Coordination of thermal/wind energies in power-to-gas process for cost/pollution abatement considering wind energy recovery

Hemmati, Reza; Nosratabadi, Seyyed Mostafa; Mehrjerdi, Hasan; Bornapour, Mosayeb

doi:10.1080/15567036.2022.2049930

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…By ofsetting conventional power generation, the system helps reduce emissions of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O). In addition, it enhances air quality by replacing diesel-powered fans and reducing pollutants like nitrogen oxides (Nox), particulate matter, and sulfur dioxide [81]. Wind energy recovery aligns with sustainability goals and demonstrates a commitment to cleaner energy and carbon footprint reduction [79].…”

Section: Environmental Sustainability: Emissions Reduction Viamentioning

confidence: 98%

Evaluation of Wind Energy Recovery from an Underground Mine Exhaust Ventilation System

Yeboah,

Ackor,

Abrowah

2023

Journal of Engineering

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Wind energy is a reliable renewable source of energy with significant technological advancements. However, recovering wind energy from waste and predictable sources remains untapped. Certain industrial activities emit pollutants while generating wind energy, presenting opportunities for cleaner energy utilization. This study investigates wind energy recovery from an underground mine’s exhaust through experimental research and analysis. It revealed a drop in wind velocity at −2.5162 Hz frequency as distance increased. This frequency predicted a wind speed of 7.67 m/s at 1 m from the exhaust fan in a real mine. Theoretical calculations show significant wind energy potential of 1031.31 kWh over 13 hours, which is equivalent to 79.3 kW. Realistic estimates suggest 55.51 kW wind power can be recovered, yielding 721.63 kWh. Compared with previous studies in the mining industry, recovery potential varies based on site-specific factors. The study shows a recoverable power percentage of 28% theoretically and up to 19.8% realistically, highlighting wind energy’s potential in underground mining. Moreover, the wind energy significantly contributes to the lighting system, enhancing energy efficiency. To optimize recovery, the ventilator fan system is upgraded, multiple fans are used, and optimizing the design is recommended. The study emphasizes continuous research and real-world implementations for energy savings. Utilizing wind energy effectively improves sustainability and reduces reliance on conventional sources, promoting a greener future for mining.

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Section: Environmental Sustainability: Emissions Reduction Viamentioning

confidence: 98%

Evaluation of Wind Energy Recovery from an Underground Mine Exhaust Ventilation System

Yeboah,

Ackor,

Abrowah

2023

Journal of Engineering

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“…Wind power is a significant renewable energy source, and its growth is helpful in terms of energy supply security and lowering greenhouse gas emissions. , The wind power curve plays an important role in estimating wind energy potential and wind turbine selection. − Wind turbines must disperse a substantial quantity of heat during operation. The produced heat must be effectively distributed; otherwise, the temperature of the mechanical and electrical components would rise, lowering overall energy efficiency.…”

Section: Machine Learning For Rementioning

confidence: 99%

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System

Sharma¹,

Said

Kumar³

et al. 2022

Energy Fuels

222

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Nanofluids have gained significant popularity in the field of sustainable and renewable energy systems. The heat transfer capacity of the working fluid has a huge impact on the efficiency of the renewable energy system. The addition of a small amount of high thermal conductivity solid nanoparticles to a base fluid improves heat transfer. Even though a large amount of research data is available in the literature, some results are contradictory. Many influencing factors, as well as nonlinearity and refutations, make nanofluid research highly challenging and obstruct its potentially valuable uses. On the other hand, data-driven machine learning techniques would be very useful in nanofluid research for forecasting thermophysical features and heat transfer rate, identifying the most influential factors, and assessing the efficiencies of different renewable energy systems. The primary aim of this review study is to look at the features and applications of different machine learning techniques employed in the nanofluid-based renewable energy system, as well as to reveal new developments in machine learning research. A variety of modern machine learning algorithms for nanofluid-based heat transfer studies in renewable and sustainable energy systems are examined, along with their advantages and disadvantages. Artificial neural networks-based model prediction using contemporary commercial software is simple to develop and the most popular. The prognostic capacity may be further improved by combining a marine predator algorithm, genetic algorithm, swarm intelligence optimization, and other intelligent optimization approaches. In addition to the well-known neural networks and fuzzy- and gene-based machine learning techniques, newer ensemble machine learning techniques such as Boosted regression techniques, K-means, K-nearest neighbor (KNN), CatBoost, and XGBoost are gaining popularity due to their improved architectures and adaptabilities to diverse data types. The regularly used neural networks and fuzzy-based algorithms are mostly black-box methods, with the user having little or no understanding of how they function. This is the reason for concern, and ethical artificial intelligence is required.

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Green Energy—A Review of the Definitions and the Main Directions of Development

Bąk

Cheba

2022

Green Energy

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Coordination of thermal/wind energies in power-to-gas process for cost/pollution abatement considering wind energy recovery

Cited by 6 publications

References 29 publications

Evaluation of Wind Energy Recovery from an Underground Mine Exhaust Ventilation System

Evaluation of Wind Energy Recovery from an Underground Mine Exhaust Ventilation System

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System

Green Energy—A Review of the Definitions and the Main Directions of Development

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