IMITATION MODELING OF ENERGY RESOURCES MANAGEMENT PROCESSES OF METALLURGICAL ENTERPRISES

Authors

  • S. Kiyko
  • E. Druzhinin
  • O. Prokhorov

DOI:

https://doi.org/10.26906/SUNZ.2019.6.020

Keywords:

portfolio of energy saving projects, project feasibility, risk, resource allocation, agent model, metallurgical enterprise

Abstract

As a result of the analysis of the energy saving program structure at the metallurgical enterprises,it was found the problems that are solved by the energy saving projects are inefficient consumption (significant losses) of energy resources (gas, thermal energy, electricity), control over the costs formation and the results of improvements in energy consumption. The overall goal of improving energy efficiency at the enterprise is realized through the management of a energy-saving projects portfolio, which are aimed at fulfilling the following tasks: optimization of energy balance; minimization of natural gas consumption; optimization of energy efficiency, etc. Success criteria for an energy-saving project include: efficiency; operating costs, losses, etc. It should be noted that it is difficult to objectively estimate the share of each energy resource in the total flow, to determine the energy intensity of individual production, departments and the whole enterprise, etc. To implement optimal management of energy flows at a metallurgical enterprise we proposed the method based on a multi-agent approach, which consists in forming a community of agents for energy consumption, energy conversion, energy production and the purchase of energy resources on the external market. An agent-based simulation model has been developed for analyzing the energy management processes of a metallurgical enterprise when implementing a portfolio of energy-saving projects. The article described the features of the information interaction of agents in a multi-agent system, due to mechanisms associated with decentralized multi-project planning, including the resolution of resource conflicts when performing tasks, the search for the most optimal resources, during which the work will be performed on the most favorable conditions

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Published

2019-12-28