Speaker
Description
Electromechanical systems occupy a central place among the energy-intensive technical objects of industry and consume about 75% of the generated electricity. Analysis of the technological conditions of emergencies during the operation of electrical equipment of enterprises showed that the operation of electric motors is associated with a large percentage of energy use. And even a small improvement in the efficiency of electric motors can significantly reduce energy consumption. Based on experiments and simulations, it has been proven that the development of defects leads to additional energy losses and a decrease in the level of energy efficiency for the entire production.
The cost-effective potential for improved energy efficiency in electromechanical systems is approximately 20-30%, which will reduce overall electricity demand by 10%. The study revealed that electromechanical systems can become a deterrent to innovative development and the transition to a digital economy. The high level of penetration of digital technologies in power supply and electromechanics makes it possible to extend the life cycle and allocate time and funds for the repair and renewal of the equipment fleet. Therefore, the transition to control based on predicting the residual resource based on data is relevant for electromechanical systems. Diagnostic and monitoring systems generate a large amount of data that must be accumulated for subsequent analysis and extraction of useful information. Big data helps unlock the potential for energy efficiency management throughout the entire lifecycle.
The integration of means for predicting and assessing the energy efficiency of the operation of electromechanical complexes is proposed on the basis of Internet of Things technologies. The study of the possibilities of interaction of distributed objects through services in order to form a redundant data field with a limited information flow is carried out. A methodology and substantiation of the structure and parameters of a distributed control system for the life cycle of electromechanical equipment based on the "digital twin" technology and information and control interaction with control and energy saving systems in smart electrical grids is proposed.
The paper provides a list of functions that the digital twin should provide access to, and formulates system requirements, on the basis of which, as well as on the basis of the previously presented approaches, a conceptual model of the digital twin of the energy efficiency management process is formed. This model consists of a physical product, a virtual product and associated data, which represent the boundary between the media between physical and virtual spaces and ensure their convergence within the product.
| Affiliation of speaker | Saint-Petersburg Mining University |
|---|---|
| Position of speaker | PhD student |
| Publication | Impact Factor journals |
