| Issue |
E3S Web of Conf.
Volume 524, 2024
VII International Conference on Actual Problems of the Energy Complex and Environmental Protection (APEC-VII-2024)
|
|
|---|---|---|
| Article Number | 01020 | |
| Number of page(s) | 7 | |
| Section | Issues of the Energy Complex | |
| DOI | https://doi.org/10.1051/e3sconf/202452401020 | |
| Published online | 16 May 2024 | |
Multicriteria fuzzy statistical analysis of biogas energy systems dependability
1 Financial University under the Government of the Russian Federation, Moscow, 125167, Russia
2 Belgorod State Agricultural University named after V. Gorin, Mayskiy, 308503, Russia
3 Belgorod State National Research University, Belgorod, 308015, Russia
4 Voronezh State Agricultural University, Voronezh, 394087, Russia
* Corresponding author: vlomazov@yandex.ru
The work is devoted to the problems of assessing the dependability of autonomous energy systems with biogas type of electrical generation. The purpose of the work is to develop an intelligent tool for multi-criteria dependability assessment, taking into account the statistical uncertainty of individual indicators. A three-level hierarchy (according to the degree of generalization) of dependability indicators, represented by statistical (at the lower level) and fuzzy linguistic (starting from the second level) variables, has been developed. It is proposed to implement the transition from statistical values of lower-level indicators to numerical values of second-level indicators using an artificial neural network. Fuzzification of second-level indicators was carried out using L. Zadeh’s z-number apparatus, which allows taking into account statistical uncertainty. To determine the integral dependability indicator (top of the hierarchy) based on second-level indicators, it is proposed to use the Mamdani fuzzy inference algorithm. The constructed procedure for determining the level of dependability allows us to obtain data for making scientifically based decisions when operating biogas energy systems.
© The Authors, published by EDP Sciences, 2024
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.