Fractional Order PID Design Using Big Bang-Big Crunch Algorithm and Order Reduction: Application to Load Frequency Control

A new technique for tuning a fractional order proportional integral derivative (FOPID) controller is presented and analyzed for load frequency control of power systems. The proposed technique involves model order reduction for model simplification, internal model control for initial estimation of PID gains to formulate a compact solution space required for big bang-big crunch (BB-BC) algorithm, which ascertains optimal FOPID parameters in the search space delineated via IMC technique. The beauty of the proposed approach is that it gives an innovative way to incorporate soft computing algorithms in control applications in such a manner that leads to reduction in randomness associated with heuristic techniques. To validate the effectiveness of the proposed scheme, it is implemented on a power system comprising of reheated turbine and a realistic model of IEEE 10 machine 39 bus New England system in presence of nonlinearities. A comprehensive comparative analysis with other recent controller design techniques, conducted in terms of simulation plots, performance indices and statistical parameters is a testimony to efficacy of proposed technique.

Automated summary

This study presents a new technique for tuning FOPID controllers for load frequency control, involving model simplification and internal model control for optimal parameter estimation. Compared to heuristic techniques, the proposed approach incorporates soft computing algorithms in control applications, reducing randomness.