Design and control of Takagi-Sugeno-Kang fuzzy based inverter for power quality improvement in grid-tied PV systems

Abstract

The addition of solar photovoltaic energy penetration to the electric grid is widely increasing across the world due to the many advantages such as clean energy source, easy to install and improved performance of power converters for the grid synchronization, and so on. Instead of many stages taking place for the grid-tied, a single stage is preferable to avoid the greater number of power electronic converters connected in the system which in turn reduce the cost of the overall system. In general, the DC-to-DC converters are used in the PV systems to track the maximum power point. However, an inverter circuit is needed to synchronize the source to grid and it can be utilized to extract maximum power from PV systems through proper controlling techniques. The proper control of inverter avoids the DC-to-DC power converter usage for the maximum power point tracking purpose. On the other hand, this technology can be used for small scale solar power plants. An irregular irradiance of solar is a bottleneck for the solar systems and to overcome it, a Takagi-Sugeno-Kang Fuzzy (TSKF) controller is designed for controlling the inverter operation in this paper. The TSKF controller responds very quickly to the input rapid changes of solar irradiance than the conventional proportional integral controllers. In this paper, a single stage 1 MW rating solar PV grid system is designed and verified the performance of the proposed controller under different loading conditions. Further, the proposed system is loaded with local loads and their reactive compensation is evaluated through hardware-in-loop on the platform of OPAL-RT software.

Keywords

• Photovoltaic
• Takagi-Sugeno-Kang fuzzy (TSKF) controller
• Maximum power point tracking (MPPT)
• Inverter control
• Grid-tied