Integration of power optimizers in photovoltaic systems is standard practice in some parts of the world. Manufacturers claim that optimizers can significantly reduce electrical losses due to shading. Hence, it is important to investigate this claim and determine under what conditions it is economically warranted to utilize optimizers. In this thesis systems were modelled in PVSyst, for 6 different locations: Abu Dhabi, Borlänge, Madrid, New Delhi, Sydney, and Vienna. In each location there were 3 types of systems: a regular non-optimised system, a SolarEdge optimised system and a TIGO optimised system. Each of these systems had 10 variants where the amount of shading was varied. The system variants were simulated in PVSyst and the effect of power optimizers on electrical losses due to shading was analysed. Afterwards, payback periods were calculated for each system to determine under which conditions power optimizers are economically feasible. It was found that power optimizers significantly reduce electrical losses due to shading. In some scenarios, the losses were reduced by up to 58 %. However, in the current economic climate in 2018, it is not feasible to incorporate power optimizers, in photovoltaic systems in Abu Dhabi, New Delhi or Sydney. Furthermore, in Borlänge, Madrid, and Vienna, optimizers are only feasible if there are high levels of shading, which is not realistic for a regular photovoltaic system.

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.