An improved maximum power point tracking control approach for photovoltaic systems based on model predictive control with a condition-triggered strategy

Abstract

This article proposes a novel maximum power point tracking control approach which is based on model predictive control theory with a condition-triggered strategy. First, because the matching of the external impedance and the internal impedance of the photovoltaic system can provide the maximum power output of solar cell, dynamic impedance matching method is used to adjust the external impedance of the system. Then, the model predictive control method is used to calculate the duty ratio of the boost circuit to force the external impedance to approach the internal impedance based on the definition of cost function. In order to deal with the problems on computational complexity of model predictive control for the online implementation demand, a condition-triggered strategy is proposed to reduce the burden of computation during control process. According to the requirement of control performance, the triggered condition is designed based on the difference between external impedance and internal impedance together with the difference of the state variable between the variable and its first derivative. Thereafter, the stability of model predictive control system with condition-triggered strategy is also discussed. The discussion shows that the implementation of triggered strategy cannot change the stability of original model predictive control system. Finally, an example of photovoltaic system is discussed. The simulation shows that the operation time will be reduced obviously with the guaranteed performance under the condition-triggered strategy, and the result also verifies the feasibility and effectiveness of the strategy proposed in this article.