Automated Planning of Rooftop PV Systems with Aerial Image Processing

The increasing prevalence of photovoltaic (PV) panels for microgrid and off-grid energy applications makes affordable PV planning an important issue. Since recording rooftop area and dimensions traditionally required on-site measurements, the process was expensive, slow, and hard to scale. This research develops software that uses image processing for roof detection. Satellite images feed into the software, which estimates the rooftop area receiving solar exposure in that area as well as the number of individual buildings receiving solar exposure. In this way, entire villages can be analyzed automatically, and PV installations planned from afar, rather than requiring a human taking measurements of each building from the ground. This research further develops a GUI to accomplish this rooftop classification for users around the globe, making this capability available even to parties with low resources who would benefit from access to electricity. In this way, the study makes planning PV systems feasible and affordable for many scales of installation, from a single home to a city of numerous assorted buildings.

[1]  D. Zaum,et al.  ROBUST BUILDING DETECTION IN AERIAL IMAGES , 2005 .

[2]  Taha Selim Ustun,et al.  Differential protection of microgrids with central protection unit support , 2013, IEEE 2013 Tencon - Spring.

[3]  Taha Selim Ustun,et al.  Smart microgrid operation simulator for management and electrification planning , 2016, 2016 IEEE PES PowerAfrica.

[4]  Yassine Ruichek,et al.  Building Roof Segmentation from Aerial Images Using a Line-and Region-Based Watershed Segmentation Technique , 2015, Sensors.

[5]  Acakpovi Amevi.  PERFORMANCE ANALYSIS OF PARTICLE SWARM OPTIMIZATION APPROACH FOR OPTIMIZING ELECTRICITY COST FROM A HYBRID SOLAR, WIND AND HYDROPOWER PLANT , 2016 .

[6]  Taha Selim Ustun,et al.  Scaling renewable energy based microgrids in underserved communities: Latin America, South Asia, and Sub-Saharan Africa , 2016, 2016 IEEE PES PowerAfrica.

[7]  Taha Selim Ustun,et al.  Novel business models and policy directions based on SE4ALL global framework for minigrids , 2016, 2016 IEEE International Conference on Emerging Technologies and Innovative Business Practices for the Transformation of Societies (EmergiTech).

[8]  Taha Selim Ustun.  Computer-based Decision Making Systems for Improved Energy Access in Sub-Saharan Africa , 2016 .

[9]  Taha Selim Ustun,et al.  Composition, placement, and economics of rural microgrids for ensuring sustainable development , 2018 .

[10]  Taha Selim Ustun,et al.  The case for microgrids in electrifying Sub-Saharan Africa , 2015, IREC2015 The Sixth International Renewable Energy Congress.

[11]  Arnold W. M. Smeulders,et al.  Color Based Object Recognition , 1997, ICIAP.

[12]  Taha Selim Ustun,et al.  The role of microgrids & renewable energy in addressing Sub-Saharan Africa's current and future energy needs , 2015, IREC2015 The Sixth International Renewable Energy Congress.

[13]  S. Karekezi,et al.  Renewable energy strategies for rural Africa: is a PV-led renewable energy strategy the right approach for providing modern energy to the rural poor of sub-Saharan Africa? , 2002 .