud registration ( Free Full-text Access )

  by Xuan Qi, Honglin Yan, Xiao Tu, Yinying Liu, Weihua Ding 
  Abstract: To address the inefficiency in feature point extraction and registration caused by the complex structure of power transmission towers, this study proposes a feature registration strategy incorporating curvature feature. Given the critical role of power transmission infrastructure in smart grid systems, accurate and efficient tower modelling is essential for ensuring structural safety and operational reliability. First, an algorithm based on normal vector angles is employed to obtain an initial set of feature points. Subsequently, high-curvature points rich in geometric information are identified and retained through Gaussian curvature analysis. This approach enhances feature distinctiveness compared to uniform sampling or intensity-based selection methods. To further enhance registration efficiency, Gaussian curvature parameters are introduced into the random sample consensus (RANSAC) algorithm for preliminary matching. This integration significantly reduces the number of incorrect correspondences compared to standard RANSAC implementations. Additionally, a symmetric objective function optimises the iterative closest point (ICP) algorithm to achieve precise registration across surfaces with varying characteristics. Unlike conventional ICP, which assumes consistent surface normals, the proposed method handles asymmetric structures more effectively. Finally, by using 3D inspection software to compare the registered point cloud with a standard model, accurate quality assessment data for power transmission towers are obtained.
  Keywords: iterative closest point; ICP; power transmission; Gaussian curvature; random sample consensus; RANSAC; 3D inspection.
  DOI: 10.1504/IJETP.2025.10074604
   
  

• Open Access

  Flow field analysis of agitated displacement tank for cementing equipment ( Free Full-text Access )

  by Lin Hou, Chunxia Chen, Rongxing Jiang, Wei Ji, Biao Lei, Mengfei Zhang, Yunrui Huang 
  Abstract: To address the problems of low mixing efficiency and uneven dispersion of additives in the mixing displacement tank of cementing equipment, this paper uses CFD simulation to analyse the influence of impeller parameters on flow field characteristics and optimise the mixing performance. This paper takes the cementing equipment stirring displacement tank as the research object and uses computational fluid dynamics (CFD) to analyse the mixing effect of the stirring displacement tank on liquid additives and clean water. The distribution results of liquid additives, clean water, and fluids with a flow rate greater than 0.5 m/s are obtained. Comparative analysis of the simulation results showed that increasing the rotational speed is the best way to enhance the fluidity of the fluid in the tank. The inclined impeller is conducive to the lateral flow of the fluid, while the vertically arranged impeller is conducive to the vertical upward movement of the fluid.
  Keywords: agitated displacement tank; agitating performance; rotational speed; impeller; CFD simulation; fluid mixing performance.
  DOI: 10.1504/IJETP.2025.10074704
   
  

• Open Access

  Reinforcement learning-based optimisation of intelligent battery thermal management system data ( Free Full-text Access )

  by Junda Ge 
  Abstract: Effective battery thermal management (BTMS) is vital for safety, longevity, and performance, yet rule-based or PID schemes falter under rapid operational changes. We propose an RL-driven BTMS that learns control policies in a high-fidelity thermal simulator. The agent observes cell temperature, state of charge, and ambient conditions, and outputs continuous cooling/heating commands. We adopt deep deterministic policy gradient to cope with nonlinear dynamics and continuous actions. For safety and generalisation, the learned policy is fused with a rule-based controller via a confidence-aware hybrid scheme. Tests on real driving cycles show 3.2 x faster response, 18.4% lower temperature-tracking MAE, and 18.0% less cooling energy than conventional BTMS, improving regulation efficiency and robustness. These results indicate deep RL with hybrid control is a scalable, adaptive, and safety-aware solution for intelligent BTMS.
  Keywords: reinforcement learning; electric vehicles; intelligent control; thermal optimisation.
  DOI: 10.1504/IJETP.2025.10074834
   
  

Regular Issues

• Carbon Neutrality: Evaluating the Impact of Carbon Emissions Trading Policy on Green Energy and Environmental Economic Efficiency  
  by Yanmei Li, Yi Zhang 
  Abstract: Amid rising global concern over climate change, China launched its carbon emissions trading pilot (CETP) in 2011 to promote green energy and low-carbon development. This study investigates the impact of CETP on green energy environmental and economic efficiency (GEEEE), using a new measurement index and the slack-based measure super-efficiency model. Treating the policy as a quasi-natural experiment and analysing its implementation across seven pilot provinces between 2009 and 2023, a difference-in-differences approach is employed to assess its effectiveness. We evaluate both the dynamic and spatial heterogeneity of the policys outcomes by examining variations across regions and industries. The findings suggest that the CETP significantly enhances GEEEE performance in the designated pilot areas. Moreover, this effect is amplified by three key mechanisms: technological innovation, energy and industrial restructuring, and regional policy responsiveness. These findings provide theoretical and practical insights for policymakers in designing carbon reduction strategies and advancing global climate goals.
  Keywords: Carbon emissions trading policy; Carbon neutrality; Low carbon development; Energy Green Transition; Super-efficiency model with undesired outputs; DID model.
  DOI: 10.1504/IJETP.2025.10074895
   
  
• High efficiency output stability of DC-DC boost converter based on adaptive sliding mode control method  
  by Guimin Li, Zhen Jing, Qing Wang, Zhiru Chen 
  Abstract: To control the stable output of the direct current to direct current more effectively, the study is based on the improved adaptive sliding mode control method to explore the efficiency output of the boost converter. The results revealed that the adaptive sliding mode controller saved 26.21% of time compared to the conventional inductor control. The rotor position error of the adaptive inductor with improved phase-locked loop reduced by 28.16% compared to the conventional inductor control at a given speed of 300 r/min and 200 r/min, respectively. Moreover, the rotor position error of the adaptive inductor with improved phase-locked loop was further reduced compared with that of the traditional phase-locked loop. The performance stability of the improved adaptive sliding mode controller is well illustrated.
  Keywords: adaptive sliding mode controller; SMC; direct current to direct current; DC-DC; boost converter; speed loop; quadrature phase-locked loop.
  DOI: 10.1504/IJETP.2026.10075324
   
  

Special Issue on: Advancing Sustainable Development Banking Strategies Energy Transition and Green Economies

• Empowering communities: a case study of sustainable solutions to address load shedding in South Africa  
  by Chané De Bruyn  
  Abstract: South Africans have been plagued by varying stages of load shedding, with 2023 seeing a record-breaking 332 days of load shedding. This prolonged crisis has had severe repercussions, impacting local economic development, water services, food security, education and healthcare. As it affects businesses across all sectors, productivity, employment, and overall growth, addressing this issue is crucial for sustainable development and maintaining a thriving local economy. Using a case study approach, this paper assesses South Africa’s first 'smart town’, that through collaboration and innovative measures have been able to manage their own electricity demand, ensuring the continuation of business and economic activity. This study examines the significance of empowering local communities, discusses important tactics for encouraging community involvement, and provides a compelling case study of sustainable development projects led by empowered communities.
  Keywords: community empowerment; loadshedding; community led development; sustainable development; community; South Africa.
  DOI: 10.1504/IJETP.2025.10071921
   
  
• The impact of AI on China’s energy policy for EVs  
  by Klemens Katterbauer, Sema Yilmaz, Hassan Syed, Gözde Meral 
  Abstract: China’s national energy policy is fundamentally oriented toward achieving a low-carbon economy, with electric vehicles (EVs) serving as a key pillar in this transition. AI plays a crucial role in enhancing energy efficiency, optimizing grid integration, accelerating the widespread adoption of EVs. This report provides a comprehensive analysis of AI’s contributions to China’s EV-related energy policies, examining its applications, benefits, challenges, future developments. AI technologies are instrumental in facilitating China’s ambition to achieve carbon neutrality by 2060. In the energy distribution, AI significantly enhances grid stability through the implementation of smart charging systems, vehicle-to-grid(V2G) technologies, predictive analytics. However, several challenges must be addressed to realize these advantages. These are data security, the digital divide in rural areas, the high costs, the need for regulatory frameworks that balance innovation with compliance. Consequently, AI represents a transformative tool in advancing China’s EV adoption and aligning its energy policies with long-term sustainability objectives.
  Keywords: artificial intelligence; energy policy; electric vehicles; China; carbon neutrality.
  DOI: 10.1504/IJETP.2025.10072079
   
  
• NEOM Smart City the urban oasis in Saudi desert (green energy technologies, policies and strategies)  
  by Somayya Madakam, Shidhar M. Samant, Pragya Bhawsar 
  Abstract: Today, the cities are facing an energy crisis as day-to-day urban operations including home automation, manufacturing, transportation, water, entertainment and others depend on fossil fuel energy. These urban challenges are not just faced by a particular city, nation but also across the globe including Saudi Arabia. In light of all the above challenges, the present manuscript highlights how the new urban energy solutions can meet the present needs and can also help in sustainable urban development. The paper is based on the secondary data collected through reports, white papers, blogs, snaps, and videos on ‘NEOM’. The insights from the content analysis explores NEOM Smart City’s commitment to sustainable energy technologies that reflects its ambition to set new standards in urban sustainability and environmental stewardship. By harnessing renewable energy sources, implementing smart grid technologies, promoting energy efficiency, and fostering innovation, NEOM aims to create a model city that balances environmental preservation.
  Keywords: circular economy; green building; green energy technologies; green hydrogen economy; NEOM Smart City; quality of life; QoL; smart cities; smart grids; sustainable development.
  DOI: 10.1504/IJETP.2026.10075557