Name
Abstract | ||
|---|---|---|
Shading is a crucial issue for the placement of PV installations, as it heavily impacts power production and the corresponding return of investment. Nonetheless, residential rooftop installations still rely on rule-of-thumb criteria and on gross estimates of the shading patterns, while more optimized approaches focus solely on the identification of suitable surfaces (e.g., roofs) in a larger geographic area (e.g., city or district). This work addresses the challenge of identifying an optimal (with respect to the overall energy production) placement of PV panels on a roof. The novel aspect of the proposed solution lies in the possibility of having a sparse, irregular placement of individual modules so as to better exploit the variance of solar data. The latter are represented in terms of the distribution of irradiance and temperature values over the roof, as elaborated from historical traces and Geographical Information System (GIS) data. Experimental results will prove the effectiveness of the algorithm through three real world case studies, and that the generated optimal solutions allow to increase power production by up to 28% with respect to rule-of-thumb solutions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.23919/DATE.2018.8342049 | 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE) |
Keywords | Field | DocType |
residential installations,PV installations,power production,residential rooftop installations,rule-of-thumb criteria,gross estimates,shading patterns,optimized approaches,larger geographic area,energy production,PV panels,sparse placement,irregular placement,individual modules,solar data,irradiance,temperature values,Geographical Information System data,generated optimal solutions,rule-of-thumb solutions,GIS-based optimal photovoltaic panel floorplanning | Geographic information system,Renewable energy,Return on investment,Industrial engineering,Computer science,Solar energy,Exploit,Real-time computing,Roof,Photovoltaic system,Floorplan | Conference |
ISSN | Citations | PageRank |
1530-1591 | 1 | 0.40 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sara Vinco | 1 | 24 | 8.59 |
| Lorenzo Bottaccioli | 2 | 13 | 6.34 |
| Edoardo Patti | 3 | 63 | 17.17 |
| A. Acquaviva | 4 | 46 | 5.13 |
| Enrico Macii | 5 | 2405 | 349.96 |
| Massimo Poncino | 6 | 125 | 18.57 |