International Journal of Energy Technology and Policy (7 papers in press)

Regular Issues

• Sustainable fuels for thermal power generation for sustainable energy supply in a low-density population cluster  
  by Izuchukwu Francis Okafor, Nwachukwu Paul Nwachukwu, Ifeanyi Wilfred Okonkwo, Ikenna David Okeke 
  Abstract: Fossil fuels for thermal power generation have been the dominant fuels for energy generation, which are unsustainable and harmful to the environment. This study examined thermal power generation with biomass briquette fuel and solar thermal energy for sustainable power supply in a low-density population cluster. The power supply situation in Nigeria was highlighted. Regenerative Rankine thermal plant with biomass fuel and concentrated solar thermal power (CSTP) plant was examined for improvement in thermal efficiency. Engineering equation solver was used in solving the mathematical formulations generated in this study. It was found that the thermal efficiency of the plant increased with temperature. Potentially, the plant can operate at peak thermal efficiency if the operating parameters are optimized, and can switch to either biomass fuel to handle solar intermittency issues or to solar thermal to conserve biomass fuel, indicating the novelty of hybrid fuel sources for sustainable thermal power generation.
  Keywords: solar thermal power; regenerative Rankine; power plant; thermal efficiency; power generation.
  DOI: 10.1504/IJETP.2025.10069114
   
  
• Supply chain governance for sustainable solar energy system: impact of artificial intelligence  
  by Monica Bhatia, Pradyumn Chaturvedi, Vikas Khare 
  Abstract: This paper delves into various facets of supply chain management for solar energy systems, with a particular focus on the profound impact of AI. Paper explore the current state of solar energy supply chain management, emphasizing the need for improved efficiency, environmental sustainability, and reliability. The creation of a semantic network for supply chain management of solar energy systems highlight the significance of structured knowledge representation, fostering intelligent decision- making and real-time responsiveness to dynamic operational challenges. Paper examine into the push-pull view of the solar energy supply chain, where AI plays a pivotal role in orchestrating demand-driven and efficient operations. Additionally, this paper includes a comprehensive SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of supply chain management in the solar energy sector. The SWOT analysis identifies critical areas for improvement and underscores the transformative potential of AI.
  Keywords: logistic management; inventory management; SWOT analysis; supplier selection; artificial intelligence.
  DOI: 10.1504/IJETP.2025.10070456
   
  
• Solar PV panel efficiency enhancement through particle swarm optimisation assisted adaptive reconfigurable connection system  
  by Amarendra Kumar  
  Abstract: This paper presents a novel scheme for efficiency enhancement of solar PV arrays through optimisation assisted adaptive connection scheme. Leveraging the power of particle swarm optimisation (PSO), the proposed scheme focuses on dynamically adapting electrical connections of solar panels to maximise efficiency. The potential connection configuration scheme allows real-time adjustments based on environmental factors such as shading, temperature variations, and panel mismatches. The comparative study presented in this paper demonstrates the efficacy of the ARCS-PSO approach in achieving remarkable efficiency improvements compared to static or fixed connection configurations. The simulation results show that the ARCS-PSO scheme consistently outperformed fixed connection configurations under varying conditions. Under uniform irradiance, the proposed method results in higher energy yield. In challenging cases like partial shading and temperature variations, ARCS-PSO demonstrated increased power output. These findings validate the potential of ARCS-PSO in optimising solar energy systems under diverse operating conditions.
  Keywords: adaptive reconfigurable connection system; ARCS; particle swarm optimisation; PSO; solar panel arrays; energy efficiency; dynamic connectivity.
  DOI: 10.1504/IJETP.2025.10072551
   
  
• Optimal operation and profit maximisation of a wind-integrated energy hub under risk-taking strategy: a case study on renewable energy integration and storage capacity analysis  
  by Hailiang Rong, Jia Wang 
  Abstract: This study investigates the optimal operation of a wind-integrated local energy hub aimed at maximising profit while coordinating with electrical, thermal, and natural gas networks. The system comprises combined heat and power (CHP) units, heat pumps, and both electrical and thermal energy storage, with wind energy as the sole renewable source. To address wind speed uncertainty, information gap decision theory (IGDT) was applied under both risk-averse and risk-taking strategies. A mixed-integer linear programming (MILP) model was developed and solved using GAMS, incorporating detailed constraints related to energy balance, storage, ramping, and market exchanges. Sensitivity analysis across twenty scenarios revealed that risk-taking strategies yielded higher profits but required more operational adjustments. Notably, particularly electrical, significantly enhanced economic outcomes. Demand response programs such as time-of-use (TOU) and direct load control (DLC) were also integrated to improve operational flexibility. The findings demonstrate that robust, market-responsive strategies enhance both profitability and renewable energy utilisation.
  Keywords: wind energy; profit maximisation; energy storage; info-gap decision theory; risk-taking strategy; demand response; mixed-integer linear programming; MILP; renewable energy integration.
  DOI: 10.1504/IJETP.2025.10074011
   
  
• Energy-saving design and new energy utilisation evaluation of building engineering, heating, ventilation, and air conditioning based on internet of things technology  
  by Xiaowen Bian, Peimin Zhao, Bingqing Xue, Song Zhou 
  Abstract: As building sizes expand and demands for indoor comfort continue to rise, traditional heating, ventilation, and air conditioning (HVAC) systems face challenges such as energy waste, inefficiency, and a lack of intelligent control, making them unable to meet the energy-saving, environmentally friendly, and efficient operation requirements of modern buildings. This paper leverages internet of things (IoT) technology to connect heating stations, employees, and a central control system to form an integrated heating and energy-saving system. Furthermore, a ten-fold cross-validation method is introduced to optimise parameters, which are selected based on the characteristics of the optimal input. The experimental results showed that the model root mean squared error (RMSE) corresponding to the results of the energy prediction model decreased from 8.9338 to 4.2271, while the residual standard error (RSE) decreased from 0.3202 to 0.1105. It could be seen that the predictive ability of the model was significantly improved.
  Keywords: construction engineering; heating; ventilation; and air conditioning; numerical simulation; internet of things; IoT; support vector regression algorithm; SVR; cross-validation method.
  DOI: 10.1504/IJETP.2025.10074093
   
  

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