Nguyen Dinh Quang's scientific contributions

The demand for electrical energy is increasing in Vietnam in recent decades; which has motivated the use of renewable energy sources (RES). Among them, Photovoltaic (PV) energy is becoming a promising energy source because of their advantages. The connection and use of PV in distribution grid in Vietnam should be in line with the framework of sustainable energy development worldwide. The different techniques of modeling and control of grid connected PV system with the objective to help intensive penetration of PV electricity into grid have been proposed so far in different literatures. The current methodologies for optimizing of generation power of PV system are not completely efficient. Therefore many researches are required for overall configuration of the grid connected PV system, the Maximum Power Point Tracking algorithm, the synchronization of the inverter. This paper presents a control technique of the PV generation power by shift of phase angle of the inverter output voltage and grid voltage. In order to synchronize an alternating current output of the PV system’s inverter into the grid, the proposed method has been described, simulated in MATLAB/Simulink. The work helps to give study results about interconnection standard, power generation optimization method of PV system into power grid

In building energy management, the electrical storage is important to ensure power supply continuity and reduce the cost of electrical consumption. Therefore, an electrochemical battery model is highly recommended for our main objectives, which can contribute to simulate the impact of electrical storage in the building. In our framework, we have developed a complete solution for the electrical optimal management, including prediction, optimization, and real-time management of an electrical storage system with photovoltaic generation. We first present the models required to predict consumption patterns, production, and storage. Then, under our experimental platform, we detail the predictive control algorithm, monitoring solutions and equipment control, as well as the results obtained. In near future, this research will be applied for the “Micro Smart Grid Development and Application for Building Energy Management” project (USTH, HIT, G2Elab and VAST).