Optimized Fractional order Controllers for Solar Wind Hybrid Generating Systems

Abstract

The two most popular types of renewable energy are solar and wind.Although they offer tremendous potential,renewable energy sources like solar and wind are quite unpredictable. It is therefore risky to design a renewable energy system that is dependent on a single resource. Solar and wind are complementary energy sources. These two resources can be used to develop a Hybrid Generating System (HGS) that is extremely reliable. The primary feature of hybrid generating systems is that they combine two or more renewable power generation technologies to maximize their operating characteristics and attain efficiency levels that are superior to those possible with a single power source. The drawback of these renewable energy sources is that they are highly dependent on environmental conditions, which causes their output profiles to fluctuate significantly. This research investigates the potential of fractional order controllers for grid-connected and isolated HGS. An efficient Fractional Order PID (FOPID) controller for isolated HGS with a power management control has been developed in the initial phase of this research work. A hybrid k-means Grasshopper Optimization Algorithm (k-GOA) is used to optimize the proposed FOPID controller. The recommended hybrid k-GOA technique avoids random initialization in GOA, which results in a faster convergence rate for the best solution. A suitable power management control algorithm was also satisfactorily included in the proposed solar-wind HGS. The Robust Disturbance Observer (RDO) based fractional order PID controller for grid connected solar-wind HGS is proposed in the second phase of the work. A novel robust disturbance observer has been developed for a grid-connected HGS to precisely estimate the disturbances caused by stochastic variations in climatic conditions, external disturbances, grid side fluctuations, unmodeled nonlinearities, and other parametric variations. The RDO based FOPID controller parameters are then optimally tuned by k-GOA. The Photovoltaic (PV)- FOPID, Wind..