A Smart Grid Wireless Neuro-fuzzy Power Control For Wind Energy Systems

The wind energy generation is the huge driver behind the push for supergrids and cross-border infrastructure for renewable energy systems. To improve the energy system and reduce deployment costs, the wireless communications can arise as a powerful tool in this new scenario. However, the wireless technology for transmitting control information to wind generator requires special attention to avoid any damage to the generator and to the energetic plant caused by transmission errors. In this context, this work proposes a wireless coded power control system for variable speed wind doubly-fed induction generators. The proposed controller is based on the adaptive neuro-fuzzy inference system and it uses the vector control technique to independently control the active and reactive power. The wireless communication system employs QPSK digital modulation and LDPC coding scheme to reduce the transmission errors and the overall system latency. In addition, it is presented its feasibility analysis and impact to the overall system by investigating the control performance in operational conditions at AWGN and flat fading propagation channels.