energyЭнергетика. Известия высших учебных заведений и энергетических объединений СНГENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations1029-74482414-0341BNTU10.21122/1029-7448-2022-65-4-301-316energy-2177Research ArticleЭЛЕКТРОЭНЕРГЕТИКАELECTRICAL POWER ENGINEERINGМетодика оптимизации компоновки ветроэлектростанций морского базирования с учетом затрат на электрическую систему сбора мощностиOffshore Wind Farm Layout Optimization Considering the Power Collection System CostОбуховС. Г.ObukhovS. G.

Адрес для переписки:Обухов Сергей Геннадьевич - Национальный исследовательский Томский политехнический университет,просп. Ленина, 30, 634050, г. Томск, Российская Федерация.Тел.: +7 3822 70-17-77serob@tpu.ru

Address for correspondence:Obukhov Sergey G. - National Research Tomsk Polytechnic University30, Lenina Ave., 634050, Tomsk, Russian FederationTel.: +7 3822 70-17-77serob@tpu.ru

serob@tpu.ruДавыдовД. Ю.DavydovD. Y.

г. Томск

Tomsk

serob@tpu.ruНациональный исследовательский Томский политехнический университетРоссияNational Research Tomsk Polytechnic UniversityRussian Federation202202082022654301316Copyright © Обухов С.Г., Давыдов Д.Ю., 20222022Обухов С.Г., Давыдов Д.Ю.Obukhov S.G., Davydov D.Y.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://energy.bntu.by/jour/article/view/2177

Предложена методика оптимизации компоновки ветроэлектростанций морского базирования для повышения их эффективности за счет снижения влияния эффекта аэродинамического затенения, минимизации электрических потерь в кабельных линиях системы приема и передачи электрической энергии, вырабатываемой ветроэлектрическими установками в электрическую сеть энергосистемы. Задача сводится к определению нескольких параметров, которыми задаются геометрические размеры и форма компоновочной сетки с предварительно установленными местами расположения турбин. Такой подход, в отличие от покоординатного метода поиска, дает возможность выполнять построение симметричных сеточных схем расположения ветроэлектрических установок, которые на практике более удобны с точки зрения обслуживания и эксплуатации. Совместно с оптимизацией компоновки производятся поиск оптимального места расположения морской трансформаторной подстанции и синтез схемы кабельных соединений между ветроэлектрическими установками. Для решения данной задачи используется эвристический алгоритм поиска минимального остовного дерева с ограничением на проводимость связей, позволяющий осуществлять построение реалистичных схем и более адекватно оценивать их технико-экономические характеристики. Как показали результаты апробации предложенной методики на примере оптимизации компоновки ветроэлектростанции Horns Rev 1, использование такого подхода позволило сократить стоимость электрической системы на 10–12 %. Это на 7–11 % превосходит результат, полученный при использовании MST-алгоритма, выполняющего построение схемы кабельных соединений упрощенной топологии. Изменение размеров и формы границ площадки ветроэлектростанции привело к увеличению расчетной выработки электроэнергии на 2,3 % и снижению ее себестоимости на 4 %. При оптимизации компоновки ветроэлектрических установок в пределах фиксированных границ площадки эти показатели улучшены только на 1 и 2 % по сравнению с оригинальной схемой.

The paper proposes a method for optimizing the layout of offshore wind farms to increase their efficiency by reducing the effect of aerodynamic shading, minimizing electrical losses in cable lines of the system for receiving and transmitting electrical energy generated by wind turbines to the electrical grid of the power system. The task is reduced to determining several parameters that define the geometric dimensions and shape of the layout grid with pre-installed tur-bine locations. This approach, in contrast to the coordinate-wise search method, makes it possible to build symmetrical grid layouts of wind power plants, which in practice are more convenient in terms of maintenance and operation. Together with the optimization of the layout, the search for the optimal location of the offshore transformer substation and the synthesis of the scheme of cable joints between wind power plants has been carried out. To solve this problem, a heuristic algorithm was used to search for a minimum spanning tree with a restriction on the conductivity of connections, which made it possible to build realistic schemes and more adequately assess their technical and economic characteristics. As the results of testing the proposed methodology on the example of optimizing the layout of the Horns Rev 1 wind farm have shown, the use of this approach has reduced the cost of the electrical system by 10–12 %. This is 7–11 % higher than the result obtained by using the MST algorithm, which performs the construction of a circuit of cable joints of a simplified topology. The change in the size and shape of the boundaries of the wind farm site resulted in an increase in the estimated electricity generation by 2.3 % and a decrease in its cost by 4 %. When optimizing the layout of wind turbines within the fixed boundaries of the site, these indicators are improved by only 1 and 2 % as compared to the original scheme.

ветроэнергетикаморские ветроэлектростанциикомпоновка ветроэлектростанцийминимизация потерь мощностиаэродинамический эффектсебестоимость энергииоптимизация схемы кабельных соединенийwind energyoffshore wind farmswind farm layoutpower loss minimizationaerodynamic effectcost of energycable joints layout optimizationReferencesМарченко, О. B. Конкурентоспособность солнечных и ветровых электростанций в странах СНГ / О. B. Марченко, С. В. Соломин // Энергетика. Изв. высш. учеб. заведений и энерг. объединений СНГ. 2020. Т. 63, № 4. С. 301–311. https://doi.org/10.21122/1029-7448-2020-63-4-301-311.Marchenko O. V., Solomin S. V. (2020) Competitiveness of Solar and Wind Power Plants in the Countries of the Commonwealth of Independent States. Enеrgеtika. Izvestiya Vysshikh Uchebnykh Zavedenii i Energeticheskikh Ob’edinenii SNG = Energetika. Proceedings of CIS Higher Education Institutions and Power Engineering Associations, 63 (4), 301–311. https://doi.org/10.21122/1029-7448-2020-63-4-301-311 (in Russian).Петруша, Ю. С. Перспективы развития ветроэнергетики в Республике Беларусь / Ю. С. Петруша, Н. А. Попкова // Энергетика. Изв. высш. учеб. заведений и энерг. объединений СНГ. 2019. Т. 62, № 2. С. 124–134. https://doi.org/10.21122/1029-7448-2019-62-2-124-134.Petrusha U. S., Papkova N. A. (2019) The Prospects for Wind Energy Development in the Republic of Belarus. Enеrgеtika. Izvestiya Vysshikh Uchebnykh Zavedenii i Energeticheskikh Ob’edinenii SNG = Energetika. Proceedings of CIS Higher Education Institutions and Power Engineering Associations, 62 (2), 124–134. https://doi.org/10.21122/1029-7448-2019-62-2-124-134 (in Russian).Global Wind Energy Council. Global Offshore Wind Report 2020 [Electronic Resource]. Mode of access: https://gwec.net/global-offshore-wind-report-2020.Global Wind Energy Council. Global Offshore Wind Report 2020. Available at: https://gwec.net/global-offshore-wind-report-2020.A Review on Development of Offshore Wind Energy Conversion System / J. Li [et al.] // International Journal of Energy Research. 2020. Vol. 44, Iss. 12. P. 9283–9297. https://doi.org/10.1002/er.5751.Li J., Wang G., Li Z., Yang S., Chong W. T., Xiang X. (2020) A Review on Development of Offshore Wind Energy Conversion System. International Journal of Energy Research, 44 (12), 9283–9297. https://doi.org/10.1002/er.5751.U. S. Energy Information Administration’s Annual Energy Outlook 2020. Levelized Cost and Levelized Avoided Cost of New Generation Resources [Electronic Resource]. Mode of access: https://www.eia.gov/outlooks/aeo/pdf/electricity_generation.pdf.U. S. Energy Information Administration’s Annual Energy Outlook 2020. Levelized Cost and Levelized Avoided Cost of New Generation Resources. Available at: https://www.eia.gov/outlooks/aeo/pdf/electricity_generation.pdf.Modelling and Measuring Flow and Wind Turbine Wakes in Large Wind Farms Offshore / R. J. Barthelmie [et al.] // Wind Energy. 2009. Vol. 12, Iss. 5. P. 431–444. https://doi.org/10.1002/we.348.Barthelmie R. J., Hansen K., Frandsen S. T., Rathmann O., Schepers J. G., Schlez W., Phillips J., Rados K., Zervos A., Politis E. S., Chaviaropoulos P. K. (2009). Modelling and Measuring Flow and Wind Turbine Wakes in Large Wind Farms Offshore. Wind Energy, 12 (5), 431–444. https://doi.org/10.1002/we.348.Давыдов, Д. Ю. Оптимизация расположения ветроустановок с учетом аэродинамического взаимовлияния и протяженности кабельных линий сети сбора мощности / Д. Ю. Давыдов, С. Г. Обухов // Энергосбережение и водоподготовка. 2020. Т. 125, № 3. С. 30–34.Davydov D. Y., Obukhov S. G. (2020) Wind Farm Layout Optimization Considering Wake Effects and Length of Power Collection Cables. Energosberezhenie i Vodopodgotovka = Energysaving and Watertreatment, 125 (3), 30–34 (in Russian).A Review of Offshore Wind Farm Layout Optimization and Electrical System Design Methods / P. Hou [et al.] // Journal of Modern Power Systems and Clean Energy. 2019. Vol. 7. P. 975–986. https://doi.org/10.1007/s40565-019-0550-5.Hou P., Zhu J., Ma K., Yang G., Hu W., Chen Z. (2019) A Review of Offshore Wind Farm Layout Optimization and Electrical System Design Methods. Journal of Modern Power Systems and Clean Energy, 7, 975–986. https://doi.org/10.1007/s40565-019-0550-5.A Review of Methodological Approaches for the Design and Optimization of Wind Farms / J. F. Herbert-Acero [et al.] // Energies. 2014. Vol. 7, Iss. 11. P. 6930–7016. https://doi.org/10.3390/en7116930.Herbert-Acero J. F., Probst O., Réthoré P., Larsen G. C., Castillo-Villar K. K. (2014) A Review of Methodological Approaches for the Design and Optimization of Wind Farms. Energies, 7 (11), 6930–7016. https://doi.org/10.3390/en7116930.Optimal Wind-Turbine Micro-Siting of Offshore Wind Farms: A Grid-Like Layout Approach / J. S. Gonzalez [et al.] // Applied Energy. 2017. Vol. 200. P. 28–38. https://doi.org/10.1016/j.apenergy.2017.05.071.González J., Trigo-Garcia A., Payán M., Santos J., Gonzalez Rodríguez A. (2017) Optimal Wind-Turbine Micro-Siting of Offshore Wind Farms: A Grid-Like Layout Approach. Applied Energy, 200, 28–38. https://doi.org/10.1016/j.apenergy.2017.05.071.Feng, J. Co-Optimization of the Shape, Orientation and Layout of Offshore Wind Farms / J. Feng, W. Z. Shen // Journal of Physics: Conference Series. 2020. Vol. 1618. https://doi.org/10.1088/1742-6596/1618/4/042023.Feng J., Shen W. Z. (2020) Co-Optimization of the Shape, Orientation and Layout of Offshore Wind Farms. Journal of Physics: Conference Series, 1618, 042023. https://doi.org/10.1088/1742-6596/1618/4/042023.Combined Optimization for Offshore Wind Turbine Micro Siting / P. Hou [et al.] // Applied Energy. 2017. Vol. 189. P. 271–282. https://doi.org/10.1016/j.apenergy.2016.11.083.Hou P., Hu W., Soltani M., Chen C., Chen Z. (2017) Combined Optimization for Offshore Wind Turbine Micro Siting. Applied Energy, 189, 271–282. https://doi.org/10.1016/j.apenergy.2016.11.083.Elkinton, C. N. Algorithms for Offshore Wind Farm Layout Optimization / C. N. Elkinton, J. F. Manwell, J. G. McGowan // Wind Engineering. 2008. Vol. 1, Iss. 1. P. 67–84. https://doi.org/10.1260/030952408784305877.Elkinton C. N., Manwell J. F., McGowan J. G. (2008) Algorithms for Offshore Wind Farm Layout Optimization. Wind Engineering, 32 (1), 67–84. https://doi.org/10.1260/030952408784305877.Esau, L. R. On Teleprocessing System Design: Part II a Method for Approximating the Optimal Network / L. R. Esau, K. C. Williams // IBM Systems Journal. 1966. Vol. 5, Iss. 3. P. 142–147. https://doi.org/10.1147/sj.53.0142.Esau L. R., Williams K. C. (1966) On Teleprocessing System Design: Part II a Method for Approximating the Optimal Network. IBM Systems Journal, 5 (3), 142–147. https://doi.org/10.1147/sj.53.0142.Katsouris, G. Infield Cable Topology Optimization of Offshore Wind Farms: Master of Science Thesis / G. Katsouris. Delft University of Technology. Delft, 2015. 86 p.Katsouris G. (2015) Infield Cable Topology Optimization of Offshore Wind Farms: Master of Science Thesis. Delft, Delft University of Technology. 86.Fischetti, M. Optimal Wind Farm Cable Routing: Modeling Branches and Offshore Transformer Modules / M. Fischetti, D. Pisinger // Networks. 2018. Vol. 72, Iss. 1. P. 42–59. https://doi.org/10.1002/net.21804.Fischetti M., Pisinger D. (2018) Optimal Wind Farm Cable Routing: Modeling Branches and Offshore Transformer Modules. Networks, 72 (1), 42–59. https://doi.org/10.1002/net.21804.Erdem, U. M. Fast Line Segment Intersection. MATLAB Central File Exchange [Electronic Resource]. 2010. Mode of access: https://www.mathworks.com/matlabcentral/fileexchange/ 27205-fast-line-segment-intersection.Erdem U. M. (2010) Fast Line Segment Intersection. MATLAB Central File Exchange. Available at: https://www.mathworks.com/matlabcentral/fileexchange/27205-fast-line-segment-intersection.Katic, I. A Simple Model for Cluster Efficiency / I. Katic, J. Hojstrup, N. Jensen // EWEC'86. European Wind Energy Association Conference and Exhibition. Proceedings Vol. 1. Rome, 1987. P. 407–410.Katic I., Hojstrup J., Jensen N. (1987) A Simple Model for Cluster Efficiency. EWEC'86. Proceedings. European Wind Energy Association Conference and Exhibition Vol. 1. Rome, 407–410.Feng, J. Solving the Wind Farm Layout Optimization Problem Using Random Search Algorithm / J. Feng, W. Z. Shen // Renewable Energy. 2015. Vol. 78. P. 182–192. https://doi.org/10.1016/j.renene.2015.01.005.Feng J., Shen W. Z. (2015) Solving the Wind Farm Layout Optimization Problem Using Random Search Algorithm. Renewable Energy, 78, 182–192. https://doi.org/10.1016/j.renene.2015.01.005.Frohboese, P. Thrust Coefficients Used for Estimation of Wake Effects for Fatigue Load Calculation / P. Frohboese, C. Schmuck // European Wind Energy Conference and Exhibition. Warsaw, 2010.Frohboese P., Schmuck C. (2010) Thrust Coefficients Used for Estimation of Wake Effects for Fatigue Load Calculation. European Wind Energy Conference and Exhibition. Warsaw.Обухов, С. Г. Методика оптимизации состава оборудования электроэнергетических систем на основе возобновляемых источников энергии / С. Г. Обухов, Г. Н. Климова, А. Ибрагим // Вестник ИГЭУ. 2020. № 6. С. 25–38.Obukhov S. G., Klimova G. N., Ibrahim A. (2020) Methodology of Optimum Unit Commitment of Energy Systems with Renewable Energy Sources. Vestnik IGEU = Vestnik of Ivanovo State Power Engineering University, (6), 25–38 (in Russian).Lundberg, S. Performance Comparison of Wind Park Configurations: Technical Report No 30R / S. Lundberg. Chalmers University of Technology, 2003. 202 p.Lundberg S. (2003) Performance Comparison of Wind Park Configurations. Technical Report No 30R. Goteborg, Chalmers University of Technology. 202.Gerdes, G. Case Study: European Offshore Wind Farms – A Survey for the Analysis of the Experiences and Lessons Learnt by Developers of Offshore Wind Farms / G. Gerdes, A. Tiedemann, S. Zeelenberg. Groningen: University of Groningen, 2008. 158 p.Gerdes G., Tiedemann A., Zeelenberg S. (2008) Case Study: European Offshore Wind Farms – A Survey for the Analysis of the Experiences and Lessons Learnt by Developers of Offshore Wind Farms. S. l. University of Groningen. 158.Vestas V80 Offshore. [Electronic Resource]. Mode of access: https://en.wind-turbine-models.com/turbines/668-vestas-v80-offshore. Date of access: 15.12.2020.Vestas V80 Offshore. Available at: https://en.wind-turbine-models.com/turbines/668-vestas-v80-offshore (Accessed 15 December 2020).The Kingfisher Information Service – Offshore Renewable & Cable Awareness Project (KIS-ORCA). Horns Rev 1 Awareness Chart [Electronic Resource]. Mode of access: https://kis-orca.org/wp-content/uploads/2022/03/Chart-38-Horns-Rev-1.pdf. Date of access: 15.12.2020.The Kingfisher Information Service – Offshore Renewable & Cable Awareness project (KIS-ORCA). Horns Rev 1 Awareness Chart. Available at: https://kis-orca.org/wp-content/uploads/2022/03/Chart-38-Horns-Rev-1.pdf (Accessed 15 December 2020).Nexans Submarine Power Cables [Electronic Resource]. Mode of access: https://www.nexans.com/Germany/2013/SubmPowCables_FINAL_10jun13_engl.pdf. Date of access: 16.12.2020.Nexans Submarine Power Cables. Available at: https://www.nexans.com/Germany/2013/SubmPowCables_FINAL_10jun13_engl.pdf (Accessed 16 December 2020).XLPE Submarine Cable Systems Attachment to XLPE Land Cable Systems: User’s Guide [Electronic Resource]. Mode of access: https://new.abb.com/docs/default-source/ewea-doc/xlpe-submarine-cable-systems-2gm5007.pdf. Date of Access: 16.12.2020.XLPE Submarine Cable Systems Attachment to XLPE Land Cable Systems: User’s Guide. Available at: https://new.abb.com/docs/default-source/ewea-doc/xlpe-submarine-cable-systems-2gm5007.pdf. (Accessed 16 December 2020).RP5 Weather Archive in Blavand [Electronic Resource]. Mode of access: https://rp5.md/Weather_archive_in_Blavand. Date of access: 16.12.2020.RP5 Weather Archive in Blavand. Available at: https://rp5.md/Weather_archive_in_Blavand (Accessed 16 December 2020).Обухов, С. Г. Сравнительный анализ методов оценки параметров распределения Вейбулла для повышения точности прогнозирования ветроэнергетического потенциала / С. Г. Обухов, Д. Ю. Давыдов // Международный технико-экономический журнал. 2019. № 5. С. 7–15. https://doi.org/10.34286/1995-4646-2019-68-5-7-15.Obukhov S. G., Davydov D. Y. (2019) Comparative Study of Methods for Estimating Weibull Parameters to Improve Accuracy of Probabilistic Wind Energy Models. Mezhdunarodnyi Tekhniko-Ekonomicheskii Zhurnal = The International Technical-Economic Journal, 5, 7–15. https://doi.org/10.34286/1995-4646-2019-68-5-7-15 (in Russian).

The authors declare that there are no conflicts of interest present.