With the increasing chances of depletion of essential energy sources like coal, crude oil, and natural gas over a few decades, finalizing suitable alternatives is the need of the hour. Experts have come up with the idea of using renewable energy sources such as solar, wind, biomass, and geothermal in place of the otherwise typical crude, coal, and natural gas.
However, this cleaner and smarter energy production and transmission process will not be successfully deployed without geospatial technology. GIS or geospatial technology will become a crucial part as it will be the typical tool to monitor and analyze the entire procedure, ensuring the efficient generation and delivery of renewable power to the sites.
Let’s dig deeper on how geospatial technology stands necessary in including renewable energy sources into our daily lives.
NERL, or National Renewable Energy Laboratory, is the body that works to promote renewable sources of energy. Of the various forms of renewable energy like solar, wind, biomass, geothermal, etc., wind energy has been the most developing resource in the early 20th century in the United States. There were windmills on the US landscape that further evolved into wind turbines that boxed more energy and ensured cost-effectiveness too.
Going by the reports released back in the year 2008 by the US Department of Energy (DOE), a demand of around 20% wind energy will be met in the country by the year 2030. The report worked as a roadmap to reach a significant goal, involving ways to overcome massive challenges and steps. It was when Esri and NREL came together to realize the role of GIS in the process of realizing the long-term goal.
GIS helped the NREL team to identify the most beneficial locations for setting up wind farms based on the cost of transmission, load centres and wind resources’ locations, and the electrical grid layout. The wind farm project starts with proper observation of the potential plots in the area, which can be done by exacting the distance of transmission line to be tied in power to the electrical grid. The process was made easier for the researchers by loading utility data into the GIS system. This way, they could see the transmission routes existing in the land and estimate the advantage of accessing the existing electric lines.
So, we can understand that GIS-based modelling helps in the analysis of the terrain, that is directly proportional to the wind quality at a specific location. Moreover, it also helps in the identification of the areas under development restriction in the country.
Solar Energy is the new way of life in many countries with the changing patterns of energy production and consumptions over the decade. But, how do researchers and experts know if a roof has solar potential? Here’s when geospatial technology gets to play a crucial role.
Initially, the researchers collected rooftop data with the help of aerial laser scanners. With ArcGIS Desktop tools, along with an ArcGIS Spatial Analyst, the team obtained all the essential rooftop data, such as inclination, outer form, clouding, and orientation. They used a specific algorithm pattern, developed using the ArcGIS Desktop ModelBuilder application, to identify the solar potential of the roof areas.
With the help of ArcGIS, researchers could also calculate potential power output, solar suitability, CO2 reduction and the investment volume for every roof subarea. For sustainable living, many villages and cities are embracing the use of solar energy. The researchers gave importance to the geography of the particular area – the wind patterns, sun angles, building height and density, and street widths.
In the ArcGIS modelling for a building, its orientation is shown on a diagonal grid to offer highest natural shading. Today, geodatabase helps companies to understand all the necessary variables and interact successfully throughout the project. A standard base map is constructed to support the planning, design and development of the city structure to enable solar power roofs.
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Based on the various researches carried out over the years, a combination of satellite imagery, historical data, and productivity models was used by researchers to identify the lands with potential yields. It also helped them learn about the amount of biomass that could sustainably be used to the energy needs of the world while eradicating global warming.
Given the above situation, the role geospatial technology played and continues to take responsibility in the biomass energy production is quite evident in the case studies of the United Nation’s Food and Agriculture Organisation (FAO). The FAO utilized the efficient GIS-based modelling for estimation of biomass production.
As per the calculative formulas derived by FAO:
Potential biomass density index (PBI) = Climatic index + topograpghy + precipitaion + soil type (texture, slope, depth).
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Talking about the part of GIS or geospatial technology in the production of geothermal energy, It is the best option as per the experts. All the phases of geothermal resources – exposition, development, exploration, drilling, resource appraisal, exploitation and management of hot water fields/steam, the resource information/data are geographic or location-based.
According to the reports released by experts, GIS has widely used in geosciences. From the standard mapping to complex uses like geological or geographic modelling processes, GIS applies in all the stages of geothermal energy production. The application of geospatial technology is brought to use in geological mapping, mainly for integrating remote sensor data to ground collected data, agriculture, hydrology, urban planning, environmental monitoring and planning, etc.
Not limiting to these roles, experts also added that the capability to develop geodatabases representing information in the form of GIS data models is a highly crucial aspect for managing geological data as a larger percentage of the geo-scientific data includes the events and features of the Earth. Yet another plus point of GIS concerning the production of geothermal energy is geoprocessing. It is the process of utilizing information transition tools for deriving new datasets from the databases already secured. Geoprocessing includes using analytical functions such as statistical analyses.
The Bottom Line
In the evolving world of technology, we have multiple options for renewable energy sources. The production of renewable energy options is related to several geo variables, suggesting the use of geospatial analysis to find the best site for each energy resource.
Over the last decade, geospatial energy has become a significant component of the decision making of renewable energy production. From finalizing sites for wind farms to the areas best for solar energy and geothermal development, GIS/geospatial data science have played a crucial role in the overall analysis of the production process. In the coming years, the importance of spatial science is nowhere to decrease.