Power flow analysis in a distributed network for a smart grid system

Abstract

This article presents the implementation of a hybrid renewable energy-based smart grid in a distributed system. Photovoltaic (PV) and wind generation are variable and time-dependent, yet they are very efficient and correlated, making them perfect for a two-source hybrid system. To maximize the generated power, using the maximum power point tracker (MPPT) technique, the incremental conductance (IC) algorithm is employed. The proportional integral (PI)-based MPPT controller is chosen to improve the efficiency of conventional MPPT controllers. A battery system is implemented as an energy management system (EMS) to aid in transferring or managing the high load throughout peak and off-peak hours. The proposed system uses an optimization technique called genetic algorithm (GA) to control the inverter voltage. The GA-tuned PI controller performs efficiently and has less harmonic distortion than the traditional sinusoidal pulse width modulation (SPWM) control method. The designed system uses real-time measurable parameters as inputs and is simulated in Matlabtool. The system generates 42 kW of solar power and 250 kW of wind power; the total harmonic distortion (THD) value is 5% less than the SPWM technique. For future work, flexible alternating current transmission system (FACTS) devices can improve the power quality and lower the oscillations.