Affiliations: Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran | Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran
Note: [] Corresponding author. Elham Ganji, Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran. Tel./Fax: +989366922343; E-mail: [email protected]
Abstract: This paper makes uses of an intelligent framework based on improved fuzzy particle swarm optimization (IFPSO) algorithm to control the desired frequency of the power grid for stand-alone application. In this regard, a new schematic of an isolated hybrid energy system combining Wind Turbine (WT), Fuel Cell (FC) and Ultra Capacitor (UC) using nonlinear detailed models has been presented. In this system, the WT is used as the main power generation source. Fuel cell and Ultra Capacitor are introduced as a backup energy source and buffer storage to supply the load demand for all various operating conditions. In the proposed system, in order to use the grid's capability to its best, the second order sliding (SOSMC) mode strategy is employed to extract the maximum power from wind in the below the rated wind speed. In this part, to validate the performance and capabilities of the proposed MPPT strategy, a comparison with the classical ATF controller was performed using Matlab/Simulink. Moreover, to demonstrate the effectiveness of IFPSO algorithm, optimal droop frequency controller using IFPSO algorithm is compared with conventional and improved droop controllers. According to the simulation results, applying proposed method, the frequency deviation of the isolated power grid in dynamical state declines significantly.
Keywords: Isolated hybrid system, frequency control, dynamic modelling, maximum power point tracking (MPPT), Second Order Sliding Mode Controller (SOSMC), improved fuzzy particle swarm optimization (IFPSO), improved droop control
