Assessment of the potential effect of applying demand management technology at mining enterprises
Year: 2024
Type: article
Abstract: Introduction. Currently, the lack of classification of electricity consumers to manage load profiles leads to the impossibility of implementing measures to improve economic and energy efficiency using demand management methods. The study aims to develop a classification of consumers according to their load profiles. Materials and methods. The developed classification of electrical loads is described in terms of the proposed characteristics by graph analytical method. The proposed classification is used in the construction of the simulation model of the electrical complex for the purpose of demand management modelling. Results. The classification of electrical loads obtained in the paper is given in a form ready for conducting experiments in simulation modelling environments. Such environments can be Matlab or AnyLogic. Discussion. In the article, certain restrictions and assumptions that need to be introduced into the model to simplify the calculations were also given. The authors assume that in the future this may become an obstacle in the validation of results. Conclusion. In this article, groups of loads were reviewed and described for use in the demand management process. Further, a modelling approach was selected and justified. The simulation model was based on several aspects described in the paper: the developed classification of loads, the equipment grouped by mining sites, and the electrical part of the model, punctuated by a hybrid electrical system with three independent EE sources. For the model, the assumptions and the main objectives of creation were described in the context of assessing the possibility and potential effect of applying demand management technology in mining enterprises.
Authors: Yury Zhukovsky, Pavel Suslikov
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406090576