Поагрегатная оценка капиталовложений в энергоблоки электростанций с использованием параметрической степенной функции

Abstract

In the course of designing new generating equipment for power plants and their thermal circuits, in the absence of information about their cost, analog indicators and/or expert assessments are used in the design practice. This approach allows us to compare various options if they can be brought to a comparable form and when the same type of equipment is used. When it is necessary to compare options that differ not only in the specified capacity, but also in the equipment configuration, a more accurate assessment of investment is required. The article proposes a method for estimating capital investment in power plants using a power parametric function. Capital investment is assessed for each unit of the power plant and its engineering system. A special feature of the approach is that the higher the cost of the unit is, the higher its thermodynamic characteristics, power, time of load use, etc. These factors are taken into account by the exponent in the power function. In addition, the correction coefficients take into account the configuration of the equipment, its climatic design, and configuration features. The combination of factors that are taken into account in the power function makes it possible to obtain an estimate of the cost of equipment in different versions. The uniformity of the problem statement makes it possible to apply the approach both to design tasks and to scientific and applied tasks of comparing the existing, newly developed and promising technologies. This paper presents the updating and development of the method developed in previous years at the department of thermal power plants of NSTU. Equations for determining investment in the main units and technical systems of power plants are presented. Estimates of investment in power plants currently under construction in Russia are made. It is shown that investment in power plants in Russia is 20-50% lower than in the USA and Europe, and 20-30% higher than in China.