Determining the potential for solar power generation.

Using Solar Radiation toolset available in ArcGIS Pro

Canada, like many other countries, is grappling with the complex issue of nuclear waste disposal. Nuclear power, indeed, contributes to the reduction of carbon emissions by providing a low-carbon alternative to fossil fuels. However, the environmental concerns related to the long-term management of nuclear waste remain a significant challenge. This waste can remain hazardous for thousands of years, necessitating secure and sustainable management strategies to protect human health and the environment.
Regarding the transition towards renewable energy sources, solar
power emerges as a highly promising alternative.

It’s a common misconception that the effectiveness of solar power is directly tied to the heat of the sun. In reality, solar panels generate electricity through the photovoltaic effect, which converts light energy into electricity.

This means that the key factor for solar power generation is the intensity of sunlight rather than the ambient temperature. Solar panels can still produce electricity on cloudy days, albeit at reduced efficiency compared to direct sunlight conditions.

The Solar Radiation toolset in ArcGIS Pro’s Spatial Analyst extension allows for the analysis and estimation of solar energy potential across different surfaces, such as terrain or buildings, using raster data. This toolset can compute the amount of solar radiation that a particular location receives over a specified period, which is crucial for identifying areas with high solar energy potential. These insights can inform the optimal placement and configuration of solar panels to maximize energy production.

To illustrate this method, the Ontario Digital Surface Model (Lidar-Derived) raster dataset from the Ontario Ministry of Natural Resources and Forestry was utilized. Additionally, the building footprint data was sourced from the Statistics Canada website. These data are specifically trimmed to cover the Yonge Bay Neighborhood.

Data Links

Ontario Digital Surface Model (Lidar-Derived) — Overview (arcgis.com)

Building Footprints — Building Footprint — Open Government Portal (canada.ca)

First, we’ll begin by learning how to assess the solar energy potential of a location using a Digital Surface Model (DSM) with the Raster Solar Radiation tool within the Solar Radiation toolset.

We’ll set up the necessary parameters.

• Use the DSM raster tailored to your specific study area, such as the Yonge-Bay neighborhood in my case, as the Input Surface Raster. Assign an appropriate name for the Output Solar Radiation Raster.
• The tool provides options to input the start and end dates and times, accommodating time zones and daylight-saving adjustments. This feature enables the tool to estimate the annual solar radiation output for an area, considering the sun’s movements throughout the year. I am going to use the entire year of 2023 for this analysis. Enter 1/1/2023 at 12:00:01 AM as the Start Date And Time to commence on January 1, 2023, and 12/31/2023 at 11:59:59 PM as the End Date And Time to conclude on December 31, 2023.
• Considering Toronto, Ontario falls within the Eastern Standard Time zone and observes daylight saving, select Eastern Standard Time for the Time Zone and enable the Adjust Times For Daylight Saving Time option.
• For the Input Analysis Mask, opt for the Building Footprints shape file. This tool can perform a solar radiation analysis on a complete raster layer or be restricted to a specific area using a mask.
• Next, decide on the time interval for the analysis. Selecting a time interval generates various radiation or insolation values for the chosen duration. To balance processing time and detailed intervals, opt for a two-week time interval. Enable the Calculate Insolation For Time Intervals option, select Week for the Time Interval Unit, and ensure it is set to 2 weeks.

Input the required information and hit the ‘Run’ button. Your map will be updated with a new layer that displays the outcome of your solar radiation analysis. This tool’s output reveals the solar radiation received by each cell in the raster layer, measured in kilowatt hours per square meter (kWh/m²). To obtain the total and average solar radiation for a specific area within a raster layer, such as the roof of a building, further processing steps are necessary. The representation of the layer distinguishes areas with the highest solar radiation in red and those with the lowest in blue. Nonetheless, the displayed results represent an annual average of the solar radiation values.

We will also receive the time slider feature. By setting it to weekly and pressing the play button, the layer alters its appearance according to the month. The animation below demonstrates that in the summer, particularly in July, the potential increases, as indicated by a dark red color.

After visualizing the amount of solar radiation over time using the time slider, we want to see the amount of solar radiation generated so that we can identify ideal locations for solar panels. You can do this by viewing a temporal profile chart. The temporal profile visualizes the distribution of solar radiation over time. On the ribbon, click the Multidimensional tab, and then in the Analysis group, click Temporal Profile. You can select a single point or multiple points to compare their temporal profile. In the Chart Properties pane, under Define An Area Of Interest, click the Point button. As shown in the above graphic two locations were selected.

The chart shows that the point of the second location generates more solar radiation over the course of the year than if placed on a darker red area of a roof.

Being able to identify the amount of solar radiation that a rooftop can generate over the course of a year and also the best location on a rooftop to place solar panels allows for the best utilization of solar panels. Typically, in the Northern Hemisphere, houses that have south-facing roofs and are clear of trees will generate the most solar radiation and be the best candidates for solar panels.

This approach not only enhances the efficiency of solar panels by ensuring their placement in areas with the highest solar energy potential but also contributes significantly to the adoption of clean energy sources. By quantifying solar radiation in kilowatt hours per square meter (kWh/m²), stakeholders can make informed decisions that align with environmental sustainability goals and address the global challenge of transitioning to renewable energy sources effectively.