- predicative capability
- analytical capability
- preventative capability
So far, I have learned a ton of ways to apply this technology. Planning and execution on large scale system analysis continues to arise. In today’s article, we will focus on Solar Planning and how it leverages 3D data and LiDar systems to conduct large scale planning.
Solar energy is very intriguing to me. Solar energy is a form of radiant light and heat that comes from the sun. It is typically harnessed using a range of evolving technologies such as solar heating, photovoltaics, solar thermal energy, solar architecture, molten salt power plants, and artificial photosynthesis.
The field of solar energy and harvesting has been interesting to me for a while through undergraduate studies. I do not believe in replacing all fossil fuels with only solar energy and electrical energy as some others do. I do see the value of leveraging these fields to reduce the overall consumption of fossil fuels. So how can we partition the use of solar energy properly? There is a limited supply available.
Solar energy is of massive importance to our anthroposphere. The anthroposphere is the part of the environment that is made of or modified by humans for use in various human activities and human inhabitance. When we want to leverage technology and human advancement through energy resources, things become problematic in terms of energy partitioning.
How do we currently partition solar energy? How can we effectively utilize LiDar and 3D data to do so? Researchers have been working on the implementation of LiDar to assess rooftop solar voltaic deployment potential within urban areas. This is of most use to us because cities are where energy resources are us readily within our anthroposphere.
Challenges in urban information extraction and management for solar PV deployment assessment can be done with LiDar and 3D data. To determine PV potential for a city, we must have access to a 3D urban model. This requires that individual buildings are represented. This includes having data of buildings that are next to urban vegetation, particular streets, and various objects within a city infrastructure. This includes watercourses, power supply lines, and minor things such as street signs or fountains. A Digital Surface Model can be derived from point cloud data from a LiDar device. LiDar does a general job of approximating roof shapes. The interaction the sun may have with the environment is directly affected by the city and its urban development. We can then plan to place specific solar grids on buildings that would do their best in different locations.
This type of work is crucial for concepts such as the Circular Economy. We are in a state where we are determining the future of cities and their development. The more knowledge we have, the better we can serve the anthrophosphere as a whole. Urban development and solar energy partitioning are of vital importance when we want to plan for a Circular Economy of the future.
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