Author(s)

ALEXEY Y. DOMNIKOV, MICHAEL KHODOROVSKY, LIUDMILA DOMNIKOVA

Abstract

In real life energy problems that do not contain uncertainties are more of an exception than the rule. Solving the problems of analyzing the state and development of energy systems, including power generating companies, is seriously complicated by the uncertainty of initial information observed when describing the current and future level of competitiveness, as well as the uncertainty of criteria on quality of the state and of decisions on effective development being made. The difficulties in analyzing the state of energy systems caused by the influence of objective factors are such that, despite numerous researchers working in this area, they are still far from being overcome. Therefore, studies on improving the decision-making system to improve the competitiveness of a power generating company, taking into account the uncertainty factors in solving the tasks considered in this article, are relevant. The article proposes a scheme for elaborating a system of informational support for decision-making pertaining to development of a power generating company. Methods for determining results of operations on fuzzy parameter values have been developed. We present here methods for solving selection problems with fuzzy values of criterion assessments on a finite set of alternatives and classification problems with a fuzzy description of classes and values of indicators characterizing the power generating companies’competitiveness. An algorithm for informational support of the process of generation and selection of development alternatives for power generating companies in a high economic risk environment has been developed. In the course of this study we have reviewed the directions for increasing the level of competitiveness of a power generating company, taking into account any peculiarities of the use of innovative technologies in the area of energy generation in an environment where uncertainty and multiple criteria are present.

Keywords

power generation industry, efficiency, competition, strategy, reliability, risks, mathematical economic models, uncertainty, centralized energy sources