Identification and Classification of the States of Cogeneration Systems by Competitiveness Levels of Power Generating Companies

This paper tackles the issues of elaborating and researching methods for generating and selecting information for classifying the states of energy cogeneration systems according to levels of competitiveness. Assessment of the level of competitiveness consists in analyzing the state of centralized and distributed energy cogeneration systems, both in terms of local and integrated indicators of their operations. Joint analysis of the said systems is a complex task that requires the use of adapted methods for its solution. Creating methods for classifying the states of energy cogeneration systems according to levels of their competitiveness is a multilayered task. Since these systems are a combination of engineering, economic, environmental and other subsystems, the number of factors affecting their operations is rather high. A change in the state of energy cogeneration systems can be accompanied by a change in a variety of performance indicators. The behavior of such systems is effectively studied by means of mathematical statistics methods. It is well-known that the issues of diagnosticating and modeling the expected level of competitiveness of power generating companies are poorly formalized multiparametric problems with insufficiently defined information and multidimensional relationships between indicators that typify competitiveness. Therefore, the procedure for classifying the states of energy cogeneration systems according to their competitiveness levels, with subsequent review of both the properties of individual classes and the differences between them, fit well into the discriminant analysis model. The use of discriminant analysis technique made it possible to build a classification system that allows to identify the state of multidimensional objects in energy cogeneration systems. © 2021 WITPress. All rights reserved.The work was supported by Act 211 Government of the Russian Federation, contract No 02. A03.21.0006 and Russian Foundation for Basic Research (RFBR), contract № 20-010-00886