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.
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.
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.
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.
