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Добірка наукової літератури з теми "ELECTRICITY DENSITY"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "ELECTRICITY DENSITY"

1

Buceti, Giuliano. "Sustainable power density in electricity generation." Management of Environmental Quality: An International Journal 25, no. 1 (2014): 5–18. http://dx.doi.org/10.1108/meq-05-2013-0047.

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Purpose – When comparing renewables with fossil fuels, emotional approaches are fuelled by the difficulties in defining a proper metric able to make consistent comparisons among energy sources. In literature several approaches have been proposed, all effective in some way but ineffective in others. Variables like energy density, prices, estimated resources, life time emissions, water use and waste, all come at the same time to form an unmanageable mix. This paper discuss the adoption of a shared metric to clarify the boundary conditions that limit the solutions can be operated and to define wh

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2

Zheng, Hua, Li Xie, and Jun Xiong. "Application of Intelligent Algorithm for Probability Density Estimation." Advanced Materials Research 186 (January 2011): 388–92. http://dx.doi.org/10.4028/www.scientific.net/amr.186.388.

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There is no doubt that probability distribution is primary and important for the risk analyses on financial time series. And various non-Gaussian distributions have become one of focused and unsolved problems, especially for those studies on the real continuous variables. So this paper concentrates on the intelligent algorithm for probability density estimation by Least Squares Support Vector Machines (LS-SVM), and its application on the electricity price. Moreover a practical probability density modeling of electricity price is implemented by LS-SVM. Finally, case studies on the electricity p

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3

Saunders, C. P. R., and C. C. Zhang. "Rime density, radial forces and atmospheric electricity." Atmospheric Research 21, no. 2 (1987): 101–11. http://dx.doi.org/10.1016/0169-8095(87)90001-9.

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4

Hyndman, Rob J., and Shu Fan. "Density Forecasting for Long-Term Peak Electricity Demand." IEEE Transactions on Power Systems 25, no. 2 (2010): 1142–53. http://dx.doi.org/10.1109/tpwrs.2009.2036017.

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5

Boukarta, Soufiane, and Ewa Berezowska. "Exploring the Energy Implication of Urban Density in Residential Buildings." Journal of Applied Engineering Sciences 7, no. 1 (2017): 7–14. http://dx.doi.org/10.1515/jaes-2017-0001.

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AbstractIn the context of the Algerian energy policy, and through the review of the Algiers’ residential building stock, this paper explores the correlation between the energy consumption of gas and electricity with urban density. Based on a holistic approach of the 57 Algiers’ municipalities, the analysis is organized in two ways. Firstly, the spatial approach is conducted within a GIS implementation, carried out based on the 2013 aggregated annual energy consumption data. The cross analysis of Electricity and Gas consumption and density of population within a GIS spatial distribution approac

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6

Munkhammar, Joakim, Jesper Rydén, and Joakim Widén. "Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data." Applied Energy 135 (December 2014): 382–90. http://dx.doi.org/10.1016/j.apenergy.2014.08.093.

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7

Amara, Fatima, Kodjo Agbossou, Yves Dubé, Sousso Kelouwani, Alben Cardenas, and Jonathan Bouchard. "Household electricity demand forecasting using adaptive conditional density estimation." Energy and Buildings 156 (December 2017): 271–80. http://dx.doi.org/10.1016/j.enbuild.2017.09.082.

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8

Gao, Chong Yang, Ai Jie Wang, and Yang Guo Zhao. "Contribution of Sulfate-Reducing Bacteria to the Electricity Generation in Microbial Fuel Cells." Advanced Materials Research 1008-1009 (August 2014): 285–89. http://dx.doi.org/10.4028/www.scientific.net/amr.1008-1009.285.

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Double-chambered microbial fuel cells (MFCs) were used to investigate the effect of sulfate and sulfate-reducing bacteria (SRB) on electricity generation by molybdate inhibition coupled with PCR-DGGE technique. Results showed that low influent sulfate (< 1470 mg/L) improved power density and voltage, while higher sulfate blocked the MFC efficiency. Molybdate inhibited the activity of SRB and consequently decreased MFC voltage and power density which confirmed some SRB were involved in the electricity generation. Microbial community analysis indicated thatDesulfovibrio desulfuricanscontribut

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9

Liu, Huixin, Xiaodong Shen, Xisheng Tang, and Junyong Liu. "Day-Ahead Electricity Price Probabilistic Forecasting Based on SHAP Feature Selection and LSTNet Quantile Regression." Energies 16, no. 13 (2023): 5152. http://dx.doi.org/10.3390/en16135152.

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Electricity prices are a central element of the electricity market, and accurate electricity price forecasting is critical for market participants. However, in the context of increasingly integrated economic markets, the complexity of the electricity system has increased. As a result, the number of factors required to consider in electricity price forecasting is growing. In addition, the high percentage of renewable energy penetration has increased the volatility of electricity generation, making it more challenging to predict prices accurately. In this paper, we propose a probabilistic foreca

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10

Cheng, Chiu Yu, Cheng Che Li, and Ying Chien Chung. "Continuous Electricity Generation and Pollutant Removal from Swine Wastewater Using a Single-Chambered Air-Cathode Microbial Fuel Cell." Advanced Materials Research 953-954 (June 2014): 158–62. http://dx.doi.org/10.4028/www.scientific.net/amr.953-954.158.

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Microbial fuel cell (MFC) represents a new method for simultaneously swine wastewater treatment and electricity generation. However, few studies revealed the high electricity generation and pollutant removal using a large-scale single-chambered MFC in treating swine wastewater. Results indicated optimal hydraulic retention time (HRT) of swine wastewater was 8 d considering the removal efficiency and the power density. Under this condition, this MFC system removed 85.62% TCOD and 73.6% NH3 as well as achieved power density of 368 mW/m2. Results also showed the maximum power density of the MFC w

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