author = {Yanzhi Wang and Xue Lin and Massoud Pedram and Jaemin Kim and Naehyuck Chang},

title = {Capital Cost-Aware Design and Partial Shading-Aware Architecture Optimization of a Reconfigurable Photovoltaic System},

booktitle = {Proceedings of Proceedings of Design Automation and Test in Europe (DATE)},

year = {2013},

pages  = {909-912},

location = {Grenoble, France},

month = {March},

note = {},

abstract = {Photovoltaic (PV) systems are often subject to partial

shading that significantly degrades the output power of the whole systems. Reconfiguration methods have been proposed to adaptively change the PV panel configuration according to the current partial shading pattern. The reconfigurable PV panel architecture integrates every PV cell with three programmable switches to facilitate the PV panel reconfiguration. The additional switches, however, increase the capital cost of the PV system. In this paper, we group a number of PV cells into a PV macro-cell, and the PV panel reconfiguration only changes the connections between adjacent PV macro-cells. The size and internal structure (i.e., the series-parallel connection of PV cells) of all PV macro-cells are the same and will not be changed after PV system installation in the field. Determining the optimal size of the PV macro-cell is the result of a trade-off between the decreased PV system capital cost and enhanced PV system performance. A larger PV macro-cell reduces the cost overhead whereas a smaller PV macro-cell achieves better performance. In this paper, we set out to calculate the optimal size of the PV macro-cells such that the maximum system performance can be achieved subject to an overall system cost limitation. This "design" problem is solved using an efficient search algorithm. In addition, we provide for in-field reconfigurability of the PV panel by enabling formation of series- connected groups of parallel-connected macro-cells. We ensure maximum output power for the PV system in response to any incurring partial shading pattern. This "architecture optimization" problem is solved using dynamic programming.},

keywords = {},