This thesis deals with quantifying the merits of Distributed Maximum Power Point Tracking (DMPPT), as well as providing solutions to achieve DMPPT in PV systems. A general method based on 3D modeling is developed to determine the energy yield of PV installations exploiting different levels of DMPPT granularity. Sub-string-level DMPPT is shown to have up to 30% more annual energy yield than panel-level DMPPT. A Multi-Input-Single-Output (MISO) dc-dc converter is proposed to achieve DMPPT in parallel-connected applications. A digital current-mode controller is used to operate the MISO converter in pseudo-CCM mode. For series-connected applications, the virtualparallel concept is introduced to utilize the robustness of the parallel connection. This concept is demonstrated on a three-phase boost converter. The topology offers reduced output voltage ripple under shading which increases the life-time of the output capacitor. The prototypes yield output power benefits of up to 46% and 20% for the tested shading conditions.

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

This thesis deals with quantifying the merits of Distributed Maximum Power Point Tracking (DMPPT), as well as providing solutions to achieve DMPPT in PV systems. A general method based on 3D modeling is developed to determine the energy yield of PV installations exploiting different levels of DMPPT granularity. Sub-string-level DMPPT is shown to have up to 30% more annual energy yield than panel-level DMPPT. A Multi-Input-Single-Output (MISO) dc-dc converter is proposed to achieve DMPPT in parallel-connected applications. A digital current-mode controller is used to operate the MISO converter in pseudo-CCM mode. For series-connected applications, the virtualparallel concept is introduced to utilize the robustness of the parallel connection. This concept is demonstrated on a three-phase boost converter. The topology offers reduced output voltage ripple under shading which increases the life-time of the output capacitor. The prototypes yield output power benefits of up to 46% and 20% for the tested shading conditions.