Modelling and analysis of PV/wind system for power generation with dynamic input datasets

Increasing world population and industrial activities are rapidly consuming the energy resources of the world which are restricted in recent years so renewable energy sources have gained great importance. The wind power plants which is eco-friendly and clean renewable energy source are growing faster than other renewable energy sources because of lower installation cost and positive developments in turbine technology. It is necessary to have necessary and adequate controls and regulations otherwise this rapid increase cause network imbalance and uncertainty. In this thesis, Fuzzy neural network approach is used to estimate the generation of wind turbines. The power system with wind power plant and solar power plant is modelled in PSCAD/EMTDC. In case studies, a fuzzy neural network is applied to estimate PMSG based and DFIG based wind turbines power generation in MATLAB program and after applied load in the system the changes in active and reactive power are observed.