A comparative investigation on the effect of different nanofluids on the thermal performance of two-phase closed thermosyphon

Xu, Qian; Liu, Lin; Feng, Jianmin; Qiao, Lihong; Yu, Chuqiao; Shi, Wei; Ding, Chong; Zang, Yong; Chang, Chun; Xiong, Yaxuan; Ding, Yulong

doi:10.1016/j.ijheatmasstransfer.2019.119189

Cited by 106 publications

(29 citation statements)

References 43 publications

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“…The calibration report for the anemometers used in the present work showed a maximum uncertainty of 0.6% for a wind speed range of 4–7 m/s, which reduced at higher wind speeds. The overall uncertainty in the estimation of wind speed is obtained by taking all the above uncertainties into account (Jain, 2016; Xu et al., 2020a) and using the relation in equation (1) where ε i is each component of uncertainty and N is the number of components of uncertainty. The uncertainties were estimated at 95% confidence level.…”

Section: Methodsmentioning

confidence: 99%

Assessment of wind energy potential for Tuvalu with accurate estimation of Weibull parameters

Talama

Kutty

Kumar

et al. 2020

Energy Exploration & Exploitation

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Wind resource assessments are carried out for two sites in Tuvalu: Funafuti and Nukufetau. The wind speeds at 34 and 20 m above ground level were recorded for approximately 12 months and analyzed. The averages of each site are computed as the overall, daily, monthly, annual, and seasonal averages. The overall average wind speeds for Funafuti and Nukufetau at 34 m above ground level were estimated to be 6.19 and 5.36 m/s, respectively. The turbulence intensities at the two sites were also analyzed. The turbulence intensity is also computed for windy and low-wind days. Wind shear analysis was carried out and correlated with temperature variation. Ten different methods: median and quartiles method, the empirical method of Lysen, the empirical method of Justus, the moments method, the least squares method, the maximum likelihood method, the modified maximum likelihood method, the energy pattern factor method, method of multi-objective moments, and the wind atlas analysis and application program method were used to find the Weibull parameters. From these methods, the best method is used to determine the wind power density for the site. The wind power density for Funafuti is 228.18 W/m2 and for Nukufetau is 145.1 W/m2. The site maps were digitized and with the WAsP software, five potential locations were selected for each site from the wind resource map. The annual energy production for the sites was computed using wind atlas analysis and application program to be 2921.34 and 1848.49 MWh. The payback periods of installing the turbines for each site are calculated by performing an economic analysis, which showed payback periods of between 3.13 and 4.21 years for Funafuti and between 4.83 to 6.72 years for Nukufetau.

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Section: Methodsmentioning

confidence: 99%

Assessment of wind energy potential for Tuvalu with accurate estimation of Weibull parameters

Talama

Kutty

Kumar

et al. 2020

Energy Exploration & Exploitation

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“…Xu et al (2020a) showed that if coke oven gas is used as the fuel, the NOx concentration reduced by almost 35%. Xu et al (2020b) analyzed five types of nanofluids to obtain single and hybrid nanofluids with the best heat transfer performance. Their results showed that with the usage of hybrid nanofluid 25% Al 2 O 3 þ 75% TiO 2 H 2 O and the single nanofluid TiO 2 H 2 O, best heat transfer performance was obtained.…”

Section: Hps Control Systems and Optimization Techniquesmentioning

confidence: 99%

“…(2020a) showed that if coke oven gas is used as the fuel, the NOx concentration reduced by almost 35%. Xu et al. (2020b) analyzed five types of nanofluids to obtain single and hybrid nanofluids with the best heat transfer performance.…”

Section: A Statistical Overview Of the Existing Hps Around The Globementioning

confidence: 99%

Hybrid power systems – Sizes, efficiencies, and economics

Rehman

2020

Energy Exploration & Exploitation

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In the context of electricity generation in the oil and gas producing countries, it has become implicit to develop new, clean, and renewable sources of energy to supplement the fossil fuel based power generation. With this single aim, one can hit two targets, conservation of fixed fossil fuel resources and combat the adverse climatic changes to safeguard our planet. In regional context, solar photovoltaic, solar thermal, wind power, geothermal, and hydro power are alternative sources for power mitigation. Of these renewables, wind, solar photovoltaic (PV), diesel, and energy storage in hybrid combinations are the possible ways to supply continuous energy for all sizes of applications. This paper provides a review of the existing hybrid power systems and the theoretical studies around the globe in varied climatological conditions to identify the best combinations of hybrid systems for Saudi Arabia to supplement the existing energy portfolio. The wind/solar-pv, wind/solar-pv/diesel, and solar-pv/diesel with and without battery backup are most commonly used systems with respective popularity of 28, 22, and 21%. Among users, remote communities are the highest while islands and communication towers are the next common applications. Average costs of energy of wind/solar-pv, wind/solar-pv/diesel, and solar-pv/diesel are around 0.458, 0.355, and 0.349 US$/kWh.

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“…Meanwhile, the release of energy reserves would not only suppress the energy price which is not conducive to the survival of energy enterprises, but also result in a large outflow of national foreign exchange impacting on the national economy. If the predictive value of energy supply was excessive, it would lead to insufficient energy import and massive energy will be allocated and stored, endangering the national energy security and social stability [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Reliable Prediction on Emerging Energy Supply for National Sustainability and Stability: A Case Study on Coal Bed Gas Supply in China Based on the Dual-LSTM Model

Kang

Lao

et al. 2021

IEEE Access

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Aiming to prevent from the imbalance between supply and demand of energy in which the share of emerging type is rapidly increasing, to predict the supply of emerging energy reliably is significant. However, the expected distribution uncertain and high-noise characteristics of emerging energy supply impede the reliable prediction. The Dual-LSTM (Long Short-Term Memory) model was constructed for the characteristic extracting and effective prediction of the expected distribution uncertain high-noise emerging energy supply time series. A case study on coal bed gas supply in China was conducted. Results showed that the Dual-LSTM model effectively solved the the problem of superfluous and non-quantifiable variables in the prediction of coal bed gas supply and extracted the statistical characteristics of expected distribution uncertain and high-noise data samples effectively with a relative error major less than 5% in short-term. Besides, the Dual-LSTM model has a significantly higher prediction accuracy while comparing with ARIMA model and original LSTM model. Ultimately, it is predicted that the year-on-year growth rates of coal bed gas supply of China from January to September, 2021, approximately maintains 75% in average based on the Dual-LSTM model. The Dual-LSTM model provides a reliable statistical model for policy decision to maintain national sustainability and stability. INDEX TERMSImproved deep learning model; Uncertain expected distribution high-noise sample; Emerging energy; Supply-demand stability; Reliable prediction; Time series analysis

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A comparative investigation on the effect of different nanofluids on the thermal performance of two-phase closed thermosyphon

Cited by 106 publications

References 43 publications

Assessment of wind energy potential for Tuvalu with accurate estimation of Weibull parameters

Assessment of wind energy potential for Tuvalu with accurate estimation of Weibull parameters

Hybrid power systems – Sizes, efficiencies, and economics

Reliable Prediction on Emerging Energy Supply for National Sustainability and Stability: A Case Study on Coal Bed Gas Supply in China Based on the Dual-LSTM Model

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