Optimization of equipment composition of hybrid energy systems with renewable energy sources
Автор: Obukhov S.G., Ibrahim A.
Журнал: Вестник Южно-Уральского государственного университета. Серия: Энергетика @vestnik-susu-power
Рубрика: Альтернативные источники энергии
Статья в выпуске: 2 т.20, 2020 года.
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The article develops of a methodology and a software application to optimize the equipment composition of hybrid energy systems with renewable energy sources. The paper describes the proposed methodology and the mathematical models of the main components of hybrid systems: a photovoltaic station, a wind power plant, a battery and a diesel generator set. A distinctive feature of the proposed method is an original model used to forecast the solar radiation based on the data of the National Aeronautics and Space Administration. This allows it to be used for predicting the main characteristics of solar radiation in any location of Russia, including the territories with no regular actinometric observations data. The reverse Weibull distribution function is used to predict the daily course of the wind speed, which provides an increase in the reliability of predicting the generation of electricity by the wind power plant at daily time intervals. An evolutionary particle swarm algorithm is utilized to solve the optimization problem, which provides for a reliable and efficient definition of the global extremum of the objective function under various optimization criteria and constraints. A practical example of the proposed methodology use in selecting the optimal composition of the equipment of a hybrid energy system with a different equipment configuration is considered for an area located in the Vladivostok city. The proposed technique is implemented as a software application in the popular mathematical complex MATLAB, which ensures the convenience of its practical application.
Hybrid power system, renewable energy, optimization of equipment composition, particle swarm optimization algorithm
Короткий адрес: https://sciup.org/147234055
IDR: 147234055 | DOI: 10.14529/power200206