Power control strategy of an integrated PV system for active power reserve under dynamic operating conditions

In recent years, the increase in the amount of photovoltaic penetration in the grid has caused a serious threat to the inertia of the power system. The situation has dictated to look for methods to enable the inertial capabilities in the PV systems. One of the most explored methods to enable this capability is to generate an active power reserve by deloading the PV. The deloading methods work well for constant operating conditions, but for dynamic conditions, the monitoring of MPP and tuning of the reserve become a challenging situation. In this paper, a novel deloading based power control strategy for dc/dc converter is proposed, in which, the MPP is monitored by an artificial neural network based estimator and reserve is adjusted using a fuzzy reserve controller. The suitability of the adopted reserve control approach is justified by comparing the proposed control with the mainstream reserve approaches. The working of the developed controls is validated by the help of simulations and experimental results.

Automated summary

The paper proposes a novel deloading-based power control strategy for a dc/dc converter, monitoring MPP using an artificial neural network and adjusting reserve using a fuzzy reserve controller. The suitability of this approach is justified by comparing it with mainstream reserve approaches. The effectiveness of the developed controls is validated through simulations and experimental results.