Wednesday, May 24, 2017

A Mickey Mouse-shaped solar farm

Fig. 1: An aerial view of the Mickey Mouse-shaped solar farm
Fig. 2: An Energy3D model of the Mickey Mouse-shaped solar farm
If I didn't tell you that this is an actual solar farm near the Epcot Theme Park in the Disney World in Orlando, Florida, you probably would think this is some kind of school project done by kids. But no, this 22-acre 5 MW project was designed and installed by Duke Energy and it has been powering Disney World's facilities since 2016 (Figure 1 is an image from Disney.com). So this is some kind of serious business and has drawn a lot of media attention. The solar farm is so new that even the latest version of Google Maps in May 2017 still does not show it (it is available through Google Maps API that we are using, though).

By shaping the beloved Mickey Mouse character with tens of thousands of solar panels, Disney World has delivered a strong message to the world that the company is committed to a sustainable future.

Fig. 3: A solar radiation heat map representation (June 22).
But who says that kids should not do this? Perhaps they couldn't do it because of the lack of appropriate support and tool. Not any more. Thanks to the support from the National Science Foundation, our powerful Energy3D software and our Solarize Your World curriculum can probably turn every wild imagination in solar power into virtual reality, particularly for children who may need more inquiry- and design-based activities that connect so deeply to their world and their future. Figure 2 shows a model of the Mickey Mouse-shaped solar farm in Energy3D and Figure 3 shows a heat map representation of the solar radiation onto the solar panel arrays.

Monday, May 22, 2017

Designing ground-mounted solar panel arrays: Part III

Fig. 1: Rows of solar panels on racks in a solar farm
The most common configuration of solar farms is perhaps arrays consisting of rows of solar panel racks such as shown in Figure 1. But have you ever thought about why? Can we challenge this conventional wisdom?

Fig.2: Cover the field with horizontally-placed solar panels
Obviously, some inter-row spacing allows for easier cleaning and maintenance and, perhaps, even integration with agricultural farming (e.g., growing mushrooms that prefer shaded areas). But let's put those benefits aside for now and just consider the energy part of the problem. Let me point out a fact: If we completely cover the entire field with solar panels with zero tilt angle and zero gap (Figure 2), we are guaranteed to capture almost every single photon that strikes the area regardless of time and location. Such a simple-minded "design" will produce the maximal output of any given field at any location and time and there is absolutely no such problem as inter-row shading. So what solar design?
Fig. 3: Comparing two hypothetical fields.

It turns out that, although the simple-minded design can surely generate maximum electricity, each individual solar panel in it does not necessarily generate a maximum amount of electricity over the course of a year, compared with other designs. In other words, it may just use more solar panels to generate more electricity. As engineering design must consider cost effectiveness and even put it as a top priority, an engineer's job is then to look for a better solution that maximizes the production of each solar panel.

Fig. 4: Compare outputs of single panels in two fields (Boston).
A great advantage of Energy3D is that it allows one to experiment with ideas rapidly. So let's create a field with tilted rows of solar panels and leave some gap between them and then use the Group Analysis Tools to compare the daily and annual outputs of individual solar panels in the two hypothetical fields (Figure 3). And let's assume the fields are in Boston.

Fig. 5: Compare outputs of single panels in two fields (Phoenix).
Figure 4 shows that the total annual output of a single solar panel in the field of tilted rows is nearly 20% higher than that of a single solar panel in the field of flat cover in Boston (42° N). In this simulation, the tilt angle was set to be equal to the latitude. This cost effectiveness is one of the main reasons why we choose tilted rows of solar panels in high-latitude areas (aside from the fact that tilted angles allow rain to wash panels more efficiently and snow to slide from them more quickly).

What about low-latitude locations?


Fig. 6: Compare outputs of single panels in two fields (Mexico).
Note that this result applies only to high-latitude areas such as Boston. If we are designing solar farms for tropical areas such as Singapore, the story may be completely different. In low-latitude areas, small or even zero tilt angles make sense. Therefore, the design principle may be to cover the field with as many solar panels as possible or to use trackers to increase individual outputs (whichever is more economic depends on the relative prices of solar panels and solar trackers that change all the time). You can experiment with Energy3D to find out at which latitude this principle starts to become dominant. Figure 5 shows that the results in cities with a lower latitude such as Phoenix (33° N) and Mexico City (19° N) in North America. In the case of Phoenix, AZ, the gain from the tilted rows drops to about 10%. In the case of Mexico City, it drops to 5%. So designing a ground-mounted solar array for Mexico may be very different from designing a ground-mounted solar array for Canada.

Thursday, May 18, 2017

National Science Foundation funds research and development of an IoT platform for smart schools

Fig. 1: A schematic illustration of IoT as a STEM learning integrator
Future sustainable and resilient infrastructure is expected to be powered by renewable energy, be able to respond intelligently to changes in the environment, and support smart and connected communities. We are pleased to announce that the National Science Foundation (NSF) has awarded our team a $2.9 million, four-year grant to explore the STEM education and workforce development challenges and opportunities in the coming transformation of our nation's infrastructure.

One of the core innovations will be a cyber-physical engineering platform for designing Internet of Things (IoT) systems that manage the resources, space, and processes of a community based on real-time analysis of data collected by various sensors. This innovation is potentially transformative as it can turn the entire building of a home, the entire campus of a school, or the entire area of a town into an engineering laboratory with virtually unlimited opportunities for learning, research, and exploration.

Fig. 2: A possible IoT system for managing a parking lot
Designing an IoT system provides plenty of opportunities to learn math, science, engineering, and computation practices in an integrated fashion, rather than in isolation. Working with sensors allows students to learn the science behind them through inquiry. For example, to calibrate an IoT system, students must understand what specific variables the sensor data represent scientifically. They must analyze the data to explore in what ranges the variables are supposed to vary in different scenarios in order to determine which type of response should be triggered, to what, and when. The acquired knowledge is then applied to the design of an IoT system, which requires engineering design thinking to make trade-off decisions, optimize system performance, and achieve cost effectiveness. Finally, the control, response, and integration of the entire system are realized through computer programming that deals with all foreseeable complexities. The overlaps among three basic skills—scientific reasoning, design thinking, and computational thinking—supported by the IoT platform provide researchers an opportunity to study their integration, as illustrated in Figure 1. (In fact, mathematical thinking is also involved, but let's just leave that out for now.)

This project is unique to engineering and computer science education because IoT is not only a crucial part of electrical engineering and information technology, but it is also one of the few ways through which computer programming can be directly linked to scientific inquiry and engineering design in the material world. Figure 2 provides an example.

This work is supported by the NSF under grant number 1721054. Any opinions, findings, and conclusions or recommendations expressed in this paper, however, are those of the author(s) and do not necessarily reflect the views of the NSF.

Monday, May 15, 2017

Energy2D included in the technology toolkit for sustainable design at a large architecture firm

A material thermal bridge
AECbytes just published an article written by its editor Dr. Lachmi Khemlani, which introduces the technology toolkit for sustainable design at Orcutt Winslow Partnership (OWP), one of the largest architecture firms in the Southwest and ranked in the top 100 firms in the U.S.

A geometric thermal bridge
Dr. Khemlani's article explores what these applications are and how OWP is deploying them to design more energy-efficient buildings. I am honored to learn from her article that Energy2D is part of the OWP toolkit for thermal bridge analysis. It is my great pleasure to know that the humble tool I created from scratch has found its way to professional workplaces. To some extent, it doesn't surprise me that engineers and architects have found it useful as the conduction part of the Energy2D simulation engine is pretty decent, highly accurate, and unconditionally stable.

The first image of this article shows an Energy2D simulation of the material thermal bridge (discontinuities in thermal conductivity of materials such as steel studs in walls). The second image shows an Energy2D simulation of the geometric thermal bridge (discontinuities in cross section of heat flow such as junctions of two planes).

The following is an excerpt from Dr. Khemlani's article:
"Another ArchiCAD feature that OWP uses extensively is its Thermal Bridging analysis tool, which allows a 2D heat-flow simulation to be run on any element to identify those parts of the building that are responsible for heat loss and might cause vapor condensation as well as other unwanted effects. Again, OWP uses this in conjunction with Energy2D, another tool that provides not only thermal bridging analysis but can also run sophisticated CFD (computation fluid dynamics) simulations, allowing OWP to test out different materials and composites for building components."