[Research Contribution] Assessing the potential of wind energy exploitation in Vietnam

20 February, 2025

Keywords: Kernel Density Estimation (KDE), Energy conversion, Bandwidth selection, Kernel density estimation, Non-parametric distribution, Wind energy, Wind speed distribution.

Analyzing the factors affecting wind energy exploitation can optimize energy planning and contribute to sustainable development in the context of global energy transition. Confronted with the challenges of climate change and the need to reduce emissions, accurately assessing wind energy potential has become an important task to ensure energy security and reduce dependence on fossil fuels. With this goal, the research team from UEH Mekong, University of Economics Ho Chi Minh City conducted a study on “Assessing the potential of wind energy exploitation in Vietnam using the Kernel Density Estimation (KDE) model”.

Study background

In the context of increasingly serious climate change, renewable energy plays an important role in reducing greenhouse gas emissions and protecting the environment. In particular, wind energy is highly appreciated for its sustainability and wide applicability globally.

With the advantage of a long coastline and favorable climate conditions, Vietnam is considered one of the most potential countries in the region for wind energy development. According to the Global Wind Energy Council, the installed wind power capacity in Vietnam can reach approximately 4.6 GW in 2023 and is expected to increase to 36 GW by 2030. However, to effectively exploit this resource, in-depth studies are needed to accurately and scientifically assess wind potential. This is an important foundation for orienting renewable energy development planning towards sustainable goals for the country.

Research Methodology

The study used wind speed data collected over a one-year period in 06 different areas in Vietnam including Ea Phe, Da Loan, Ea Drang, Ia Der, Kon Dong, and My Thanh. The data is part of the project “Establishment of Legal Framework and Technical Assistance to Grid Connected Wind Power Development in Vietnam”. Wind speed was recorded at a height of 80m – the ideal height for wind turbine installation – with a recording frequency of every 30 minutes.

For the analysis, the authors applied the Kernel Density Estimation (KDE) method. This non-parametric method does not require prior assumptions about the distribution of the data and is highly suitable when processing complex and variable data such as wind speed. To increase accuracy, the study also tested different bandwidth selection methods to optimize the results from the KDE model.

KDE Distribution Response Curves by Each Bandwidth Selection Method

Research Results and Practical Significance

The study indicates that the two bandwidth selection methods LSCV and Scott in the KDE model work effectively in simulating the wind speed distribution in the research areas. When combined with the power curve of the Enercon E82/2300 turbine, the authors accurately estimated the potential power output for each area.

Remarkably, the results illustrate that My Thanh and Kon Dong have the highest potential, with an annual output exceeding 2000 kWh per turbine. In contrast, Ea Drang recorded the lowest level, only about 561 kWh. These findings confirm that the assessment of local wind speed is a key factor in the planning and development of wind farms, helping to optimize energy extraction efficiency.

Overall, the study has provided an accurate wind energy potential assessment model, opening up important applications in renewable energy planning and exploitation. The KDE method is not only suitable for Vietnam but can also be applied in many other regions in the world, contributing to the effective exploitation of global wind energy resources. In addition, the research results help support decision-making in selecting turbine installation locations, system design and operational management, positively contributing to the goal of sustainable development.

However, the 01-year data range from 06 regions is insufficient to fully reflect long-term climate fluctuations. The lack of integration of factors like terrain, temperature and humidity can reduce the accuracy of the forecast. In addition, although the KDE method is flexible, it requires complex calculations, leading to high application costs.

To enhance practical value, the study needs to extend the data collection period, to integrate more environmental factors, and to improve the model to increase feasibility to contribute to Vietnam’s sustainable development and energy transition strategy.

The full-text research article on Assessing the potential for wind energy exploitation in Vietnam can be accessed HERE

Authors: Prof. Dr. Do Duc Ton, Dr. Chau Trung Tin, Nguyen Ngoc Tuan – Nazarbayev University & University of Economics Ho Chi Minh City

This article is part of a series spreading research and applied knowledge with the message “For a More Sustainable Mekong”, under the program “Research Contribution For All” implemented by UEH. UEH cordially invites readers to read the next UEH Research Insights newsletter.

News, photos: The authors, UEH Mekong Department of Admissions and Communications, UEH Department of Communications and Partnerships

Audio: Thanh Kieu