Klepikova S. Management of energy efficiency of industrial enterprises

The thesis is devoted to actual problems of theoretical, methodical and practical aspects of management of energy efficiency of an industrial enterprise. In the dissertation the theoretical basis is investigated, the variety of formulations of the concepts of "energy efficiency", "energy saving", "energy efficiency management" and the use of them in work are considered. The Laws of Ukraine on energy conservation, the international and national standards, the methodology of energy audit are analyzed, and the expediency of introducing the corresponding additions to take into account the multiplicative and synergetic effects of energy resources saving during the modernization of the power equipment is established. It is suggested and justified the feasibility of using artificial neural networks (ANN) in the management of energy efficiency of an industrial enterprise. The method of determination of the energy intensity of an enterprise with the help of ANN is developed, with the involvement of expert estimation methods, a priori ranking and correlation-regression analysis. A mathematical model based on a multilayered straightforward perceptron synthesized by the genetic algorithm method was created. The efficiency of the methodological approach was checked, as well as its testing according to the statistics of the leading Kharkiv enterprises. In the process of testing and analyzing its results, the conclusions were drawn about the need for: systematic accumulation of annual statistics, both the indicator itself and the factors that influence it; analysis of calculations and establishment of correctness of data accounting; identifying typical differences in the interpretation of a factor and making appropriate adjustments; taking into account the features of the enterprise; carrying out with the help of ANN research on the choice of rational values of production indicators - input values of the neural network that affect the indicator of energy intensity; studies on improving accuracy and forecasting due to changes in the structure and type of neural network, etc. Such a wide range of functions and the need for their systematic implementation led to the conclusion that it is advisable to create in the management structure of an industrial enterprise a structure that would include specialists capable of performing these functions - the Intelligent Energy Management Group (IEM). The practical result of the dissertation work on taking into account the multiplicative and synergistic effects is: first, the conclusion about the expediency of taking into account these effects when conducting an internal energy audit, for which it is necessary to make appropriate additions to its methodology of its conduct; secondly, the conclusion about the expediency of introducing into the legislative and regulatory acts the amendments that stimulate the enterprises to prioritize the modernization of power equipment with multiplicative and synergistic effect (as such, which provides significant savings of fuel and energy resources at the state level). Recommendations are given on the use of the results of work at different hierarchical levels of energy efficiency management and in other types of industrial enterprise management.