Intelligent SMES based on Flower Pollination Algorithm on Wind Power System for Dynamic Stability Enhancement

Integration of large-scale wind power plant (WPP) in transmission level is becoming reality due to reduce dependency on fossil fuels resources. Although, WPP could provide clean and sustainable energy, they also contributein instability of power system especially on small signal stability due to uncertainty of the power output. Hence,utilizing additional devices such as energy storage can be considered to handle the uncertainty power output of WPP.This paper proposes an application of superconducting magnetic energy storage (SMES) as an additional device toprovide a better damping of frequency oscillation and enhance the small signal stability performance of a power systemaffected by integrating of large-scale WPP. To get better performance, the parameters of SMES are automaticallyadjusted by using flower pollination algorithm (FPA). Eigenvalue, damping performance and time domain simulationare investigated to analyze the robustness and successfulness of the proposed method. From the simulation result, it isfound that the proposed method (adding SMES on WPP using FPA) can enhance the small signal stability performanceof the system. It is indicated by the TKE value of the proposed method is the smallest compared to the other scenarios(0.000017)