512 / 2019-02-28 17:29:46

Assessment of Solar Road Capacity to Power Electronic Vehicles – A New Method to Calculate Road Solar Radiation with Street View

Solar road; Street View; Urban Planning

全体主题 > Big data in Urban Planning and Management

Introduction
A sustainable city relies on renewable energy, which promotes the development of electric vehicles [1]. To support electric vehicles, the concept of charging vehicles while driving has been put forward [2]. Under such a circumstance, constructing solar panels on urban roads is an innovative option with great benefits. Some countries and regions in the world have already made efforts to pave photovoltaic roads. For example, as early in 2014, in Amsterdam, a 70-meter bike path was replaced by solar panels and had generated 3000 kWh in just half a year after its construction [3]. However, solar panels acted as road construction material requires advanced technology support and high cost [4, 5]. Such a limitation implies the accurate calculation of road photovoltaic power generation is a prerequisite while it’s hard to find any work related to the assessment of road photovoltaic capacity yet.
In this paper, we propose a novel framework for predicting and calculating the solar radiation and electric energy that can be collected from the roads based on street view images.
Methodology
This research consists of the following three steps (Fig. 1):

Fig. 1 The Flow Chart of the Method
Fist, we collected Google Street View photos and adopted PTGui software to stitch images forming hemispherical images to measure the sky obstruction of roads. To recognize sky area, we applied the mean shift algorithm [6] to extract sky pixels based on Brightness [7].
Second, the resulting pictures with sky section marked is coupled with the solar radiation model improved from Solar Analyst [8] to estimate the net solar radiation received by the empty road.
Considering traffic conditions might impact the solar generation as sky is obstructed by vehicles, we also take traffic conditions and weather situations in the calculation. By utilizing traffic flow model [9], roads’ traffic conditions are simulated by road real-time observation speed obtained from TomTom traffic online.
In order to test the feasibility of our framework, we take Boston as a case study.
Results

Fig. 2 The spatial distribution (point scale) of sun duration on June 22nd (a), Dec. 22nd (c) and Mar. 21st (e); The spatial distribution (point scale) of solar radiation on Jun. 22nd (b), Dec. 22nd (d) and Mar. 21st (f) in Boston.
Radiation maps at different times in a year are produced from our work to analyze the roads photovoltaic distribution (Fig. 2). Results shows the immense potential of road power generation. The total solar radiation calculated is 1.304E+10 kWh. Considering average solar irradiance-to-electricity conversion efficiency (17%) [10], annual photovoltaic energy of Boston roads is about 2.216E+9 kWh. Such much electricity can power 763.1 thousand electric vehicles as each vehicle requires 2900 kWh per year in average [11], and is sufficient for all vehicles in Boston as the number of household vehicles in Boston is just about 272.6 thousand [12]. What’s more, main roads through Boston exhibit better power generation potential, and the effect of the traffic condition is limited.
Discussion and Conclusion
The contribution of this research is as follows. On one hand, we take many factors affecting radiation into account, including climate, seasons, daylight duration, buildings, trees, terrain, and traffic to quantify radiation accurately. On the other hand, using GSV image for calculation is more real in street simulation with low-cost compared to 3-D urban model and high-resolution satellite image. Also, this study provides a scientific basis for the policy development of sustainable energy city, especially for the photovoltaic road construction.
Our calculation framework confirms that utilizing solar panels as road surfaces is a great supplement of city power with the unique ability to charge moving cars. More notably, as a universe evaluation methodology and the more coverage of street view images, we can measure the capacity of urban road photovoltaic production.


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