Thursday, April 20, 2017

Designing ground-mounted solar panel arrays: Part I

Fig. 1: Inter-row shadowing (daily total)
Designing a ground-mounted solar panel array is one of the challenges in our Solarize Your World curriculum, in addition to other challenges such as rooftop solar power systems, solar canopies, building-integrated photovoltaics, and concentrated solar power plants. With the support of our intuitive Energy3D software, designing a solar panel array appears to be a small and simple job as students can easily add, drag, and drop solar panels to cover up a site with many solar panels. But things are not always as simple as they seem.
Fig. 2: Solar radiation on an array in four reasons.

The design of a photovoltaic solar farm is, in fact, a typical engineering problem that requires the designer to find a solution that generates as much electricity as possible with a limited number of solar panels on a given piece of land, among many other constraints and criteria. Such an engineering project mandates iterative design and optimization in a solution space that has scores of variables. And the more the variables we have to deal with, the more complicated the design challenge becomes.

Fig. 3: Annual outputs vs. row spacing and tilt angle
This sequence of articles will walk you through the essential steps for designing photovoltaic solar farms under a variety of conditions. To get you started, let's assume that 1) we have a rectangular area for the solar farm; 2) the edges of the area are perfectly aligned with the north-south and east-west axes; and 3) the area is perfectly flat. This kind of site is probably uncommon in reality (unless the site is in a desert). But let's begin with a very simple scenario like this.


Fig. 4: Surface plot of solar output (ideal)
One of the first things that we have to decide is the number of solar panels. This is usually dictated by the budget. Suppose we have a fixed quantity of solar panels that we can install at a site large enough to space them (i.e., let's assume that we are not constrained by the area of the site for the time being). As people usually put solar panels on racks (a rack of solar panels is often referred to as a row -- but don't confuse it with the rows of solar panels you put on each rack), the next things we have to decide are 1) how many solar panels we want to place on each rack, 2) whether these solar panels are placed in "portrait" or "landscape" orientation on the rack, and 3) how long each rack is. From these information, we know the number of rows for the array. For example, the array in Figure 1 has four rows, each of which has 88 solar panels stacked up in a 4x22 landscape configuration. Since the shorter side of each panel is about one meter long, each rack is about four meters wide.

Fig. 5: Surface plot of solar output (using bypass diodes)
How far should the distance between two adjacent rows be? If the solar panels are tilted towards the sun, the rows cannot be too close to one another as the inter-row shadowing (Figure 1) will reduce the total output (sometimes severely, depending on the wiring of the solar cells on the solar panels -- we will investigate this in the next article), but they cannot be too far away from one another, either, as a longer distance between rows will decrease the efficiency of land use. Determining the optimal inter-row spacing for the solar array under design depends on a number of confounding factors such as the tilt angles, location, solar cell wiring, time of year, use of trackers, type of inverters, and shape of the site that greatly complicate the problem (Figure 2). This is a case in which a thorough understanding of the domain knowledge per se does not suffice to solve the problem. As there is no exact solution, we have to come up with a procedure and a strategy to search for an optimal one in the solution space. And, sometimes, this solution space can be so vast that manual search becomes infeasible.

Fig. 6: Line graph of solar output (using bypass diodes)
To simplify the search for now, let's assume that we only have to decide on the optimal values for the tilt angle and the inter-row spacing. This assumption reduces the solution space to only two dimensions. The most straightforward way to nail them down is to gradually vary the tilt angle and the inter-row spacing and then compute the total annual output of the solar panels at each step (Figure 3), a tedious job that took me a couple of hours to do. Once we have the results, we can use Excel to create a surface plot that shows different zones of outputs as a function of the inter-row spacing and tilt angle (Figures 4 and 5 -- we will discuss their differences in the next article; for now, you just need to know that Figure 5 is a more accurate result). The yellow zones in the surface plots are the reduced solution space where we should zero in to find our solution, taking trade-offs with other criteria such as the efficiency of land use into account. To have a clearer view, Figure 6 shows a 2D line graph of the solar outputs as a function of the tilt angle for six values of inter-row spacing.

The conclusions are that a tilt angle that is approximately equal to the latitude of the site (about 42 degrees in the case of Boston, MA) is the best when the rows are relatively far apart (say, 10 meters away center-to-center or 6 meters way edge to edge when the tilt angle is zero) and when the rows become closer, a smaller tilt angle should be more favorable. For instance, with the center-to-center inter-row spacing reduced to 8 and 7 meters, 35 and 26 degrees are the optimal choices for the tilt angle, respectively. With the optimal tilt angles, we will lose about 2% and 4% of electricity output when we reduce the inter-row spacing from 10 meters to 8 meters and 7 meters, respectively. If we don't change the tilt angles, the losses will increase to 3% and 9%, respectively. These findings apply to fixed solar panel arrays that do not track or "backtrack" the sun.

The analyses we have done so far just barely scratched the surface of the problem. We have many other design topics to cover and design factors to consider. But the volume of work thus far should speak aloud for itself that this is not a simple problem. At the same time Energy3D greatly simplifies an engineering task and empowers anyone to tackle it, it could also create an illusion as if engineering were simple. Yes, a What-You-See-Is-What-You-Get (WYSIWYG) 3D design and construction program like Energy3D may be entertaining in ways similar to playing with Minecraft, but no, engineering is not gaming -- it differs from gaming in many fundamental ways.

Wednesday, April 5, 2017

A demo of the Infrared Street View

An infrared street view
The award-winning Infrared Street View program is an ambitious project that aims to create something similar to Google's Street View, but in infrared light. The ultimate goal is to develop the world's first thermographic information system (TIS) that allows the positioning of thermal elements and the tracking of thermal processes on a massive scale. The applications include building energy efficiency, real estate inspection, and public security monitoring, to name a few.
An infrared image sphere


The Infrared Street View project is based on infrared cameras that work with now ubiquitous smartphones. It takes advantages of the orientation and location sensors of smartphones to store information necessary to knit an array of infrared thermal images taken at different angles and positions into a 3D image that, when rendered on a dome, creates an illusion of immersive 3D effects for the viewer.

The project was launched in 2016 and later joined by three brilliant computer science undergraduate students, Seth Kahn, Feiyu Lu, and Gabriel Terrell, from Tufts University, who developed a primitive system consisting of 1) an iOS frontend app to collect infrared image spheres, 2) a backend cloud app to process the images, and 3) a Web interface for users to view the stitched infrared images anchored at selected locations on a Google Maps application.

The following YouTube video demonstrates an early concept played out on an iPhone:



Friday, March 31, 2017

High school students to solarize the city of Lowell -- virtually


In April, high school students in Lowell, Massachusetts will start exploring various solarization possibilities in the city of Lowell -- famously known as the Cradle of American Industrial Revolution. Many municipal properties and apartment buildings in Lowell have large roofs that are ideal for rooftop solar installations. Public parking facilities also provide space for installing solar canopies, which serve the dual purpose of generating clean energy and providing shade for parked cars. Students will discover the solar potential of their city and calculate the amount of electricity that can generated based on it.

This project is made possible by our Energy3D software, which supports engineering-grade solar design, simulation, and analysis. The Lowell High School, local business owners, and town officials have been very supportive about this initiative. They provided a number of public and private sites for students to pick and choose. Some of them have even agreed to serve as the "clients" for students to provide specifications, inputs, and feedback to students while they are carrying out this engineering project.

Among the available sites, five public parking garages managed by the municipal authority, which have not installed solar canopies, will be investigated by students through feasibility studies that include 3D modeling, solar energy simulation, and financial planning. Through the project work, students will author reports addressed to the property owners, in which they will recommend appropriate solar solutions and financial options.

Solving real-world problems like these creates a meaningful and compelling context and pathway for students to learn science and engineering knowledge and skills. Hopefully, their work will also help inform the general public about the solar potential of their city and the possibility of transitioning it to 100% renewable energy in the foreseeable future, which is a goal recently set by Massachusetts lawmakers.

Saturday, February 25, 2017

Designing building-integrated photovoltaics with Energy3D

Fig. 1: An example of solar facade.
Building-integrated photovoltaics (BIPV) represents an innovative way to think and design buildings as both human dwellings and power plants. In BIPV, solar panels or photovoltaic thin films are used to replace conventional constructional materials in parts of the building envelope such as roofs, walls, and even windows. Designing new buildings nowadays increasingly includes BIPV elements to offset operational costs. Existing buildings can also be retrofitted with BIPV (e.g., replacing glass curtain walls with solar panels). BIPV is expected to grow more important in architectural design and building engineering.

Fig. 2: An example of solar curtain walls
We are developing modeling capabilities in Energy3D to support the design, simulation, and analysis of BIPV. Figures 1 and 2 in this article show a few cases that demonstrate these capabilities in their primitive forms. Considering BIPV is relatively new and a lot of research is still under way to develop and test new ideas and technologies, we expect the development of these capabilities in Energy3D will be a long-term effort that will be integrated with latest research and development in the industry.
Fig.3: Power balancing throughout the day.

As the first step towards that long-term vision, the current version of Energy3D has already allowed you to add solar panel racks to any planar surface, being it horizontal, vertical, or slanted. Running a simulation for any day, you will be able to predict the daily output of all the solar panels. You can also compare the outputs of selected arrays. For example, if you want to track down on which side solar panels produce the most at a given time during the day, you can compare them in a graph. Figure 3 shows a comparison of the solar arrays in the model shown in Figure 1. As you can see, the east-facing array produces peak energy in the morning whereas the west-facing array produces peak energy in the afternoon. In this case, the BIPV solution ensures that the photovoltaic system generates some electricity at different times of the day.

Wednesday, February 15, 2017

Video tutorial: Solarize an imported building in Energy3D

We are pleased to announce that the solar panel and analysis tools in Energy3D (version 6.5.6 or higher) are now fully applicable to arbitrary imported structures. We hope that the new capabilities can help engineers who design rooftop solar systems and building solar facades to get their jobs done more efficiently and students who are interested in engineering to learn the theory and practice in an inquiry-based fashion. The six-minute video in this article demonstrates how easy it is to perform solar panel design and analysis in Energy3D. (Note: Unfortunately, the annotations in the video do not show if you are watching this on a smartphone.)



One of the handiest features is the automatic, real-time detection of the angle of the surface under a solar panel while the user is moving it. This feature basically allows the user to drag and drop a solar panel or a solar panel rack anywhere (on top of roofs, walls, or other surfaces) without having to set its tilt angle manually.

Solar heat map of a house with solar panels
Copy and paste a house with solar panels
Solar panels are "first-class citizens" in Energy3D as they are readily recognized by the built-in simulation engines. Energy3D provides a comprehensive list of properties that you can choose for each solar panel or solar panel array. For example, even the temperature coefficient of Pmax, a parameter that specifies the change of solar cell efficiency with regard to ambient temperature change, is supported. The software also has a variety of analytic tools for predicting the hourly, daily, and annual outputs of each solar panel and their sums. Interactive graphs are available to intuitively show the trends and allow the user to compare the outputs of different solar panels, of different arrays, on different days, or with different environmental settings (e.g., with or without a tree nearby).

These "native" solar panels are now completely blended into the "alien" meshes of structures imported into Energy3D from other CAD software or Google Earth. For example, once you drop a solar panel on a surface of the structure, it will stick to it. In other words, if you move or rotate the structure, the solar panel will go with it as if it were part of the original design. When you copy and paste the entire building, the solar panels will be copied and pasted as well (by the way, it takes only four clicks to copy and paste a building in Energy3D through the pop-up menu: one click to pick which one to act upon, one click to select the "Copy" action, one click to pick where to paste, and one last click to select the "Paste" action). That is to say, the native and alien meshes are completely meshed.

Friday, February 10, 2017

Automatic remeshing in Energy3D for solar analysis

A headache in the practice of simulation-based engineering or computer-aided engineering is the incompatibility of the meshes used to create and render structures (let's call them the drawing meshes) and the meshes needed to simulate and analyze certain functions (let's call them the analysis meshes). This incompatibility stems deeply from the fundamental differences in computer graphics for visual rendering and computer simulation for physics modeling.

When importing a model from a CAD tool into a simulation tool, engineering analysts often have to recreate new analysis meshes for their computation, which requires fine-grained discretization such is in the case of finite element analysis and other methods. It becomes a nightmare when the conversion from the drawing meshes to the analysis meshes can only be done manually. Even if only a few drawing meshes need to be taken care by hand while the majority of the meshes can be converted automatically, the analyst still would have to check all the meshes to make sure that every mesh is good for simulation. So we really need a tool that can deal with all sorts of scenarios. And this kind of tool is by no mean easy to develop.


Mesh incompatibility was (and may remain for a long time) a problem for Energy3D when it imports structure models created by other tools such as SketchUp. For example, in most architectural CAD models, a structural element such as a wall or a roof (or a part of them) is represented by two planar meshes that have exactly opposite normal vectors, representing the interior and exterior surfaces, respectively. These two meshes have identical coordinates for their vertices, though the orders of their definition are different (one goes clockwise and the other anticlockwise in order for their normal vectors to be exactly opposite). Whatever they represent has therefore no thickness, but with the two faces, we can apply two different textures to them so that the viewer can tell if they are looking at its interior or exterior surface.


While this sounds good to people who use such models in 3D games, it spells troubles to Energy3D. The first problem is that it increases the number of vertices that Energy3D has to load and, therefore, the memory footprint of such models. In a physics simulation, a structural element without thickness is meaningless. If we don't really need the two faces in most cases (we do in some other cases, but I will skip that line of discussion in the article), why bother to import them in the first place? Despite spending days on researching on the Internet and checking the Collada specification, I couldn't figure out how to force SketchUp to export only the exterior meshes (SketchUp's Colloda export function does provide the option of exporting two-sided faces or not, but it sometime exports only the interior sides for some meshes, mixed with exterior sides for others). So it occurred to me that I had to deal with them in the Energy3D code.

If we don't treat them and use the meshes as they are, we then have the second problem: which mesh should we pick to be the side that receives solar radiation? While it is self-evident which mesh of the two identical ones faces outside when we look at the 3D model after it is rendered on the computer screen, we absolutely have no way to tell from their coordinates alone in our code. Somehow, we have to invent an algorithm that simulates how people discern it when they look at the 3D view of the model on a computer screen.

Picking and choosing the right meshes, of course, is crucial to the correctness of the simulation results. In order to test the new algorithms in Energy3D, I selected the lower Manhattan island and the US Capitol Building as two test cases. The results of the lower Manhattan island have been reported in an earlier article. But the Capitol Building has turned out to be a harder case as -- with over 15,000 meshes -- it is geometrically more complicated and it has so many details that really put our code to test. After more than a week of my work on solving a myriad of problems, it seems that Energy3D has passed the test (or has it?). The screenshots of the solar irradiance heat maps of the Capitol Building from different angles show that severe anomalies are practically non-existent across the heat maps.


The heat maps occasionally suffer from a flickering effect called "Z-fighting" when two planar surfaces are visually close, especially when being looked at from a distance sufficiently far away. For the Z-fighting between identical meshes, this can be mitigated by increasing the offset of their distance. But, as this doesn't affect the simulation result, it is less a concern for the time being.

Automatic remeshing for solar analysis may also need to include automatic repair of models that contain errors. For example, some models may contain surfaces that have only one mesh with the normal vector pointing inward (this could happen if the original designer accidentally used the "Reverse Faces" feature in SketchUp without realizing that the normal vectors would be flipped). This kind of mesh is tolerated in SketchUp because it does not affect rendering. But they cannot be tolerated in Energy3D because such a single-face mesh with a north-pointing normal vector, which appears to the viewer as south-facing, will show little to zero solar radiation when the sun shines on it. Luckily, due to the visualization in Energy3D, we can quickly spot those incorrect surfaces and fix them by reversing their faces manually. But we will need to find a way to automate this process (not easy, but not impossible).

Sunday, January 29, 2017

Solar analysis of metropolitan areas using Energy3D

Fig. 1: Sunshine at the lower Manhattan island
Energy3D can be used to analyze the solar radiation on houses, buildings, and solar power plants to help engineers design strategies for exploiting useful solar energy or mitigating excessive solar heating. This blog post shows that Energy3D may also be used to analyze the solar radiation in large urban areas (e.g., to study the effect of urban heat islands).

Fig. 2: Solar irradiance heat map of Manhattan on 4/25
To demonstrate this application, I chose a 3D model of a section of the lower Manhattan island as a test. The 3D model was downloaded from SketchUp's 3D Warehouse. It was supposedly created after the lower Manhattan island in 2008. I didn't bother to check for accuracy as this was supposed to be a test of Energy3D. Figure 1 shows the model of the Manhattan area.

Fig. 3: More solar irradiance heat maps.
The model has more than 8,000 meshes of various sizes (a mesh is a polygon area for computational analysis and graphical rendering in Energy3D). The entire area is so big that even a low-resolution daily simulation took more than five hours to complete on my Surface Book computer. Figures 2 and 3 show the rendering of the solar irradiance heat map on top of the 3D model after the computation completes.

Our next step is to figure out how to optimize our simulation engine to speed up the calculations. The latest version of Energy3D already includes some optimizations that allow faster re-rendering of the solar irradiance heat map by re-generating the texture images without re-calculating the solar irradiance distribution.

Thursday, January 19, 2017

Importing and analyzing models created by other CAD software in Energy3D: Part 2


Fig.1: The Gherkin (London, UK)
In Part I, I showed that Energy3D can import COLLADA models and perform some analyses. This part shows that Energy3D (Version 6.3.5 or higher) can conduct full-scale solar radiation analysis for imported models. This capability officially makes Energy3D a useful daylight and solar simulation tool for sustainable building design and analysis. Its ability to empower anyone to analyze virtually any 3D structure with an intuitive, easy-to-use interface and speedy simulation engines opens many opportunities to engage high school and college students (or even middle school students) in learning science and engineering through solving authentic, interesting real-world problems.
Fig. 2: Beverly Hills Tower (Qatar)

There is an ocean of 3D models of buildings, bridges, and other structures on the Internet (notably from SketchUp's 3D Warehouse, which provides thousands of free 3D models that can be exported to the COLLADA format). These models can be imported into Energy3D for analyses, which greatly enhances Energy3D's applicability in engineering education and practice.

Fig. 3: Solar analysis of various houses
The images in this post show examples of different types of buildings, including 30 St Mary Axe (the Gherkin) in London, UK (Figure 1) and the Beverly Hills Tower in Qatar (Figure 2). Figure 3 shows the analyses of a number of single-family houses. All the solar potential heat maps were calculated and generated based on the total solar radiation that each unit area on the building surfaces receive during the selected day (June 22).

These examples should give you some ideas about what the current version of Energy3D is already capable of doing in terms of solar energy analysis to support, for example, the design of rooftop solar systems and building solar facades.

In the months to come, I will continue to enhance this analytic capacity to provide even more powerful simulation and visualization tools. Optimization, which will automatically identify the boundary meshes (meshes that are on the building envelope), is currently on the way to increase the simulation speed dramatically.

Saturday, January 14, 2017

Importing and analyzing models created by other CAD software in Energy3D: Part 1

Fig. 1: Solarize a COLLADA model in Energy3D
Fig.2: A house imported from SketchUp's 3D Warehouse
Energy3D is a relatively simple CAD tool that specializes in building simulation and solar simulation. Its current support for architectural design is fine, but it has limitations. It is never our intent to reinvent the wheel and come up with yet another CAD tool for architecture design. Our primary interest is in physics modeling, artificial intelligence, and computational design. Many users have asked if we can import models created in other CAD software such as SketchUp and then analyze them in Energy3D.

Fig. 3: A house imported from SketchUp's 3D Warehouse
I started this work yesterday and completed the first step today. Energy3D can now import any COLLADA models (*.dae files) on top of a foundation. The first step was the inclusion of the mesh polygons in the calculation of solar radiation. The polygons should be able to cast shadow on any object existing in an Energy3D model. This means that, if you have a 3D model of a neighboring building to the target building, you can import it into Energy3D so that it can be taken into consideration when you design solar solutions for your target. Once you import a structure, you can always translate and rotate it in any way you want by dragging its foundation, like any existing class of object in Energy3D.

Fig. 4: A house at night in Energy3D
Due to some math difficulties, I haven't figured out how to generate a solar radiation heat map overlaid onto the external surfaces of an imported structure that are exposed to the sun. This is going to be a compute-intensive task, I think. But there is a shortcut -- we can add Energy3D's solar panels to the roof of an imported building (Figure 1). In this way, we only have to calculate for these solar panels and all the analytic capabilities of Energy3D apply to them. And we can get pretty good results pretty quickly.

Fig. 5: A 3D tree imported from SketchUp's 3D Warehouse
Figures 2-4 show more examples of how houses designed with SketchUp look like in Energy3D after they are imported. This interoperability makes it possible for architects to export their work to Energy3D to take advantage of its capabilities of energy performance analysis.

Being able to import any structure into Energy3D also allows us to use more accurate models for landscapes. For instance, we can use a real 3D tree model that has detailed leaves and limbs, instead of a rough approximation (Figure 5). Of course, using a more realistic 3D model of a tree that has tens of thousands of polygons slows down the graphic rendering and simulation analysis. But if you can afford to wait for the simulation to complete, Energy3D will eventually get the results for you.

Friday, January 6, 2017

Why is Israel building the world's tallest solar tower?

Fig. 1: Something tall in Negev desert (Credit: Inhabitat)
The Ashalim solar project (Figure 1) in the Negev desert of Israel will reportedly power 130,000 homes when it is completed in 2018. This large-scale project boasts the world’s tallest solar tower -- at 250 meters (820 feet), it is regarded by many as a symbol of Israel’s ambition in renewable energy.

Solar thermal power and photovoltaic solar power are two main methods of generating electricity from the sun that are somewhat complementary to each other. Solar tower technology is an implementation of solar thermal power that uses thousands of mirrors to focus sunlight on the top of a tower, producing intense heat that vaporizes water to spin a turbine and generate electricity. The physics principle is the same as a solar cooker that you have probably made back in high school.

Why does the Ashalim solar tower have to be so tall?

Surrounding the tower are approximately 50,000 mirrors that all reflect sun beams to the top of the tower. For this many mirrors to "see" the tower, it has to be tall. This is easy to understand with the following metaphor: If you are speaking to a large, packed crowd in a square, you had better stand high so that the whole audience can see you. If there are children in the audience, you want to stand even higher so that they can see you as well. The adults in this analogy represent the upper parts of mirrors whereas the children the lower parts. If the lower parts cannot reflect sunlight to the tower, the efficiency of the mirrors will be halved.

Fig. 2: Visualizing the effect of tower height
An alternative solution for the children in the crowd to see the speaker is to have everyone stay further away from the speaker (assuming that they can hear well) -- this is just simple trigonometry. Larger distances among people, however, mean that the square with a fixed area can accommodate less people. In the case of the solar power tower, this means that the use of the land will not be efficient. And land, even in a desert, is precious in countries like Israel. This is why engineers chose to increase the height of tower and ended up constructing the costly tall tower as a trade-off for expensive land.

Fig. 3: Daily output graphs of towers of different heights
But how tall is tall enough?

Fig. 4: Energy output vs. tower height
This depends on a lot of things such as the mirror size and field layout. The analysis is complicated and reflects the nature of engineering. With our Energy3D software, however, complicated analyses such as this are made so easy that even high school students can do. Not only does Energy3D provide easy-to-use 3D graphical interfaces never seen in the design of concentrated solar power, but it also provides stunning "eye candy" visualizations that clearly spell out the science and engineering principles in design time. To illustrate my points, I set up a solar power tower, copied and pasted to create an array of mirrors, linked the heliostats with the tower, and copied and pasted again to create another tower and another array of mirrors with identical properties. None of these tasks require complicated scripts or things like that; all they take are just some mouse clicks and typing. Then, I made the height of the second tower twice as tall as the first one and run a simulation. A few seconds later, Energy3D showed me a nice visualization (Figure 2). With only a few more mouse clicks, I generated a graph that compares the daily outputs of towers of different heights (Figure 3) and collected a series of data that shows the relationship between the energy output and the tower height (Figure 4). The graph suggests that the gain from raising the tower slows down after certain height. Engineers will have to decide where to stop by considering other factors, such as cost, stability, etc.

Note that, the results of the solar power tower simulations in the current version of Energy3D, unlike their photovoltaic counterparts, can only be taken qualitatively. We are yet to build a heat transfer model that simulates the thermal storage and discharge accurately. This task is scheduled to be completed in the first half of this year. By that time, you will have a reliable prediction software tool for designing concentrated solar power plants.

Thursday, January 5, 2017

Designing on lot maps in Energy3D

Energy3D allows users to import an Earth View image from Google Maps and then design 3D structures on top of it. The image provides the reference frame, boundary lines, and other visual aids for getting the geometry right. What if there is no Google Map image, or the Google Map image is outdated, or you simply want to draw on a different substrate other than a Google Map image?

Bob Loy, a teacher at Creekside Middle School in Carmel, Indiana, has such a situation. His school is working with a builder to engage young students to design new constructions in their areas. His goal is for them to design houses that fit on assigned lots planned by the builder and then make them as energy-efficient as possible by applying all sorts of solutions, including insulation, passive solar strategies, and solar panel technologies.

Upon his request, I have added a new feature to Energy3D (V6.2.7) to enable users to import an image from a file to serve as the ground for designing a building, a solar farm, or anything made possible by Energy3D.

Since users can import any image that represents any size in the real world, it is their responsibilities to make sure that the dimension and orientation of the image that appears as the ground in an Energy3D model is accurate. Setting the correct dimension can be done by rescaling the image after it has been imported. There are some other requirements of such images, though. For instance, they have to be a square image (its width and height must be the same) with a reasonably high resolution (otherwise they will appear to be too blurry to look once they are transformed into 3D textures). Users must know the scale of such an image, i.e., the exact length in the real world that a unit length in the image represents. Once the image is inside Energy3D, users should measure its width or height within Energy3D and then rescale the image to make sure that the measurement matches the value in the real world. Currently one can use a foundation object in Energy3D as a ruler, but a real ruler should and will be added in a future version to measure any distance in a more intuitive manner.