Design of PID Controller with Grid Connected Hybrid Renewable Energy System Using Optimization Algorithms

The main target of this paper is to allow renewable energy resources (RES) to participate effectively within hybrid micro grids via an optimal proportional integral- derivative (PID) controller. This paper proposes two techniques of optimal PID controllers in a hybrid renewable generation energy system. These techniques are particle swarm optimization (PSO) and lightning attachment procedure optimization (LAPO). The hybrid renewable generation energy system in this study includes a photovoltaic source, wind turbine, and battery storage, which are connected to a point of common coupling via DC/DC boost converters. The controller at the inverter consists of a current controller and voltage source controller, which results in three PID gains at each controller. In order to obtain the PID gains, a time domain objective function is formulated in terms of the voltage, and current errors. The obtained results with the individual advanced optimization LAPO and PSO algorithm are compared. The results display that the developed LAPO algorithms give better results compared to the conventional PSO at the input and output current, voltage, and power. All the results have been taken under several operating conditions of wind turbine (wind speed) and solar sun (changing irradiance and temperature).

Automated summary

This paper aims to enable renewable energy resources to effectively participate in hybrid micro grids via an optimal PID controller. It proposes two techniques for optimal PID controllers in a hybrid renewable generation energy system, comparing the results of LAPO and PSO algorithms. LAPO algorithm outperforms PSO in terms of input and output current, voltage, and power.