Tag Archives: SmartCAD

Accelerating solar farm design in Energy3D with a new model of solar panel racks

Fig. 1: A solar farm of 5,672 solar panels on 8/16 in Boston
The solar simulation in Energy3D is based on discretizing a solar panel, a reflector, a solar water heater, a window, or any other surface into many small cells (mesh), calculating the solar radiation to the centers of the cells, and then summing the results up to obtain the total energy output. For example, a photovoltaic solar panel can be divided into 6x10 cells (this is also because many residential versions of solar panels are actually designed to have 6x10 solar cells). The simulation runs speedily when we have only a few dozen solar panels such is in the case of rooftop solar systems.

Fig. 2: Simulation of 5,672 solar panels on 8/16 in Boston
Unlike rooftop solar systems, large-scale solar farms typically involve thousands of solar panels (mega utility-scale solar farms may have hundreds of thousands of solar panels). If we use the same discretization method for each panel, the simulation would run very slowly (e.g., the speed drops to 1% when the number of solar panels are 100 times more). This slowdown basically makes Energy3D impractical to use by those who cannot afford to wait such as students in the classroom who need to get the results quickly.

Fig. 3: The result of the accelerated model
Fig. 4: The result of the original model
Luckily, solar panel arrays are often installed on parallel long racks in many solar farms (Figure 1). For such solar panel arrays, a lot of calculations could be spared without compromising the overall accuracy of the simulation too much. This allows us to develop a more efficient model of numeric simulation to do solar radiation calculation and even explore methods that use non-uniform meshes to better account for areas that are more likely to be shaded, such as the lower parts of the solar panel arrays. By implementing this new model, we have succeeded in speeding up the calculation dramatically. For example, the daily solar simulation of a solar farm consisting of more than 5,000 solar panels took about a second on my Surface Book computer (Figure 2 -- in this scene I deliberately added a couple of trees so that you can see the result of shading). With the previous model I would probably have to wait for hours to see the result and the graphics card of my computer would take a very deep breath to render more than 5,000 dynamic textures. This is a huge improvement.

Figures 3 and 4 show a comparison of the simulation results between the new and old models. Quantitatively, the total output of the new model is 93.63 kWh for the selected day of June 22 in Boston, compared with 93.25 kWh from the original model. Qualitatively, the color shading patterns that represent the distribution of solar radiation in the two cases are also similar.

The new rack model supports everything about solar panels. It has a smart user interface that allows the user to draw racks of any size and in any direction -- it automatically trims off any extra length so that you will never see a partial solar panel on a rack. When tracking systems are used with long, linear racks, there is only one way to do it -- horizontal single-axis tracker (HSAT). The new model can handle HSAT with the same degree of speed-up. For other trackers such as the vertical single-axis tracker (VSAT) or the altazimuth dual-axis trackers (AADAT), the speed-up will not be as significant, however, as the inter-rack shading is more dynamically complex and each rack must be treated independently.

Designing solar farms and solar canopies with Energy3D

Fig. 1: Single rack
Many solar facilities use racking systems to hold and move arrays of solar panels. Support of racks is now available in our Energy3D software. This new feature allows users to design many different kinds of solar farm, solar park, and solar canopy, ranging from small scale (a few dozen) to large scale (a few thousand).

Fig. 2: Multiple racks
Mini solar stations often use a single rack to hold an array of solar panels (Figure 1). This may be the best option when we cannot install solar panels on the building's roof. You probably have seen this kind of setup at some nature centers where the buildings are often shadowed by surrounding trees.

If you have more space, you probably can install multiple racks (Figure 2), especially when you are considering using altazimuth dual-axis solar trackers to drive them. This configuration is also seen in some large photovoltaic power stations.

Fig. 3: Rack arrays
Larger solar farms typically use arrays of long racks (Figure 3). Each rack can be driven by a horizontal single-axis tracker. Using taller racks usually requires larger inter-rack spacing, which may be an advantage as it allows maintenance trucks to drive through. In a recent experiment, SunPower experimented with how to grow crops or raise animals in the inter-rack space with their Oasis 3.0 system. So arrays of taller racks may be desirable if you want to combine green energy with green agriculture.

Fig. 4: Solar canopy above a parking lot
If you raise the height of a rack, it becomes a so-called solar canopy that provides shading for human activities like the green canopies of trees do. The most common type of solar canopy converts parking lots into power stations and provides shelters from the sun for cars in the summer (Figure 4).

Designing solar canopies for schools' parking lots may be a great engineering project for students to undertake. This is being integrated into our Solarize Your School Project. In fact, Figure 4  shows a real project in Natick High School in Massachusetts. The hypothetical design has more than 1,500 solar panels (each of them has the size of 0.99 x 1.96 m) and costs over a million dollars.

Modeling Charlottesville High School’s solar project using Energy3D

Schools have plenty of roof space that can be turned into small power plants to provide electricity to students. Many schools have already taken actions. Some teachers even use the subject matter in their teaching. But in most cases, students are not profoundly involved in solarizing their own schools.

Fig. 1: Google Map 3D vs. Energy3D
Sure, students are not professional engineers and adults may not trust them when making serious investments in solar energy. But there is a safe way to let them try: Computer simulation allows students to model and design solar panel arrays for their schools without incurring any cost, risk, or injury.

Fig. 2: 88-panel arrays on CHS's roof.
There have been scores of software programs for professional solar designers. But they usually cost $1,000 per license or annual subscription as their market is really a small niche. In addition to this cost barrier for schools, most of these tools do not necessarily cover education standards or support student learning. Thanks to the National Science Foundation, there is now a powerful free alternative for all students and teachers -- Energy3D. A one-stop shop for solar power design and simulation, Energy3D is an extremely versatile CAD tool that can be used to design rooftop solar solutions for not only average homes but also large buildings (you probably have also seen that it can be used to design utility-scale concentrated solar power stations as well). Importantly, Energy3D provides excellent 3D graphics, rich visualizations, and powerful analytical tools that support scientific inquiry and engineering design at fundamental levels. These features make Energy3D a perfect tool for engaging students and fostering learning.

Fig. 3: Solar irradiance map (June 22)
We are collaborating with Charlottesville High School (CHS) in Virginia to plan for a pilot test of the Solarize Your School project, in which students will learn science and engineering concepts and principles through designing large-scale solar panel arrays that achieve optimal cost effectiveness. To make sure every student has the same building to solarize, I sketched up an Energy3D model of CHS as shown in Figure 1 to provide to students as the starting point. If you want to do this for your own school, you can import a Google Map image of the school using the Geo-Location Menu in Energy3D. After the map image shows up in the view, you can draw directly on top of it to get the basic shape right. While it may not be possible to get the exact heights in Google Map, you can use the elevation data provided by Google Earth to calculate the heights of the walls and roofs.

CHS currently has six arrays of solar panels installed on their roof. Five arrays have 88 panels each and one has 10. The panels are arranged in three rows, with the portrait orientation and a tilt angle of 10 degrees (Figure 2). All the panels are 240W AP-240 PK from Advanced Solar Photonics (ASP). Their solar cell efficiency is 14.82%. Their temperature coefficient of Pmax (a property that measures the decrease of solar output when the temperature rises) is -0.4%/°C. Their size is 1650 x 992 x 50 mm. Each panel has three internal bypass diodes. The arrays use REFUsol string inverters to convert electricity from DC to AC, meaning that these arrays probably have little to no tolerance to shade and should be placed away as far from any tall structure as possible. I couldn't find the efficiency of the string inverters, so I chose 90% as it seems typical. I also didn't know the dust level in the area and the cleaning schedule, so I applied 5% of dust loss throughout the year (although the dust loss tends to be higher in the spring due to pollen). Since they went into operation on March 1, 2012, these panels have generated a total of 605 megawatt hours (MWh) as of September 8, 2016, amounting to an average of annual yield at 135 MWh.

Fig. 4: Prediction vs. reality.
I added these solar panel arrays to the Energy3D model with their parameters set for simulation. Figure 3 shows a heat map visualization of solar irradiance on June 22, indicating the ranges of major shading areas. Figure 4 shows the comparison of the predicted output and the actual output in the past 12 months. As some of the arrays were in maintenance for some time in the past year, I picked the highest-performing array and multiplied its output by five to obtain a number that would fairly represent the total yield in the ideal situation. Also note that as there is currently no weather data for Charlottesville, I picked the nearby Lynchburg, which is about 68 miles southwest of Charlottesville, as the location.

The prediction of the total output by Energy3D is a bit higher than the actual output in the past year (139 MWh vs. 130 MWh). If we compare the predicted result with the four-year average, the difference is less (139 MWh vs. 135 MWh). In terms of monthly trend, it seems Energy3D underestimates the winter outputs and overestimates the summer outputs. While the result may be satisfactory for educational use, we will continue to improve the fidelity of Energy3D simulations.

Choose solar trackers: HSAT, VSAT, or AADAT?

Fig. 1: HSAT and VSAT.
Energy3D now supports three major types of solar trackers: Horizontal single-axis trackers (HSAT), vertical single-axis trackers (VSAT), and altazimuth dual-axis trackers (AADAT). I have blogged about HSAT and AADAT earlier. Figure 1 shows the difference between HSAT and VSAT.

With all these options, which should we choose? The decision is based on the additional output of the solar panels, the space required to operate the system, and, of course, the cost of the tracking system. For instance, AADAT may be more complex as it rotates around two perpendicular axes. Space is always an important constraint and it is even more so for large solar farms considering the issue of inter-panel shading. Fixed arrays and HSAT systems may be more efficient in space usage if the inter-row shading is not significant.
Fig. 2 Energy3D predictions of annual outputs.

Let's first compare the annual output of a single solar panel under different conditions, as shown in Figure 2 and summarized in Table 1, calculated using Energy3D.

Table 1. Comparison of total annual outputs of a solar panel that has a fixed tilt angle equal to its latitude, a solar panel that is rotated by a HSAT, a solar panel that is rotated by a VSAT, and a solar panel that is rotated by an AADAT, at four different locations in the US. The unit is kWh.


Locations
Fixed (tilt=lat.)
HSAT
VSAT
AADAT
Boston, MA
428
520
559
603
Anchorage, AK
258
310
371
380
Miami, FL
507
654
617
711
San Juan, PR
523
694
617
738
 
These results suggest that the AADAT system, not surprisingly, generates the most electricity throughout the year at all four locations, as it always faces the sun. The second best, for low-latitude locations, is the HSAT system and, for high-latitude locations, is the VSAT system. In the case of HSAT, the lower the latitude, the closer the performance of the HSAT approaches that of the AADAT. In the case of VSAT, the higher the latitude, the closer the performance of the VSAT approaches that of the AADAT. This means that, considering the cost factor, HSAT at a very low latitude such as the equator is a better choice than AADAT and VSAT at a very high latitude such as Alaska is a better choice than AADAT.
Fig. 3 Optimal layout through heat map tessellation. 

The above analysis is based on a single, isolated solar panel. For arrays of panels, we must consider the shading area each panel sweeps when it is driven by a tracker. Energy3D's heat map visualization of solar irradiance may be a useful tool for designing optimal layouts for VSAT or AADAT panels that cannot be seamlessly aligned into rows such is in the case of HSAT arrays. From a mathematical point of view, an optimal layout must minimize land use. Hence, it can be imagined as a tessellation of effective shade area of individual panels (Figure 3). This may be something interesting to think about.

Simplifying solar design in Energy3D with Google Map integration

Fig. 1 2D view of Concord Consortium building in Energy3D
Solar design depends on accurate geometry. Rooftop solar panel design requires accurate 3D models of buildings, for example the shape of the roof, the height of the building, and the surrounding objects such as trees. Likewise, solar power station design requires accurate information about the field.

Fig. 2 3D view of Concord Consortium building in Energy3D
The easiest way to obtain these information is through Google Map, from which the dimension of an object can be measured. Although Google Map has not provided elevation data for a point yet, Google Earth does for many towns.

Earlier this year, students who performed solar design with Energy3D in our pilot tests must use Google Earth to retrieve the geometrical data for use in Energy3D design later. Having to master two sophisticated software tools simultaneously in a short time has turned out to be quite a challenge to many students. So an idea came to our mind: Why not just make Google Earth work within Energy3D? (Note: In fact, this is also a common feature among CAD software such as SketchUp.)

Fig. 3 Solar heat map of Concord Consortium building
It turned out that this integration is fairly simple, because Google has done the hard part of providing an easy-to-use Web API for virtually every platform. So in the latest version of Energy3D (V5.8.2 or higher), users will have an internal Google Map ready to help them with their solar designs.

Fig. 4 2D view of a solar farm in Concord, MA in Energy3D
Solar designers can specify a target location in Energy3D and then a Google Map image will be downloaded and used to overlay the ground in Energy3D. They can then draw a 3D building on top of this image by tracing the envelope of the building, eliminating the need to set the dimension of each side numerically. Figures 1-3 demonstrate the result of this new feature using the Concord Consortium's office building as an example.

Fig. 5 3D view of a solar farm in Concord, MA in Energy3D
A remarkable advantage brought by this feature is that it is easy to add model trees on top of the images of surrounding trees. A future version will also allow users to adjust the height and spread of a model tree based on the Google Map image.

Other than assisting designers to acquire site data, the map image also provides a rendering of how a new design may look like in an environment with existing buildings (just pretend for a moment that the building in Figure 2 hadn't existed and were a proposal to build two new houses at the site). Furthermore, with Google Map's elevation API, we will also be able to construct a terrain model of the ground (which is currently flat). Such a terrain model will not only make the energy simulation more accurate by taking all the surrounding objects into account but also make the rendering more realistic by giving the 2D map image a 3D effect (similar to the new 3D view of Google Map).

Based on Energy3D, we have created two solar design challenges for students to make meaningful contributions to the solarization movement. One is to solarize their own houses by designing rooftop solar panels. The other is to solarize their own schools and towns by designing solar farms (Figures 4 and 5). Aligned with the Next Generation Science Standards (NGSS) that require students to think and act like scientists and engineers, our goal is to engage students to practice science and engineering through solving real-world problems. But real-world problems are often complex and difficult (otherwise they are not problems in the real world!). This calls for the development of advanced tools that can empower students to tackle real-world problems. Our Energy3D software provides examples of how technology may knock down the barriers and help students attain the high standards set by the NGSS.

Modeling horizontal single-axis solar trackers in Energy3D

In the last post, I have blogged about modeling dual-axis solar trackers in Energy3D. To be more precise, the trackers shown in that blog post are altitude-azimuth (Alt/Az), or altazimuth trackers, or AADAT in short. In this post, I will introduce a type of single-axis tracker -- the horizontal single-axis tracker, or HSAT in short.

Fig. 1 Solar panel arrays rotated by HSATs
Because single-axis trackers do not need to follow the sun exactly, there are many different designs. Most of them differ in the choice of the axis of rotation. If the axis is horizontal to the ground, the tracker is a HSAT. If the axis is vertical to the ground, the tracker is a vertical single-axis tracker, or VSAT in short. All trackers with axes of rotation between horizontal and vertical are considered tilted single-axis trackers, or TSAT in short. None of these single-axis trackers can help the solar panels capture 100% of the solar radiation that reaches the ground. Exactly which design to choose depends on the location of the solar farm, among other consideration such as the cost of the mechanical system.

Fig. 2 Compare daily outputs of HSAT, AADAT, and fixed in four seasons.
HSAT is the first type of single-axis tracker that has been implemented in Energy3D. HSAT is probably more common than VSAT and TSAT and is probably easier to construct and install. In most cases, the rotation axis of a HSAT aligns with the north-south direction and the solar panels follow the sun in an east-to-west trajectory, as is shown in the YouTube video embedded in this post and in Figure 1.

Fig. 3 Compare annual outputs of HSAT, AADAT, and fixed.
How much more energy can a HSAT help to generate? Figure 2 shows the comparison of the outputs of a HSAT system, an AADAT system, and an optimally fixed solar panel on March 22, June 22, September 22, and December 22, respectively, in the Boston area. The results suggest that the HSAT system is almost as good as the AADAT system in June but its performance declines in March and September and becomes the worst in December (in which case it can only capture a little more than half of the energy harvested by the AADAT system). Interestingly, also notice that there is a dip at noon in the energy graphs for March, September, and December. Why so? I will leave the question for you to figure out. If you have a hard time imagining this, perhaps the visualizations in Energy3D can help.

Fig. 4 Compare wide- and narrow-spacing of HSAT arrays
Figure 3 shows the annual result, which suggests that, over the course of a year, the HSAT system -- despite of its relatively unsatisfactory performance in spring, fall, and winter -- still outperforms any fixed solar panel, but it captures about 86% of the energy captured by the AADAT system.

An important factor to consider in solar farm design is the choice of the inter-row spacing to avoid significant energy loss due to shading of adjacent rows in early morning and late afternoon. But you don't want the distance between two rows to be too far as the rows will occupy a large land area that makes no economic sense. With Energy3D, we can easily investigate the change of the energy output with regard to the change of the inter-row spacing. Figure 4 shows the gain from HSAT is greatly reduced when the rows are too close, essentially eliminating the advantages of using solar trackers. Despite of their ability to track the sun, HSATs still require space to achieve the optimal performance.

Modeling dual-axis solar trackers in Energy3D

Fig. 1: Solar panel arrays in Energy3D
A solar tracker is a system that automatically turns a solar panel or a reflector toward the sun in order to maximize the energy output of a solar power station. It is often said to be inspired by the sunflower.

In general, trackers can be categorized into two types: single-axis trackers and dual-axis trackers. Single-axis trackers have one degree of freedom that acts as an axis of rotation. The axis of rotation of single-axis trackers typically points to true north. Dual-axis trackers, on the other hand, have two degrees of freedom that act as axes of rotation. These axes are typically perpendicular to each other such as those in the altazimuth system. Single-axis trackers cannot exactly follow the sun but dual-axis trackers can.

Dual-axis trackers have been implemented in our Energy3D software for photovoltaic (PV) solar panels, as is shown in the video embedded in this post.

Energy3D has a variety of built-in tools for creating PV array layouts and analyzing their daily and annual yields. Figure 2 shows the comparison of the output of a solar panel rotated by a dual-axis tracker and those of solar panels fixed at different tilt angles (0°, 15°, 30°, 45°, 60°, 75°, and 90°) on March 22, June 22, September 22, and December 22, respectively, in Boston, MA. Not surprisingly, the result shows that the solar panel produces the most energy in June and the least in December.

Fig.2 A tracking PV panel vs. fixed panels at different tilt angles
When analyzing the benefit of using a solar tracker, we found that in June, a fixed panel at the optimal tilt angle produces about 70% of the energy produced by a panel oriented by a dual-axis tracker. That percentage increases to about 75% in March and September and to about 90% in December. This means that the benefit of using a tracker, compared with the maximal output of a fixed panel with the optimal tilt angle, will be significant in the summer but gradually diminish when the winter comes.

Having to manually adjust the tilt angles for a lot of solar panels four times a year sounds like too laborious to be practical. If that is out of the question, it would then be fair to compare the output of a solar panel with a tracker and those fixed at the same tilt angle throughout the year. Figure 3 shows that the total annual yield of a solar panel at the best tilt angle produces only 70% of the energy produced by a solar panel rotated by a tracker. In other words, a solar panel rotated by a tracker generates about 42% more energy compared with a solar panel fixed at the optimal tilt angle on the annual basis.
Fig.3 Annual outputs: tracker vs. fixed

Does the additional energy that solar trackers help generate worth the money (initial investment plus maintenance of moving parts) they cost? You may have heard that, as solar panels get cheaper and cheaper, trackers become less and less favorable. I want to offer a different point of view.

Surely, the return of the investment on solar trackers depends on a number of factors such as the price of solar panels. But one of the most important factors is the solar cell efficiency of the solar panels they rotate. The higher the efficiency is, the more the extra electricity a tracker can yield to offset the cost and make a profit. With the solar cell efficiency for commercial panels breaks record every year (reportedly 31.6% in July 2016), what didn't make economic sense in the past looks lucrative now. The future of the market for solar trackers will only look brighter.

Solar Engineering Summer Camp 2016


Computer modeling with Energy3D
The free Solar Engineering Summer Camp offered by the Concord Consortium was an intensive week-long event that focused on learning and applying solar science, 3D modeling, and engineering design. It featured a solar engineer from a leading solar company as a guest speaker. The activities included hands-on and computer-based activities that were designed to inspire and empower children to solve real-world problems and become change makers who will hopefully create a more sustainable future.

Poster session with parents
This year, eleven children (age 11-16) participated in the event that took place on Concord Consortium's east coast campus. Participants became the science advisors for their parents, investigating how their own houses could be turned into a small power station that supplies the energy needed.

A 3D house created and studied in the event
Using Google Earth and our Energy3D software, they made 3D computer models of their own houses, designed different solar array layouts, and then ran computer simulation to evaluate and compare their yields. They performed cost-benefit analysis of different solutions, based on which they completed solar assessment reports about the solarization potential of their own homes. At last, they presented their results in a poster session and discussed their findings with their parents.

The parents were generally very supportive. Some even helped their kids measure the dimensions of their houses (unfortunately, Google Earth does not provide sufficient information for students to retrieve the geometry of their houses; so some kids must learn how to measure the heights of their roofs using other methods such as photogrammetry).

3D houses created by kids
How did the little science advisors do their jobs in terms of informing their parents then? When asked "Did your child’s Solar Assessment Report make you change your view or interest in solar energy?", a parent responded in the exit survey: "We already have solar panels on our house. This project allowed me to consider our energy needs and additional options for increasing our capacity to generate electricity." This example shows that even for those people who already have solar panels on their roofs, the findings from their kids might have spurred them to think about more possibilities.

As a side note, I noticed an interesting response from a parent: "She enjoyed using the software to design our house. She said it was an interesting topic, but she cautioned me not to rely solely on her calculations to base our decision on whether to convert to solar energy use for our house." The kid is right -- all models have limitations and engineers must use caution. A science advisor should inform her advisee that a model may fail.

Integrating Solarize Mass and STEM education through powerful simulation technologies

Fig.1: Solar simulation in Energy3D.
Solarize Mass is a program launched by the Massachusetts Clean Energy Center that seeks to increase the adoption of small-scale solar electricity in participating communities. In 2016, the towns of Natick and Bolton were selected to pilot for Solarize Mass. According to the Town of Natick, "Solarize Mass Natick is a volunteer initiative run by Natick residents. Our goal is to make going solar simple and affordable for Natick residents and small business owners as part of a 2016 state-sponsored program. But it is a limited-time program: the deadline for requesting a site visit is August 1, 2016."

Solar energy does not need to be a limited-time offer. The question is to figure out how residents can do their own site assessment while the guys are not in town to give free consultation. Sure, residents can use Google's Sunroof to quickly check whether solar is right for them (if their areas are covered by Sunroof). But what Sunroof does is only to screen a building based on its solar potential, not to provide a more informative engineering solution to help homeowners make up their minds. The latter has to be done by a solar installer who will provide the PV array layout, the output projection, the financial analysis, etc., in order to run a convincing business. But this is a time-consuming process that poses financial risks to solar installers if the homeowners end up backing out. So we need to find some other creative solutions.

Fig. 2: Student work from a Massachusetts school in 2016.
Funded by the National Science Foundation (NSF), we have been working at the Concord Consortium on exploring meaningful ways to combine solar programs with STEM education that will effectively boost each other. We have been developing a powerful computer-aided engineering system called Energy3D that essentially turns an important part of solar engineering's job into something that even a middle or high school student can do (Figure 1). In a recent case study, we found that Energy3D's prediction outperforms a solar installer's prediction for my colleague's house in Bolton, MA. In a pilot test in an Eastern Massachusetts school in June 2016, we found at least 60% of the 27 ninth graders who participated in the 8-hour activity succeeded -- with various degrees -- in coming up with a 3D model of her/his house and designing a solarization solution based on it (Figure 2). Giving the fact that they had to learn both Google Earth and Energy3D in a very short time and then perform a serious job, this result is actually quite encouraging. Our challenge in the NSF-funded project is to improve our technology, materials, and pedagogy so that more students can do a better job within a limited amount of time in the classroom.

With this improving capacity, we are now asking this question: "What can middle or high school students empowered by Energy3D do for the solarization movement?" Fact is that, there are four million children entering our education system each year in the US. If 1% of them become little solar advocates or even solar engineers in schools, the landscape for green energy could be quite different from what it is now.

Fig. 3: Energy3D supports rich design.
Starting from three years ago, STEM education in the US is required to incorporate science and engineering practices extensively into the curriculum by the Next Generation Science Standards (the equivalent of Common Core for science). The expectation is that students will gradually think and act like a real scientist and engineer through their education careers. To accomplish this goal, an abundance of opportunities for students to practice science and engineering through solving authentic real-world problems will need to be created and researched. On July 8, 2016, NSF has also made this clear in the a proposal solicitation letter about what they call Change Makers, which states: "Learners can be Change Makers, identifying and working to solve problems that matter deeply to them, while simultaneously advancing their own understanding and expertise. Research shows that engaging in real world problem solving enhances learning, understanding, and persistence in STEM." Specifically, the letter lists "crowd-sourced solutions to clean energy challenge through global, public participation in science" as an example topic. An NSF letter like this usually reflects the thinking and priority of the funding agency. From a practical point of view, considering the fact that the choices for engineering projects for schools are currently quite limited, there is a good chance that schools would welcome solar engineering and other types of engineering as an alternative to, say, robotic engineering.

The overlap of timing for the ongoing solarization movement and the ongoing education overhaul poses a great opportunity for uniting the two fronts. We envision that Energy3D will play a vitally important role on making this integration a reality because 1) Energy3D is based on rigorous science and engineering principles, 2) its accuracy is comparable to that of other industry-grade simulation tools, 3) it simulates what solar engineers do in the workplace, 4) it covers the education standards of scientific inquiry and engineering design, 5) it supports many architectural styles (Figure 3), 6) it works just like a design game (e.g., Minecraft) for children, and 7) last but not least -- it is free! With more development under way and planned for the future, Energy3D is also on the way to become a citizen science platform for anyone interested in residential and commercial solar designs and even solar power plant designs.

Exactly how the integration will be engineered is still a question under exploration. But we are very excited about all the possibilities ahead and we are already in an early phase to test some preliminary ideas. If you represent a solar company and are interested in this initiative, please feel free to contact us.

Simulating photovoltaic power plants with Energy3D

Modeling 1,000 PV panels in a desert
Solar radiation simulation
We have just added new modeling capacities to our Energy3D software for simulating photovoltaic (PV) power stations. With these additions, the latest version of the software can now simulate rooftop solar panels, solar parks, and solar power plants. Our plan is to develop Energy3D into a "one stop shop" for solar simulations. The goal is to provide students an accessible (yet powerful) tool to learn science and engineering in the context of renewable energy and professionals an easy-to-use (yet accurate) tool to design, predict, and optimize renewable energy generation.

Users can easily copy and paste solar panels to create an array and then duplicate arrays to create more arrays. In this way, users can rapidly add many solar panels. Each solar panel can be rotated around three different axes (normal, zenith, and azimuth). With this flexibility, users can create a PV array in any direction and orientation. At any time, they can adjust the direction and orientation of any or all solar panels.
PV arrays that are oriented differently


What is in the design of a solar power plant? While the orientation is a no-brainer, the layout may need some thinking and planning, especially for a site that has a limited area. Another factor that affects the layout is the design of the solar tracking system used to maximize the output. Also, considering that many utility companies offer peak and off-peak prices for electricity, users may explore strategies of orienting some PV arrays towards the west or southwest for the solar power plant to produce more energy in the afternoon when the demand is high in the summer, especially in the south.

Rooftop PV arrays
In addition to designing PV arrays on the ground, users can do the same thing for flat rooftops as well. Unlike solar panels on pitched roofs of residential buildings, those on flat roofs of large buildings are usually tilted.

We are currently implementing solar trackers so that users can design solar power plants that maximize their outputs based on tracking the sun. Meanwhile, mirror reflector arrays will be added to support the design of concentrated solar power plants. These features should be available soon. Stay tuned!