Identifying Potential Area and Financial Prospects of Rooftop Solar Photovoltaics (PV)

Sarawut Ninsawat,Mohammad Hossain

doi:10.3390/su8101068

Abstract

In an urban area, the roof is the only available surface that can be utilized for installing solar photovoltaics (PV), and the active surface area depends on the type of roof. Shadows on a solar panel can be caused by nearby tall buildings, construction materials such as water tanks, or the roof configuration itself. The azimuth angle of the sun varies, based on the season and the time of day. Therefore, the simulation of shadow for one or two days or using the rule of thumb may not be sufficient to evaluate shadow effects on solar panels throughout the year. In this paper, a methodology for estimating the solar potential of solar PV on rooftops is presented, which is particularly applicable to urban areas. The objective of this method is to assess how roof type and shadow play a role in potentiality and financial benefit. The method starts with roof type extraction from high-resolution satellite imagery, using Object Base Image Analysis (OBIA), the generation of a 3D structure from height data and roof type, the simulation of shadow throughout the year, and the identification of potential and financial prospects. Based on the results obtained, the system seems to be adequate for calculating the financial benefits of solar PV to a very fine scale. The payback period varied from 7–13 years depending on the roof type, direction, and shadow impact. Based on the potentiality, a homeowner can make a profit of up to 200%. This method could help homeowners to identify potential roof area and economic interest.

Highlights

A major concern regarding fossil fuel is that it creates environmental effects along with contributing to global warming [1]
In contrast to fossil fuels, renewable energy can be utilized as a remedy for solving the global warming problem
Thailand is geographically appropriate for utilizing solar energy, and this is less so for other renewable energy sources, such as hydroelectric power or wind [3]

Summary

Introduction

A major concern regarding fossil fuel is that it creates environmental effects along with contributing to global warming [1]. Researchers used LiDAR technology for detecting city buildings [27], trees, and roof structures [28], identifying the potential solar radiation of built areas [29] and even for solar mapping [30]. This technology is expensive and requires extensive infrastructure and expertise [31]. Shadowing effects due to tree leafs lead to non-negligible power losses of solar PV modules [32] and reduce efficiency [33] This analysis is missing in the recently introduced Google Sunroof project (https://www.google.com/get/sunroof#p=0).

Data Preparation

Analysis

Results and Discussion

Conclusions