Publication

Abstract : In this paper, an application of intelligent non-linear discrete proportional-integral-derivative (N-DPID) controller for the maximum power point tracking (MPPT) of a photovoltaic (PV) system is presented. The proposed N-DPID MPPT method retains the conventional properties of the basic PID controller where the integral and derivative terms are discretized using Forward Euler formula and, its integral gain is varied over the simulation time according to the error. To obtain the value of controller gains is a challenge for N-DPID controllers. An intelligent technique using Particle swarm optimization (PSO) and genetic algorithm (GA) may help in finding out the gains in a dynamic situation. These optimization techniques are analyzed for proposed N-DPID MPPT to track the MPP. Performance analysis and comparison of the GA and PSO tuned N-DPID MPPT method is presented for a commercially available PV module SunPower SPR-305E-WHT-D. Furthermore, the performance is also analyzed for the smooth operation of a wound field DC (WFDC) motor fed by a PV array. Finally, results for MPPT and WFDC motor operation are compared for P&O, IC, GA-PID, GA-N-DPID, PSO-PID, and PSO-N-DPID MPPT methods.