Photovoltaic (PV) is a highly promising energy source because of its environment friendly property. However, there is an uncertainty present in the modeling of PV modules owing to varying irradiance and temperature. To solve such uncertainty, the fuzzy logic control-based intelligent maximum power point tracking (MPPT) method is observed to be more suitable as compared with conventional algorithms in PV systems. In this paper, an isolated PV system using a push pull converter with the fuzzy logic-based MPPT algorithm is presented. The proposed methodology optimizes the output power of PV modules and achieves isolation with high DC gain. The DC gain is inverted into a single phase AC through a closed loop fuzzy logic inverter with a low pass filter to reduce the total harmonic distortion (THD). Dynamic simulations are developed in Matlab/Simulink by MathWorks under linear loads. The results show that the fuzzy logic algorithms of the proposed system efficiently track the MPPT and present reduced THD.
In recent years, the integration of renewable energy resources (RESs) into the power system is growing rapidly, and it is necessary to analyse and evaluate the effect of RES on transient stability of the power system. In this study, centre of inertia (COI) concept is implemented to analyse and evaluate the integration effects of an auxiliary damping control-based virtual synchronous generator (VSG) consisting an improved governor. The impact of VSG integration is divided into synchronous generator (SG) linked parts and COI associated parts. Due to VSG integration into the power system, the significant elements which disturb the COI dynamic motion and rotor dynamics of SG are examined in detail. Different cases are considered to evaluate the effectiveness of the proposed method, i.e. VSG's different integrating location and different power capacities. It is observed in simulation results that COI dynamic motion and rotor dynamics of SG are positively affected by VSG integration, and transient stability improves significantly.
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