MPPT for Photovoltaic System Using Adaptive Fuzzy Backstepping Sliding Mode Control

Abstract

This paper presents an intelligent monitoring control strategy for a maximum power point tracking (MPPT) in photovoltaic (PV) system applications. The design of the proposed nonlinear adaptive control law (AFBSMC) is formulated based on adaptive fuzzy systems, backstepping approach and sliding mode technique to maximize the power output of a PV system under various sets of conditions and parameters variation. Unlike many conventional controllers, the main contribution of the present paper provides a soften control law which useful to handle parameters variations due to the different operating conditions occurring on the PV system and makes the controller easy to implement. This aim is achieved using fuzzy systems in an adaptive scheme to approximate the switching control function of the global control law while backstepping sliding mode control compensates uncertainties and external disturbances. The analytical stability proof of the closed-loop system is corroborated via Lyapunov synthesis while numerical simulations of different operating conditions of a PV system is conducted to validate the effectiveness of the proposed approach.

PV Distribution Network Planning Method Considering the Cost and Effectiveness of Voltage Control

“…As the PV power generation system operates grid-connected through inverters [4], the power electronics are frequently switched on and off, which easily causes harmonic pollution to the power network. At the same time, environmental elements like temperature and sunshine intensity have a substantial impact on the output of the PV power generation system [5], which easily causes voltage fluctuations in the grid-connected network.…”