Kononov Yu.D.Melentiev Energy Systems Institute of Siberian Branch of Russian Academy of Sciences (ESI SB RAS), Irkutsk, Russian Federation kononov@isem.irk.ru ORCID id: not available
Kononov D.Yu.Melentiev Energy Systems Institute of Siberian Branch of Russian Academy of Sciences (ESI SB RAS), Irkutsk, Russian Federation dima@isem.irk.ru ORCID id: not available
Subject. The article examines how the discount rate chosen influences the reasonableness of power engineering development forecasts. Economic-mathematical models of optimization serve as the main methodological tool for long-term forecasting on power engineering. Development scenarios are chosen and compared by the lowest amount of discounted cash flows for supplying fuel and energy as much as needed. Such models do not provide for generally accepted methods for substantiating values of the discount rate. Objectives. We identify distinctions in cost discounting, and results throughout phases of power engineering forecasting. We also evaluate how the discount rate chosen influences the outcome of forecasts. Methods. The study is based on the systems analysis of foreign and national practices and original methodological tools that concurrently optimizes the development of power engineering systems and uses the Monte-Carlo method. Results. The article substantiates that optimization models shall employ different approaches to discounting at different hierarchical levels of forecast studies into the fuel and energy complex development. Illustrating the optimization of the development of regional power supply systems, we demonstrate that the discount rate considerably influences the way capacities of power plants are put into operation, and other analyzable indicators. Conclusions and Relevance. Used to forecast the development of power engineering development, the discount rate depends on a future scenario in question. It is set with reference to the forecasted aspect, objectives and methods of forecast studies, the way they accommodate for the evolution of power markets. The more unlikely the future, the higher the risk component of the discount.
Keywords: energy sector, projections, economic sustainability, optimization, discounting
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