СЕТЕВОЕ МОДЕЛИРОВАНИЕ ПРОЦЕССА АНАЭРОБНОГО СБРАЖИВАНИЯ НАВОЗА

Abstract

The article discusses the technological complex of anaerobic digestion of manure (ASN). Thanks to biogas plants, it is possible to mitigate the harmful effects on reservoirs and their inhabitants, reduces pollution with ammonium salts and restores the natural oxygen saturation of waters. The effectiveness of the functioning of such systems can be ensured with the help of modern methods of information processing, using methods of system analysis of complex objects based on a mathematical description of the technological process. Based on the review of the main methods of modeling discrete-continuous chemical-technological systems (CTS), the expediency of using the apparatus of the theory of Petri nets (SP) for process modeling (ASN) is substantiated. To describe the system, we propose the use of N–schemes based on the mathematical apparatus of Petri nets, one of the advantages of which is the possibility of presenting the network model both in analytical form, with the possibility of automating the analysis process, and in graphical form to ensure the visibility of the model being developed. When analyzing chemical-technological schemes, the main limitation of the N–scheme formalism should be taken into account, which is that they do not take into account the time characteristics of the simulated systems, since the transition response time is considered to be zero. Taking into account these conditions, we have proposed modified Petri nets focused on modeling and analysis of discrete-continuous CTS by including priority transitions, delay time of labels in positions and transitions. A model in the form of a modified Petri net (SME) is constructed. By means of the TRACE MODE SCADA technology, a software package of the process control system (ASN) has been developed. The process control system allows you to perform dispatching control of the main elements of the control system, stop the system (ASN) and analyze its condition, both as a whole and in order to predict the development of emergency situations.