Fuzzy Logic Based Module-Level Power Electronics for Mitigation of Rapid Cloud Shading in Photovoltaic Systems

Abstract

A module-level DC optimization proof of concept architecture is proposed to increase the efficiency of photovoltaic (PV) strings by minimizing the negative effects of shading caused by intermittent cloud cover while reducing cloud induced fast frequency fluctuations. The decentralized inverter approach combines the benefits of string and micro-inverter technology. This device can be affixed to pre-existing or new systems and operates in compliance with IEEE 1547 and California rule 21 standards by operating in maximum power point tracking (MPPT) or curtailment mode whenever necessary. The modular level device encapsulates three individual processes: an optimization engine to determine minimum power requirements, a fuzzy logic controller (FLC) to eliminate the effect of passing cloud cover, and a voltage regulation stage to monitor and appropriately adjust the output voltage of the device. Ramp rate reduction was accomplished using adaptive fuzzy logic control with a heuristic rule base inference engine. The modular design can be affixed to grid connected or islanded systems allowing for operation in regulated and variable load conditions. Matlab/Simulink 2019a was used to design and simulate the proof of concept model to verify the resiliency to partial shading, reduction of ramp rates during passing cloud coverage, and optimal output voltage for each panel while maintaining a constant DC link voltage of 120 V. This proof of concept has been successfully validated therefore further testing will be performed for various irradiance conditions.