• Energy Research

In Vietnam, the energy demand shows an ever-increasing trend. To limit the utilization of fossil fuels and the following consequences for the environment, renewable energy sources must be adopted. In this context, the paper assesses the utilization of offshore wind and sea wave, by considering a commercial wind turbine and a prototypical wave energy converter. Solar energy can be optionally also collected by this device. An algorithm is introduced to find the best composition of the three sources able to cover a desired share of energy demand. The approach is applied to Ca Mau, a province in the southern part of Vietnam. Finally, the results encourage the adoption of these energy sources that could be easily implemented up to a share of the local energy demand equal to 65%.

Small wind turbines operating in low wind speed regions have not had any significant success. In addition, small wind speed regions occupy a large area of the world, so they represent a potential area for installing small wind turbines in the future. In this paper, a method to design an efficient airfoil for small wind turbines in low wind speed conditions using XFLR5 and CFD simulations is implemented. Because the impact of the airflow on the blade surface under low Re number conditions can change suddenly for small geometries, designing the airfoil shape to optimize the aerodynamic performance is essential. The tuning of the key geometric parameters using inversion techniques for better aerodynamic performance is presented in this study. A two-dimensional model was used to consider the airflow on the airfoil surface with differences in the angle of attack. The original S1010 airfoil was used to design a new airfoil for increasing the aerodynamic efficiency by using V6.57 XFLR5 software. Subsequently, the new VAST-EPU-S1010 airfoil model was adjusted to the maximum thickness and the maximum thickness position. It was simulated in low wind speed conditions of 4–6 m/s by a computational fluid dynamics simulation. The lift coefficient, drag coefficient, and CL/CD coefficient ratio were evaluated under the effect of the angle of attack and the maximum thickness by using the k-ε model. The simulation results show that the VAST-EPU-S1010 airfoil achieved the greatest aerodynamic efficiency at an angle of attack of 3°, a maximum thickness of 8%, and a maximum thickness position of 20.32%. The maximum value of CL/CD of the new airfoil at 6 m/s was higher than at 4 m/s by about 6.25%.

This article presents a research approach to enhancing the quality of short-term power output forecasting models for photovoltaic plants using a Long Short-Term Memory (LSTM) recurrent neural network. Typically, time-related indicators are used as inputs for forecasting models of PV generators. However, this study proposes replacing the time-related inputs with clear sky solar irradiance at the specific location of the power plant. This feature represents the maximum potential solar radiation that can be received at that particular location on Earth. The Ineichen/Perez model is then employed to calculate the solar irradiance. To evaluate the effectiveness of this approach, the forecasting model incorporating this new input was trained and the results were compared with those obtained from previously published models. The results show a reduction in the Mean Absolute Percentage Error (MAPE) from 3.491% to 2.766%, indicating a 24% improvement. Additionally, the Root Mean Square Error (RMSE) decreased by approximately 0.991 MW, resulting in a 45% improvement. These results demonstrate that this approach is an effective solution for enhancing the accuracy of solar power output forecasting while reducing the number of input variables.

Vietnam became the world’s third largest market for solar photovoltaic energy in 2020. Especially after the Vietnamese government issued feed-in tariffs for grid-connected solar photovoltaic systems, the installed capacity of solar photovoltaic applications exploded in 2019. From studies carried out in the relevant literature, it can be said that support policies are highly important for the initial development of the renewable energy industry in most countries. This is especially true in emerging countries such as Vietnam. This paper reviews the feed-in tariffs issued and deployed in different regions of Vietnam for grid-connected solar photovoltaic applications. Moreover, the paper takes a closer look at the costs of electricity production from these systems in relation to the feed-in tariffs issued in Vietnam. The results show that the gap between the levelized cost of electricity and the feed-in tariff for solar photovoltaic electricity is relatively high, particularly in regions with a lower irradiation potential.

Data play an essential role in the optimal control of smart buildings’ operation, especially in building energy-management for the target of nearly zero buildings. The building monitoring system is in charge of collecting and managing building data. However, device imperfections and failures of the monitoring system are likely to produce low-quality data, such as data loss and inconsistent data, which then seriously affect the control quality of the buildings. This paper proposes a new approach based on Gaussian process regression for data-quality monitoring and sensor network data compensation in smart buildings. The proposed method is proven to effectively detect and compensate for low-quality data thanks to the application of data analysis to the energy management monitoring system of a building model in Viet Nam. The research results provide a good opportunity to improve the efficiency of building energy-management systems and support the development of low-cost smart buildings.

Renewable electricity for off-grid areas is widely seen as one of the top choices in supporting local economic development in most countries, and so is Vietnam. Over the years, many isolated networks using renewable energy sources have been deployed for off-grid areas in Vietnam. However, the use of these energy sources in Vietnam’s isolated networks is still facing many challenges due to its infancy here. The issues of reliability and vulnerability of these networks are not given the expected attention. Another challenge is that the issues of the operational security of these systems could also be negatively affected by the variable nature of renewable sources, including static and dynamic security. For this reason, this study aims to contribute to a better understanding of integrating renewable energy into isolated networks, and in this case, using solar power for the An-Binh Island grid in Vietnam. The findings from this study suggest that choosing the right structure of the power mix could contribute to improving the operational security of isolated networks. Moreover, several solutions to enhance the reliability of this grid are also proposed. The NEPLAN environment was selected for simulation and analysis for all the scenarios in this study.

With the average solar radiation reaching up to 5 kWh/m2, Vietnam is considered as a country showing an excellent potential for solar power production. Since the year 2000, there have been a lot of studies about the potential of this source in Vietnam. So far, many applications of solar power have been implemented on small, medium, and large scales. In fact, the total capacity of current grid-connected solar power plants has exceeded the planned capacity by 2020 nearly 6 times. However, the studies of solar potential in Vietnam are still incomplete. The policies and mechanisms for developing solar power projects have received attention from the authorities but have not been really satisfactory. The infrastructure is still poor and the power system does not keep up with the development of modern grids. This paper reviewed the potential and actual implementation stage of photovoltaic projects in Vietnam. Moreover, the barriers and challenges of institution, technique, economy, and finance have been considered explicitly for the future development of solar energy in Vietnam.