Dynamic mathematical programming model with stochastic variable for the development of the National Nuclear Power Sector

Shulzhenko S.V., PhD (Engin.), https://orcid.org/0000-0002-7720-0110
Institute of General Energy of the National Academy of Sciences of Ukraine, 172 Antonovycha St., Kyiv, 03680, Ukraine
Language: Ukrainian, English
Source: The Problems of General Energy, 2015, 1(40):5-19
Section: Mathematical modeling of energy facilities and systems
UDC: 621.311.001.57
Received: 12.05.2015
Published: 19.05.2015


Economic globalization stipulating the limited capabilities of the State to influence the national markets of fuel and energy resources that consequently leads to the volatility of markets and the introduction of market philosophy into power sector regulation result in significant rise of uncertainty of future conditions of the power sector operation and objectively necessitate the updating of existing and development of new mathematical models and forecasting methods that should take into account the above specified factors. This paper presents a mathematical optimization model of the development of national nuclear power sector that is capable of taking into account the growing variety of available nuclear technologies for power generation and also the increasing uncertainty of future conditions of the power sector operation, for example, the possible lifetime extension of existing nuclear power plant units that is simulated by an appropriate stochastic variable. Unlike the mathematical models built on using simulation methods that are inherent to studies of the development of nuclear power as the most conservative sector and capable of simulating the disturbances of external factors to a very limited extent resulting in a possible calculation of a limited number of the scenarios of development, the proposed mathematical model and its implementation algorithm are capable of simulating actually unlimited number of external disturbances, in particular, by using stochastic variables.

Keywords: Mathematical model, mathematical programming, stochastic variable, nuclear power plant, national power sector.


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