RESEARCH OF AUTOMATION AND ARTIFICIAL INTELLIGENCE METHODS FOR OPTIMIZING BIOGAS TRANSPORTATION

In modern conditions of sustainable development and energy efficiency improvement, optimization of biogas transportation processes is becoming particularly relevant. This paper is devoted to the study of automation and artificial intelligence methods used to improve the efficiency of biogas transportation at all stages-from production to the end user. The article discusses modern intelligent control algorithms, including machine learning and neural network models that allow predicting losses, monitoring pressure, and optimizing transportation routes. The article analyzes the possibilities of integrating the Internet of Things (IoT) and digital twins to monitor the system state in real time. A comparative study of traditional and automated transportation management methods is conducted, and their advantages and limitations are revealed. А также This paper also presents a structural diagram of a container for transporting compressed biogas and a logical diagram of an automated control system operating on the basis of a microcontroller. The container includes 16 high-pressure cylinders, piping, pressure sensors, temperature sensors, gas leaks, as well as shut-off valve elements and solenoid valves. This ensures the physical safety of storage and transportation of biogas. The control system shown in the first diagram is implemented using a microcontroller that collects data from sensors, controls actuators (ventilation, valves), displays parameters on the display, and transmits information to remote monitoring devices. This architecture allows you not only to quickly respond to changes in environmental parameters, but also to prevent emergencies through data mining.