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All Journal JOIV : International Journal on Informatics Visualization International Journal of Renewable Energy Development
Chung, Nghia
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Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering

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Artificial intelligence applications in solar energy Le, Thanh Tuan; Le, Thi Thai; Le, Huu Cuong; Dong, Van Huong; Paramasivam, Prabhu; Chung, Nghia
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2686

Abstract

Renewable energy research has become significant in the modern period owing to escalating prices of fossil fuels and the pressing need to reduce greenhouse gas emissions. Solar energy stands out among these sources due to its abundance and global accessibility. However, its weather-dependent and cyclical nature add inherent risks, making effective planning and management difficult. Soft computing technologies provide attractive solutions for modeling such systems, while machine learning and optimization techniques are gaining popularity in the solar energy industry. The current literature highlights the growing use of soft computing technologies, emphasizing their potential to address difficult challenges in solar energy systems. To effectively reap the benefits, these strategies must be seamlessly connected with emerging technologies like the Internet of Things (IoT), big data analytics, and cloud computing. This integration provides a unique opportunity to improve the scalability, flexibility, and efficiency of solar energy systems. Researchers can use these synergies to create intelligent, linked solar energy ecosystems capable of real-time optimization of energy production, delivery, and consumption. These technologies have the potential to transform the renewable energy environment, allowing for more resilient and sustainable energy infrastructures. Furthermore, as these technologies improve, there is a growing demand for trained experts to address associated cybersecurity problems, assuring the integrity and security of these sophisticated systems. Researchers may pave the road for a more sustainable and energy-efficient future by working collaboratively and using interdisciplinary methodologies.
Integrated multi-objective optimization of fuel injection and engine strategy in oxyhydrogen/producer gas-powered dual-fuel diesel engine Nguyen, Du; Nguyen, Lan Huong; Nguyen, Duy Tan; Chung, Nghia; Truong, Thanh Hai
International Journal of Renewable Energy Development Vol 15, No 1 (2026): January 2026
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2026.62062

Abstract

Biomass gasification has taken on a new significance as a decentralized and sustainable route of turning solid biomass into oxyhydrogen (HHO) enriched producer gas that can be employed in internal combustion engines using diesel as the pilot fuel. This dual fuel system can cut down on reliance on fossil diesel as well as improve the energy security of rural and semi-urban applications. This study examines the engine operation and emissions characteristics of the producer-gas-diesel dual-fuel engine under the main operating parameters and uses statistical optimization to reduce the emissions and still attain acceptable efficiency. Indeed, Prosopis juliflora wood gasification was conducted in a small, fixed-bed downdraft gasifier, which is only intended to be used in decentralized and experimental engines. Downdraft design was chosen because of the intrinsic effect that it provides low-tar PG, which must be supplied to internal combustion engines. The optimization findings reveal that the maximum brake mean effective pressure (BMEP) is 4.23 bar, pilot fuel injection pressure (PFIP) is 240 bar, and HHO flow rate (HHOFR) is 2.08 LPM. The predicted values of Brake Thermal Efficiency (BTE), Brake Specific Energy Consumption (BSEC), and carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) emissions at these settings are estimated to be 20.71 %, 4.17 MJ/kWh, and 77.95, 79.47, and 335.99 ppm, respectively. The findings indicate that the balance between the supply of producer gas and the optimization of injection parameters can greatly enhance the sustainability and emission characteristics of the dual-fuel engine running on gaseous fuel that is produced from biomass.
Co-Authors Dong, Van Huong Le, Huu Cuong Le, Thanh Tuan Le, Thi Thai Nguyen, Du Nguyen, Duy Tan Nguyen, Lan Huong Paramasivam, Prabhu Truong, Thanh Hai