Abstract
This paper presents an improved stator flux oriented (SFO) control system for a stand-alone induction generator. The induction generator supplies a variable resistive dc load. In order to provide an essentially constant terminal voltage, the product of the rotor speed and the stator flux reference should remain constant. However, in this case the control system is not able to function properly at different loads and dc-link voltages. In this paper, we introduce a new algorithm in which this product is constant at certain dc-load and dc-link voltage references. The dependence of the stator flux reference on the dc load and dc voltage reference is mapped using an artificial neural network (ANN). We also present an analysis of the efficiency of the SFO control system, as well as its performance during transients, over a wide range of both dc-link voltage references and loads. The validity of the proposed approach is verified by realistic simulation in a Matlab–Simulink environment.
Dinko Vukadinović
Full Professor | Department of Power Electronics and Control
Full professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, specialized in modern control systems for power electronic converters, electric motors, and generators. At the Power Electronics Research Laboratory, he leads experimental projects and develops advanced methods for regulating electrical machines and converters, while supervising doctoral research in these areas.
Mateo Bašić
Full Professor | Department of Power Electronics and Control
Full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split, with recent research interests related to the fields of power electronics and renewable energy sources, with a special focus on energy-efficient control of inverters, battery systems, wind turbines, photovoltaic sources and self-excited induction generators in microgrids - both in island operation and in grid-tie operation.