Volume 1 Issue 2 (2025)

This study comprehensively evaluates the wind energy potential of the Mediterranean Region of Turkey and highlights the strategic importance of the area within the context of the country’s renewable energy goals. As global energy demands continue to rise and the transition to sustainable energy sources becomes more urgent, identifying and utilizing regional renewable resources is critical. In this regard, the Mediterranean Region stands out with its favorable geographical and climatic characteristics for wind energy generation. Using data from the Global Wind Atlas, the study examines the region’s wind speeds and directions across various locations. The analysis reveals that the annual average wind speeds generally range between 5.5 m/s and 7 m/s. These wind speeds are considered technically sufficient for wind energy production, especially along the coastline and in high‑altitude mountainous zones where the wind conditions are more stable and intense. The findings suggest that targeted wind energy projects could significantly contribute to both local economic development and national energy sustainability efforts. In addition to emphasizing the technical viability of the region, the study recommends increasing infrastructure investments, deploying advanced and regionally appropriate turbine technologies, and fostering collaboration with local communities to enhance project acceptance and effectiveness. Overall, the research supports the development of informed policies and investment strategies aimed at maximizing the region’s wind energy potential. It provides a valuable framework for stakeholders interested in leveraging renewable resources to support Turkey’s long‑term energy transition goals.

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Since Wind and Solar renewable energy costs dropped below Natural Gas (NG) prices in 2017, there has been an increasing problem setting the price for electrical energy, which this century has been based on NG because cheaper coal has declined in usage to cut carbon emissions. The background is that renewable Wind and Solar are now more economic than NG, and are increasing rapidly in application, yet calculations of energy prices are still regularly based on NG cost. For example, electricity prices today relate more to NG than to renewables although more than 50% of UK electricity now comes from Wind and other renewables in 2025. The key problem is that Wind and Solar outputs fluctuate considerably and cannot be compared directly with electricity from an NG power station which delivers continuously. Consequently, energy storage mechanisms must be added to renewable power if fair comparisons are to be made. Lithium battery and Hydrogen gas storage are plausible options. This paper compares Wind/Solar plus Lithium battery electric storage with Wind/Solar and Hydrogen gas energy stores as replacements for NG to create a new benchmark. The conclusion is that this new benchmark should be deϐined before 2030 when most of UK grid electricity is planned to be green.

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This work presents the development of a hydrogen‑based green energy system for powering fuel cell electric vehicles (FCEVs), with a specific focus on sustainable urban transportation. Current battery‑electric vehicles still face persistent challenges, primarily related to high manufacturing cost, limited driving autonomy, and the need for extensive charging infrastructure. To overcome these limitations, a novel prototype was designed and implemented, integrating an autonomous hydrogen production unit directly within the vehicle. The system is supported by photovoltaic sources for renewable energy input and Lithium‑ion batteries for efficient storage and operational stability. The hydrogen produced on board is utilized by a reversible Proton Exchange Membrane Fuel Cell (PEMFC), which converts the chemical energy into electricity to drive the vehicle’s engine and supply auxiliary systems. This integrated approach ensures continuous energy availability while minimizing dependence on external charging stations. The proposed concept demonstrates several advantages, including extended driving range, reduced refueling time, increased system autonomy, and zero carbon dioxide emissions. Moreover, the design contributes to urban air quality improvement and aligns with Circular Economy (CE) protocols by promoting renewable integration and resource efficiency. Overall, the study highlights hydrogen‑based embedded systems as a promising pathway towards clean, sustainable, and resilient mobility solutions.

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Riverbank filtration is used for producing a large amount of groundwater for a long time. The surface water infiltration is accompanied with riverbank filtration and may significantly affect the quality and temperature of pumping water if the pumping well is located nearby the river. A coupled groundwater flow and heat transport model was developed to estimate the influence of surface water on the temperature in pumping well for groundwater heat pump system at the riverbank. The model included the aquifers under river and considered the variation of surface water temperature with season and depth to simulate accurately pumping water temperature. To depict in detail the aquifers and riverbed sediment in contact with the river, the 3D geological model was developed by Geomodeller, and the numerical model was completed by FEFLOW. For model calibration, the simulation results were compared to the measured groundwater level and temperature data in pumping well during 2 years. The result showed high accuracy with the coefficient of determination (R²) of 0.971, root mean square error (RMSE) of 0.211 ℃. Using calibrated model, the groundwater temperature changes in pumping well were predicted for 15 years. The proposed modeling method can be used to estimate the groundwater flow, quality, and temperature change by the surface water infiltration in riverine aquifer.

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Our research focuses on IoT-integrated hydrogen fuel cells for clean energy in Inner Mongolia and Hebei, China. The system features a 100 kW PEMFC array (65–80 ℃, 98% pure H₂, 850 mbar) paired with an optimized AWS IoT Cloud using MQTT/LoRaWAN for 1 Hz data communication. AI-driven EMS optimizes operations (35–85% load, 30–80% battery charge), while predictive maintenance via Random Forests achieves 96% fault detection, maintaining 5 mΩ membrane resistance and 0.8% voltage deviation. The system consumes 4.1 kg/h of H₂, operates for 720 h (−25 ℃ to 38 ℃, 20–100 kW load), and reduces unscheduled downtime by 68%. Estimated results show 58% efficiency, 28% battery cycle reduction, and 814 t of annual CO₂ savings per unit. Advanced security (AES-256/TLS, blockchain) ensures data integrity, supporting clean energy access and industrial growth in remote regions. The proposed system holds significance in adding sustainable energy, but it is challenged by high initial cost, extreme range of weather adaptability, complications in scalability, and industrial acceptance. These challenges are addressed by feasible solutions, including the cost reduction through mass production, advanced hydrogen infrastructure development, data security with cybersecurity enhancements (AES-256/TLS, blockchain), and thermal management. The research paper aims to add a feasible and sustainable technology helping in achieving energy goals set for China’s futuristic industrial growth, and ensuring sustainable energy access in Inner Mongolia and the Hebei region.

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