FAΘPSO based fuzzy controller to enhance LVRT capability of DFIG with dynamic references

With increasing demand for energy, there is a growing tendency to employ renewable sources such as wind energy. Using large amounts of energy from wind arouses critical issues such as voltage variation and poor quality power supply. Several papers have been published on suggestions to improve performance of wind turbines during grid fault; however, to the authors´ knowledge only a few papers address this problem with dynamic references. This paper presents the fuzzy adaptive theta particle swarm optimization (FAΘPSO)-based fuzzy controller applied to a doubly fed induction generator (DFIG) to operate at medium voltage. The proposed method attempted to determine required reactive power reference and active power amplification factors based on recommendations presented by the German Transmission Code 2007 and capability limits of the DFIG. Optimum values of membership functions were obtained by utilizing an FAΘPSO algorithm. This method improves voltage profile at the first instant besides during the grid fault. Moreover, aforementioned method also acts as an additional controller that could emerge with different inner controllers in the DFIG.