The problem-oriented library SOWFA for solving the applied tasks of wind energy

Kraposhin, Matvey; Стрижак, С. В.

doi:10.15514/ispras-2018-30(6)-14

Proceedings of ISP RAS

2018

DOI: 10.15514/ispras-2018-30(6)-14

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The problem-oriented library SOWFA for solving the applied tasks of wind energy

Matvey Kraposhin¹,

С. В. Стрижак²

Abstract: Аннотация. В статье рассматриваются возможности открытой библиотеки SOWFA. Проблемно-ориентированная библиотека, работающая в составе открытого пакета OpenFOAM v.2.4.0, предназначена для решения задач ветроэнергетики. В связи со строительством новых ветропарков на территории РФ (Ульяновская область, республика Адыгея) вопросы проектирования, моделирования работы ветропарков и ветроустановок являются актуальными в настоящее время. В статье приводится описание структуры библиотеки SOWFA и некоторых ее классов. И… Show more

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Modeling and Investigation of the Effect of a Wind Turbine on the Atmospheric Boundary Layer

et al. 2022

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Wind power engineering is one of the environmentally safe areas of energy and certainly makes a significant contribution to the fight against CO2 emissions. The study of the air masses movement in the zone of wind turbines and their influence on the boundary layer of the atmosphere is a fundamental basis for the efficient use of wind energy. The paper considers the theory of the movement of air masses in the rotation zone of a wind turbine, and presents an analytical review of applied methods for modeling the atmospheric boundary layer and its interaction with a wind turbine. The results of modeling the boundary layer in the wind turbine zone using the STAR CCM+ software product are presented. The wind speed and intensity of turbulence in the near and far wake of the wind turbine at nominal load parameters are investigated. There is a significant decrease in the average wind speed in the near wake of the wind generator by 3 m/s and an increase in turbulent intensity by 18.3%. When considering the long-distance track behind the wind turbine, there is a decrease in the average speed by 0.6 m/s, while the percentage taken from the average value of the turbulent intensity is 7.2% higher than in the section in front of the wind generator. The influence of a wind turbine on the change in the temperature stratification of the boundary layer is considered. The experiments revealed a temperature change (up to 0.5 K), which is insignificant, but at night the stratification reaches large values due to an increase in the temperature difference in the surface boundary layer. In the long term, the research will contribute to the sustainable and efficient development of regional wind energy.

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Modeling and Investigation of the Effect of a Wind Turbine on the Atmospheric Boundary Layer

et al. 2022

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Applied Machine Learning to Study the Movement of Air Masses in the Wind Farm Area

Kovalnogov,

Fedorov,

Chukalin

et al. 2024

Energies

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Modeling the atmospheric boundary layer (ABL) in the area of a wind farm using computational fluid dynamics (CFD) methods allows us to study the characteristics of air movement, the shading effect, the influence of relief, etc., and can be actively used in studies of local territories where powerful wind farms are planned to be located. The operating modes of a wind farm largely depend on meteorological phenomena, the intensity and duration of which cause suboptimal operating modes of wind farms, which require the use of modern tools for forecasting and classifying precipitation. The methods and approaches used to predict meteorological phenomena are well known. However, for designed and operated wind farms, the influence of meteorological phenomena on the operating modes, such as freezing rain and hail, remains an urgent problem. This study presents a multi-layered neural network for the classification of precipitation zones, designed to identify adverse meteorological phenomena for wind farms according to weather stations. The neural network receives ten inputs and has direct signal propagation between six hidden layers. During the training of the neural network, an overall accuracy of 81.78%, macro-average memorization of 81.07%, and macro-average memorization of 75.05% were achieved. The neural network is part of an analytical module for making decisions on the application of control actions (control of the boundary layer of the atmosphere by injection of silver iodide, ionization, etc.) and the formation of the initial conditions for CFD modeling. Using the example of the Ulyanovsk wind farm, a study on the movement of air masses in the area of the wind farm was conducted using the initial conditions of the neural network. Digital models of wind turbines and terrain were created in the Simcenter STAR-CCM+ software package, version 2022.1; an approach based on a LES model using an actuating drive disk model (ADM) was implemented for modeling, allowing calculation with an error not exceeding 5%. According to the results of the modeling of the current layout of the wind turbines of the Ulyanovsk wind farm, a significant overlap of the turbulent wake of the wind turbines and an increase in the speed deficit in the area of the wind farm were noted, which significantly reduced its efficiency. A shortage of speed in the near and far tracks was determined for special cases of group placement of wind turbines.

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The problem-oriented library SOWFA for solving the applied tasks of wind energy

Cited by 2 publications

References 4 publications

Modeling and Investigation of the Effect of a Wind Turbine on the Atmospheric Boundary Layer

Modeling and Investigation of the Effect of a Wind Turbine on the Atmospheric Boundary Layer

Applied Machine Learning to Study the Movement of Air Masses in the Wind Farm Area

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