BIO Web Conf.
Volume 17, 2020International Scientific-Practical Conference “Agriculture and Food Security: Technology, Innovation, Markets, Human Resources” (FIES 2019)
|Number of page(s)||5|
|Published online||28 February 2020|
Concept of “smart” oil storage facility for agricultural purposes
All-Russian Scientific Research Institute for the Use of Machinery and Oil Products in Agriculture, 392022 Tambov, Russia
2 Lipetsk State Technical University, 398055 Lipetsk, Russia
3 Bauman Moscow State Technical University, 105005 Moscow, Russia
* Corresponding author: email@example.com
Technological parameters and technical level of the equipment at an oil storage facility influence motor fuel’s quality and its waste during reception, storage and transfer. The use of intelligent systems during the oil storage and handling process enhances quality preservation and reduction of motor fuel waste caused by evaporation, oxidation and hydration while stored in above-ground horizontal steel tanks. Systems managing “smart” oil-storage facilities combine technologies for on-line collection, transmission and storage of information with instant data processing and analysis, and managerial decision-making techniques. A methodological framework, that includes algorithms and a program with sensors to monitor indicators of an automated horizontal oil reservoir, has been developed to control the technological parameters (temperature, pressure, fuel level) of the tanks during storage of light oil products, and to protect fuel against flooding and evaporation. The application of the neural network forecasting technique for fuel waste from evaporation during storage, and processing of the data array, made it possible to calculate with a 98% accuracy rate the gasoline waste during storage in horizontal on-ground tanks with up to 100 m3 in volume capacity. The application of a neural network enables development of new fuel storage algorithms and calculation of the optimal storage amount to minimise losses. The concept and developed digital intelligent control solutions for oil storage allows combining data in oil management into a single information space, and to control the automated oil storage system with application of neural networks, deep learning and Big Data.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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