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Energies
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Modeling the Efficiency of Biogas Plants by Using an Interval Data Analysis Method

Authors: Mykola Dyvak; Volodymyr Manzhula; Andriy Melnyk; Bohdan Rusyn; Iryna Spivak;

Modeling the Efficiency of Biogas Plants by Using an Interval Data Analysis Method

Abstract

This article considers the task of developing mathematical models and their computer implementation that would establish the dependence of pH (acidity of the environment) on the volume and structure of raw materials for daily loading, as well as on the operating parameters of temperature and humidity based on the interval analysis of experimental data obtained during BGP research of a given type. In the process of research, based on the developed interval models, it was established that this indicator depends on the volume and structure of raw materials, as well as on the temperature and humidity of the substrate in the bioreactor. To build this mathematical model, it is proposed to use the method of interval data analysis and the method of identification of model parameters based on multidimensional optimization. The results of experimental studies for a specific type of biogas plant are given, and interval models with guaranteed prognostic properties that characterize the pH of the environment depending on the specific type of bio-raw material of solid and liquid fractions, temperature, and humidity are obtained. Based on the use of different types of raw materials, the developed models, based on experimental data, describe different configurations of the structure and volumes of raw materials for daily loading. The obtained mathematical models are an algebraic nonlinear equation that can be applied to control the level of pH of the environment in the bioreactor by determining the optimal volumes of raw materials of each type during the loading period depending on the temperature and humidity of the substrate in the bioreactor.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average