Power Quality Enhancement in the Integration of Distributed Generation using Particle Swarm Optimization

Electrical energy is vital to the sustainability and quality of life on earth. Photovoltaic (PV) and wind energy are considered as the most efficient renewable energy technologies. Greenhouse gas emissions can be reduced with the proper usage of solar energy. In this research, a hybrid distributed generation of solar and wind energy is presented using Matlab software. Wind and solar power are two examples of renewable energy which have experienced a recent increase in synthesis due to environmental, social, and technical advantages over fossil fuel-based power generation. The most promising and well-established renewable energy technologies are solar and wind energy. This paper uses MATLAB software to analyze load flow analysis, short circuit analysis, and also the real and reactive power compensation. It presents a particle swarm optimization technique for performing harmonic suppression in distribution system along with nonlinear load. Transmission loss, fuel costs, and transmission line stability are reduced by using particle swarm optimization. In the MATLAB software, the models and simulations for a practical distributed grid is used for the construction and for validating the proposed system's design validity. To make the simulation models more realistic, real load and hybrid energy data is used. The outcome of the proposed analysis is used to display the output as a waveform and this has been discussed throughout this paper.