Category Archives: Molecular Workbench

Visualizing design issues in heliostat layouts of concentrated solar power stations with Energy3D

Fig. 1: Visualizing shadowing loss
As a one-stop-shop for solar solutions, Energy3D supports the design of concentrated solar power (CSP) stations. Although the main competitor of the CSP technology, the photovoltaic (PV) power stations, have become dominant in recent years due to the plummet of PV panel price, CSP has its own advantages and potential, especially in energy storage. According to the US Department of Energy, the levelized cost of electricity (LCOE) for CSP has dropped to 13 cents per kWh in the US in 2015, comparable to the LCOE for PV (12 cents per kWh). In general, it is always better to have options than having none. A combination of PV and CSP stations may be what is good for the world: CSP can complement PV to generate stable outputs and provide electricity at night. As a developer of solar design and simulation software, we are committed to supporting the research, development, and education of all forms of solar technologies.

Numerical simulation plays an important role on designing optimal CSP stations. Concentrated solar power towers are the first type of CSP stations covered by the modeling engine of Energy3D. This blog post shows some progress towards the goal of eventually building a reliable simulation and visualization kernel for CSP tower technology in Energy3D. The progress is related to the study of heliostat layouts (the heat transfer part is yet to be built).

Numerous studies of heliostat layouts have been reported in literature in the past three decades, resulting in a variety of proposals for minimizing the land use and/or maximizing the energy output (see a recent review: Li, Coventry, Bader, Pye, & Lipiński, Optics Express, Vol. 24, No. 14, pp. A985-A1007, 2016). The latest is an interesting biomimetic pattern suggested by Noone, Torrilhon, and Mitsos (Solar Energy, Vol. 862, pp. 792–803, 2012), which resembles the spiral patterns of a sunflower head (each floret is oriented towards the next by the golden angle of 137.5°, forming a Fermat spiral that is probably Mother Nature's trick to ensure that each seed has enough room to grow and fair access to sunlight).
Fig. 2: Visualizing blocking loss

If you haven't worked in the field of solar engineering, you may be wondering why there has been such a quest for optimal layouts of heliostats. At first glance, the problem seems trivial -- well, a tower-based CSP station is just a gigantic solar cooker, isn't it? But things are not always what they seem.

Fig. 3: Annual outputs of the heliostats in Fig. 2
The design of the heliostat layout is in fact a very complicated mathematical problem. We have some acres of land somewhere to begin with. The sun moves in the sky and its trajectory varies from day to day. But that is OK. The heliostats can be programmed to reflect sunlight to the receiver automatically. These all sound good until we realize that the heliostats' large reflectors can cast shadow to one another if they are too close or the sun is low in the sky (Figure 1). Like the case of PV arrays, shadowing causes productivity loss (but luckily, reflectors -- unlike solar panels based on strings of connected solar cells -- do not completely lose power if only a part of it is in the shadow).

Fig. 4: Visualizing cosine efficiency
Unlike the case of PV arrays, heliostats have an extra problem -- blocking. A heliostat must reflect the light to the receiver at the top of the tower and that path of light can be blocked by its neighbors. Of course, we rarely see the case of complete blocking. But if a portion of the reflector area is denied optical access to the receiver, the heliostat will lose some productivity. Energy3D can visualize this loss on each heliostat reflector. The upper image of Figure 2 shows the insolation to the reflectors whereas the lower one shows the portion of the insolation that actually reaches the receiver. Figure 3 shows a comparison of the outputs of the heliostats over the course of a year. As you can see, the blue parts of the reflectors can never bounce light to the receiver because the heliostats in front of them block the reflection path for the lower parts of those heliostats. The way to mitigate this issue is to gradually increase the spacing between the heliostats when they are farther away from the tower.
Fig. 5: Cosine efficiency is lower in the winter

Another problem with CSP tower technology is the so-called cosine efficiency. As we know, the insolation onto a surface is maximal when the surface directly faces the sun (this is known as the projection effect). In the northern hemisphere, however, the heliostats to the south of the tower (the south field) cannot face the sun directly as they must be positioned at an angle so that the incident sunlight can be reflected to a northern position (where the receiver is located). Figure 4 shows a visualization of the cosine effect and Figure 5 shows the comparison of the annual outputs of the heliostats. Clearly, the cosine efficiency is the lowest in the winter and the highest in the summer.

Fig. 6: Semicircular layout in the north field
Does the cosine efficiency mean that we should only deploy heliostats in the north field as is shown in Figure 6? This depends on a number of factors. Yes, the cosine efficiency does reduce the output of a heliostat in the south field in the winter (maybe early spring and late fall, too), but a heliostat far away from the tower in the north field also produces less energy. For a utility-scale CSP station that must use thousands of heliostats, the part of the south field close to the tower may not be such a bad place to put heliostats, compared with the part of the north field far away from the tower. This is more so when the site is closer to the equator. If the site is at a higher latitude to the point that it makes more sense to deploy all heliostats in the north field, dividing the site into multiple areas and constructing a tower for each area may be a desirable solution. The downside is that additional towers will increase the constructional cost.

We now multiply these three problems (shadowing, blocking, and cosine effect) with thousands of heliostats, confine them within an area of a given shape, and want to spend as less money as possible while producing as much electricity as possible. That is the essence of the mathematical challenge that we are facing in CSP field design. With even more functionalities to be added in the future, Energy3D could become a powerful design tool that anyone can use to search for their own solutions.

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 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.

Simulating concentrated solar power towers with Energy3D

Concentrated solar power (CSP) systems generate electricity using arrays of mirrors to concentrate sunlight shed on a large area onto a small area. The concentrated light is converted into thermal energy, which then drives a heat engine connected to an electrical power generator. Put it simply, a CSP power station operates like a solar cooker that you might have made in a high school science project. You can think of it as a gigantic solar cooker.


But a small science idea like this could turn into big money. For example, the Ivanpah Solar Power Facility in the California Mojave Desert, which drew $2.2 billion of investment, generates 392 megawatts (MW) -- enough to power hundreds of thousands of homes. As of 2016, the largest CSP project in the world is the Ouarzazate Solar Power Station in Morocco, which is expected to output 580 MW at peak and cost about $9 billion. Globally, CSP power stations will generate 4,705 MW this year.


CSP stations do not need to be only large-scale. Small-scale CSP stations (below 1 MW, on-grid or off-grid) may provide more flexible and affordable solutions to communities, especially those in rural areas. They provide attractive alternatives to photovoltaic power stations. Reflecting mirrors would probably cost less and last longer than solar panels and there is little to no concern of outdated or degraded efficiency (reflectivity loss may be less than 1% after 10 years of exposure to UV). The latter is an issue for solar panels if you consider that, in just six years, the latest 24.1% of solar cell efficiency of commercial panels in 2016 (UPDATE: In July, Hanergy debuted the 31.6% efficiency solar cells for their solar cars!) almost render those 12%-efficiency panels installed in 2010 obsolete and more breakthroughs forecast down the road will only make the old ones look less pretty.

To support the exploration of all kinds of solar energy exploitation, we have added the initial capacity to model CSP power stations in our Energy3D software, which is intended to be a "one-stop-shop" for solar energy modeling and design. This includes the capability of adding mirrors, heliostats, and power towers and analyzing the outputs as a function of time, location, and weather. This article shows some of the graphic effects of solar power towers (with more than 500 reflectors, each of which has the size of 2 by 3 meters, amounting to a total reflective area of more than 3,000 square meters). The four images above demonstrate how heliostats change the orientations of the reflectors at different times of the day (the selected date is June 22 and the selected location is Phoenix, AZ). The images show a simple circular field layout. In reality, radial stagger layouts that minimize shadow loss and block loss and maximize cosine efficiency are commonly used.

In the months to come, we plan to enhance Energy3D's ability to support a variety of field layout designs for power towers and model various configurations of solar thermal power (e.g., parabolic trough and Fresnel reflectors).

I have blogged about Energy3D's capacity to simulate large-scale photovoltaic power stations. This new capacity of simulating CSP stations has enabled Energy3D to model and design two of the three main types of solar power plants (the remaining one is solar updraft tower, or solar chimney, which you will also be able to model in Energy3D in the future).

Updates: 

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!

Energy3D makes designing realistic buildings easy

The annual yield and cost benefit analyses of rooftop solar panels based on sound scientific and engineering principles are critical steps to the financial success of building solarization. Google's Project Sunroof provides a way for millions of property owners to get recommendations for the right solar solutions.



Another way to conduct accurate scientific analysis of solar panel outputs based on their layout on the rooftop is to use a computer-aided engineering (CAE) tool to do a three-dimensional, full-year analysis based on ab initio scientific simulation. Under the support of the National Science Foundation since 2010, we have been developing Energy3D, a piece of CAE software that has the goal of bringing the power of sophisticated scientific and engineering simulations to children and laypersons. To achieve this goal, a key step is to support users to rapidly sketch up their own buildings and the surrounding objects that may affect their solar potentials. We feel that most CAD tools out there are probably too difficult for average users to create realistic models of their own houses. This forces us to invent new solutions.

We have recently added countless new features to Energy3D to progress towards this goal. The latest version allows many common architectural styles found in most parts of the US to be created and their solar potential to be studied. The screenshots embedded in this article demonstrate this capability. With the current version, each of these designs took myself approximately an hour to create from scratch. But we will continue to push the limit.

The 3D construction user interface has been developed based on the tenet of supporting users to create any structure using a minimum set of building blocks and operations. Once users master a relatively small set of rules, they are empowered to create almost any shape of building as they wish.

Solar yield analysis of the first house
The actual time-consuming part is to get the right dimension and orientation of a real building and the surrounding tall objects such as trees.
Google's 3D map may provide a way to extract these data. Once the approximate geometry of a building is determined, users can easily put solar panels anywhere on the roof to check out their energy yield. They can then try as many different layouts as they wish to compare the yields and select an optimal layout. This is especially important for buildings that may have partial shades and sub-optimal orientations. CAE tools such as Energy3D can be used to do spatial and temporal analysis and report daily outputs of each panel in the array, allowing users to obtain fine-grained, detailed results and thus providing a good simulation of solar panels in day-to-day operation.

The engineering principles behind this solar design, assessment, and optimization process based on science is exactly what the Next Generation Science Standards require K-12 students in the US to learn and practice. So why not ask children for help to solarize their own homes, schools, and communities, at least virtually? The time for doing this can never be better. And we have paved the road for this vision by creating one of easiest 3D interfaces with compelling scientific visualizations that can potentially entice and engage a lot of students. It is time for us to test the idea.

To see more designs, visit this page.

Personal thermal vision could turn millions of students into the cleantech workforce of today

So we have signed the Paris Agreement and cheered about it. Now what?

More than a year ago, I wrote a proposal to the National Science Foundation to test the feasibility of empowering students to help combat the energy issues of our nation. There are hundreds of millions of buildings in our country and some of them are pretty big energy losers. The home energy industry currently employs probably 100,000 people at most. It would take them a few decades to weatherize and solarize all these residential and commercial buildings (let alone educating home owners so that they would take such actions).

But there are millions of students in schools who are probably more likely to be concerned about the world that they are about to inherit. Why not ask them to help?

You probably know a lot of projects on this very same mission. But I want to do something different. Enough messaging has been done. We don't need to hand out more brochures and flyers about the environmental issues that we may be facing. It is time to call for actions!

For a number of years, I have been working on infrared thermography and building energy simulation to knock down the technical barriers that these techniques may pose to children. With NSF awarding us a $1.2M grant last year and FLIR releasing a series of inexpensive thermal cameras, the time of bringing these tools to large-scale applications in schools has finally arrived.

For more information, see our poster that will be presented at a NSF meeting next week. Note that this project has just begun so we haven't had a chance to test the solarization part. But the results from the weatherization part based on infrared thermography has been extremely encouraging!

Listen to the data with the Visual Process Analytics


Visual analytics provides a powerful way for people to see patterns and trends in data by visualizing them. In real life, we use both our eyes and ears. So can we hear patterns and trends if we listen to the data?

I spent a few days studying the JavaScript Sound API and adding simple data sonification to our Visual Process Analytics (VPA) to explore this question. I don't know where including the auditory sense to the analytics toolkit may lead us, but you never know. It is always good to experiment with various ideas.


Note that the data sonification capabilities of VPA is very experimental at this point. To make the matter worse, I am not a musician by any stretch of the imagination. So the generated sounds in the latest version of VPA may sound horrible to you. But this represents a step forward to better interactions with complex learner data. As my knowledge about music improves, the data should sound less terrifying.

The first test feature added to VPA is very simple: It just converts a time series into a sequence of notes and rests. To adjust the sound, you can change a number of parameters such as pitch, duration, attack, decay, and oscillator types (sine, square, triangle, sawtooth, etc.). All these options are available through the context menu of a time series graph.

At the same time as the sound plays, you can also see a synchronized animation of VPA (as demonstrated by the embedded videos). This means that from now on VPA is a multimodal analytic tool. But I have no plan to rename it as data visualization is still and will remain dominant for the data mining platform.

The next step is to figure out how to synthesize better sounds from multiple types of actions as multiple sources or instruments (much like the Song from Pi). I will start with sonifying the scatter plot in VPA. Stay tuned.