Development of mathematical models to support decision-making regarding the functioning of critical infrastructure in the industry of energy supply

Authors

DOI:

https://doi.org/10.15587/2706-5448.2023.293205

Keywords:

critical infrastructure, mathematical models, decision-support system, threats, critical situation

Abstract

The object of research is the energy supply company and the processes of generation and supply of electric energy. The paper examines the problems of building mathematical models for forecasting the operation of a critical infrastructure object in the conditions of a changing security environment, characterized by unpredictability, the presence of uncertainties of various types, the appearance of new threats, their combinations, changes in the form, duration, nature of their influence. In the work, the main attention is paid to the study of the functioning of critical infrastructure in the field of energy supply. Based on the study of the functioning of the energy company system, methods of dealing with uncertainties at the stage of data preparation for analysis and during the preliminary construction of models are presented, in particular, statistical and probabilistic approaches, modeling of the studied processes, alternative methods of estimating model parameters, etc. The complexity of preparing the input data set is related to the fact that it is necessary to ensure the representativeness and variability of the data sets, given that a significant number of factors must be included in the model according to the requirements of regulatory documents, which can lead to multicollinearity of the input variables. The paper proposes an analytical toolkit based on the use of mathematical models and their combinations, intended for use in specialized decision support systems. In the course of the research, a number of numerical experiments were conducted, in which the proposed methodology was worked out on the materials of the enterprise – the object of the critical infrastructure of the energy sector. SAS Energy Forecasting software was used to build the models. The best forecasting results are obtained using generalized linear models (GLM), in particular the GLM model in the form of ARIMAX (a moving average autoregressive model that includes an integrated trend component and external regressors). The proposals presented in the work will allow to increase the efficiency of the functioning of the energy sector, including the determination of the goals, tasks and benchmarks of its operation in regular mode for certain periods of time, as well as in the field of development of universal and special mechanisms for ensuring stability in the mode of response to threats and critical situations.

Author Biographies

Oleksandr Terentiev, Institute of Telecommunications and Global Information Space of National Academy of Sciences of Ukraine

Doctor of Technical Sciences

Department of Application Informatics

Tetyana Prosyankina-Zharova, Institute of Telecommunications and Global Information Space of National Academy of Sciences of Ukraine

PhD

Department of Application Informatics

Valerii Diakon, Institute of Telecommunications and Global Information Space of National Academy of Sciences of Ukraine

PhD

Department of Department of Application Informatics

Roman Manuilenco, Institute of Applied Mathematics and Mechanics of National Academy of Sciences of Ukraine

PhD

Department of Theory of Control Systems

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Development of mathematical models to support decision-making regarding the functioning of critical infrastructure in the industry of energy supply

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Published

2023-12-15

How to Cite

Terentiev, O., Prosyankina-Zharova, T., Diakon, V., & Manuilenco, R. (2023). Development of mathematical models to support decision-making regarding the functioning of critical infrastructure in the industry of energy supply. Technology Audit and Production Reserves, 6(2(74), 44–49. https://doi.org/10.15587/2706-5448.2023.293205

Issue

Section

Systems and Control Processes