What are the advantages of Offshore Wind Power in Vietnam?

According to the World Bank [1], Vietnam's technical offshore wind power potential is about 475 GW in waterzones 200 km from the coastline- Figure 1; or according to the research group of Vietnam, Ireland and Japan [2], Vietnam's technical offshore wind power potential in the waterzones from 0 - 185 km up to 600 GW. These figures have partly proved the huge potential of offshore wind power in our country.

Figure 1. Technical offshore wind potential in Vietnam [1]

Although the offshore wind potential in Vietnamis not as good as the offshore wind potential in the North Sea - Europe, the offshore wind characteristicsin our country has a great advantage forarranging the wind farm layout - that is wind direction, with 2 main monsoon seasons following 2 main directions: Northeast and Southwest - Figure 2. Therefore, along with the power density as the offshore wind farms in the North Sea, the wind farm layout in Vietnam will be designed: reduce the distance between the turbines in the non-main wind direction and increase the distance between the turbines in the main wind direction, which will help to minimize the wake loss effect between the turbines, also helps to reduce the amount of marine cable connecting wind turbines and optimize the use of marine space. In this paper, the author illustrates choosing a wind turbine layout with the main distance between wind turbines of 4 x 18D: the distance in the non-main wind direction is 4D, in the main wind direction is 18D ( D - rotor diameter of the wind turbine). The offshore wind farm layout is also consistent with the power density trend of offshore wind farms in the world [3], [4].

Figure 2. Wind rose in Vietnam and in the North Sea – Europe [5]

In the bellow, the authors will analyze more detailed offshore wind power characteristics in Vietnam such as: the net capacity factor map, how the capacity factor of the wind farm changes over months in an operated year…

The input parameters for the calculation are as follows:

-     Wind potential from Global wind atlas data source at 100 m ASL [5].

-     Total capacity of wind farm: 600 MW.

-     Wind turbine with a rated capacity of 10 MW, rotor diameter 185 m, cut-in wind speed of 3 m/s, rated wind speed of  13 m/s and cut-out wind speed of 25 m /s.

- Power density: According to studies [3] and [4], the power density of offshore wind farm will decrease as the total installed capacity of wind farm increases; As presented at the beginning of this paper, the 600 MW offshore wind farm layout is designed with 15 x 4 turbines (the distance between the turbines is 4 x 18D). Then the designed power density of offshore wind farms is: 5.8 MW / km2.

- Wake loss model: N.O Jensen, the calculation is based on the commercial software WindPRO [6].

- Preliminary estimated losses (exclude the wake loss) during the operation of the wind farm around 10%. These losses mainly include: availability loss (stopping due to breakdown, routine maintenance), power transmission loss, environmental influences...

Figure 3 shows the calculation results of the net capacity factor map of a offshore wind farm with a total capacity of 600 MW in Vietnam. The coastal areas along the South Central Coast provinces have quite high capacity factor; Especially the coastal along the area near Binh Thuan province, the capacity factor is very high (~ 50%) and most of this sea area is quite shallow (seabed depth < 50 m), highly suitable for developing offshore wind farms using fixed foundations.

Figure 3. Net capacity factor map of 600 MW offshore wind farm in Vietnam [7]

Considering an offshore wind farm in the position symbol () in Figure 3 with an annual average wind speed of 9.5 m/s, the calculation results of the monthly generated capacity factor are presented in Figure 4. It can be determined that: In the Northeast monsoon months (December - January - February), the offshore wind farm has a very high capacity factor, typically in January - the capacity factor is over 80%. Figure 5 shows the calculation of the generated power in the first half of January 2020 of the offshore wind farm based on simulation data of wind speed ERA5 [8]: Most of the operating days during this time period, the generated power is quite stable and close to the rated power of the offshore wind farm.

Figure 4. Monthly capacity factor of 600 MW offshore wind farm[7]

Figure 5. Generated power of 600 MW offshore wind farm in the first half of January 2020 of Northeast monsoon in Vietnam [7]

According to recent studies [9] [10], with the application of predictive models based on artificial intelligence (AI), big data, scanning LiDAR, numerical weather prediction (NWP) model, the accuracy of wind power output forecasting has been improved. This also contributes to increasing the proportion of renewable energy sources in the power system, especially offshore wind power.

Therefore, if the offshore wind farms in the South Central Coast region are developed, they will partly support the power system because: the generated power is stable, the model of generated power forecasting is getting more and more accuracy and the monsoon season period when wind power reaches its best capacity factor coincide with the peak dry season in the South of our country - when hydropower is running out of water resources.

Reference:

[1]/ ESMAP, “Going Global: Expanding Offshore Wind to Emerging Markets,” World Bank, Washington DC, 2019.

[2]/ V. D. Quang, Q. V. Doan, V. N. Dinh and N. D. Duc, “Evaluation of resource spatial-temporal variation, dataset validity, infrastructures and zones for Vietnam offshore wind energy”, Vietnam Journal of Science, Technology and Engineering 62(1), 3-16; DOI: 10.31276/VJSTE.62(1).03-16, 2020, 2020.

[3]/ Musial, W., P. Beiter, D. Heimiller, and G. Scott, “Offshore Wind Energy Resource Assessment for the United States” (Technical Report, NREL/TP-5000-66599), National Renewable Energy Laboratory (NREL), Golden, CO (US), 2016. http://www.nrel.gov/docs/fy16osti/66599.pdf.

[4]/ The Renewables Consulting Group LLC, “Analysis of Turbine Layouts and Spacing Between Wind Farms for Potential New York State Offshore Wind Development”, New York, 2019.

[5]/ Global Wind Atlas (version 3.0), Technical University of Denmark (DTU). https://globalwindatlas.info.

[6]/EMD, “WindPRO 3.4 - User manual: Energy calculation”, 2020

[7] EVNPECC3, “Báo cáo kết quả đánh giá sơ bộ tiềm năng điện gió ngoài khơi Việt Nam”, 2021.

[8]/ Copernicus Climate Change Service (C3S), https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview.

[9] IRENA, “Innovation landscape brief: Advanced forecasting of variable renewable power generation”,International Renewable Energy Agency, Abu Dhabi, 2020.

[10] L. Valldecabres and M. Kühn, “On the use of remote sensing measurements for very short-term forecasting of offshore wind power”, Offshore Wind R&D Conference 2018, 2018.

Authors:

LE THANH VINH – RENEWABLE ENERGIES DEPARTMENT, POWER ENGINEERING CONSULTING J.S COMPANY 3.

DR. DINH VAN NGUYEN -  ANTS & MAREI CENTRE, UCC, IRELAND; AVSE GLOBAL MEMBER.