Saturday, November 4, 2017

Energy3D allows users to select brand name solar panels

Fig. 1: 20 brand name solar panels in Energy3D
Fig. 2: The daily outputs of 20 types of solar panels
Previous versions of Energy3D were based on a generic model of solar panel, which users can set its properties such as solar cell type, peak efficiency, panel dimension, color, nominal operating cell temperature, temperature coefficient of power, and so on. While it is essential for users to be able to adjust these parameters and learn what they represent and how they affect the output, it is sometimes inconvenient for a designer to manually set the properties of a solar panel to those of a brand name.

Fig. 3: The Micky Mouse solar farm
From Version 7.4.4, I started to add support of brand name solar panels to Energy3D. Twenty brand names were initially added to this version (Figure 1). These models are: ASP-400M (Advanced Solar Photonics), CS6X-330M-FG (Canadian Solar), CS6X-330P-FG (Canadian Solar), FS-4122-3 (First Solar), HiS-M280MI (Hyundai), HiS-S360RI (Hyundai), JAM6(K)-60-300/PR (JA Solar), JKM300M-60 (Jinko), LG300N1C-B3 (LG), LG350Q1K-A5 (LG), PV-UJ235GA6 (Mitsubishi), Q.PRO-G4 265 (Q-cells), SPR-E20-435-COM (SunPower), SPR-P17-350-COM (SunPower), SPR-X21-335-BLK (SunPower), SPR-X21-345 (SunPower), TSM-325PEG14(II) (Trina Solar), TSM-365DD14A(II) (Trina Solar), VBHN330SA16 (Panasonic), and YL305P-35b (Yingli). Figure 2 shows a comparison of their daily outputs in Boston on June 22 when they are laid flat (i.e., with zero tilt angle). Not surprisingly, a smaller solar panel with a lower cell efficiency produces less electricity.

Note that these models are relatively new. There are hundreds of older and other types of solar panels that will take a long time to add. If your type is not currently supported, you can always fall back to defining it using the "Custom" option, which is the default model for a solar panel.

Adding these brand names helped me figure out that the solar panels deployed in the Micky Mouse Solar Farm in Orlando (Figure 3) are probably from First Solar -- only they make solar panels of such a relatively small size (1200 mm × 600 mm).

Saturday, October 14, 2017

The 2017 Energy Innovation Forum

We are invited to present at the Energy Innovation Forum on October 18 organized by the University of Massachusetts Lowell and the Massachusetts Clean Energy Center. The event will connect about 30 companies in Massachusetts with funders, investors, university researchers, and industry leaders to stimulate innovations in energy technologies.

For those who cannot attend the event, I am sharing our two posters here. You can also take a look at the PowerPoint slides for the Infrared Street View Project and the Virtual Solar Grid Project (we will do both oral and poster presentations). Both projects focus on developing a unique crowdsourcing model that integrates STEM education and energy research. The projects provide examples of using citizen science to support and engage a large number of students to learn science and engineering and participate in large-scale energy research.

The Infrared Street View Project will support research and education in the field of energy efficiency whereas the Virtual Solar Grid Project will support research and education in the field of renewable energy (primarily solar energy at present). Both projects are based on cutting-edge technologies being developed in my lab.

Tuesday, September 26, 2017

The challenge to solarize the world

More and more nations and regions in the world are planning to switch their power supplies to 100% renewable resources by midcentury. There has been, however, a well-publicized debate among scientists about the feasibility of powering the entire United States with only wind, water, and solar energy, triggered mostly by a recent paper by Stanford professor Mark Jacobson and colleagues. Both proponents and opponents are leading energy researchers who support their claims with sophisticated computational models. Given the magnitude and complexity of the problem, there will likely be no clear winner in the near future. But the debate will continue to influence our energy and environmental policies in the years to come.

Since the world also belongs to the young, we are obliged to find a way to engage them in this high-stakes debate. Regardless of the sides people take, few would dispute the strategic importance of educating and preparing energy consumers and workforce of tomorrow. Motivating youth is so vital in Bill Gates’ call for an “energy miracle” that he urged high school students to “get involved” in the energy quest in his 2016 annual letter. But, apart from becoming a conscientious user of energy, how can students make meaningful contributions?

Fig. 1: Energy3D covers nearly 600 regions in 185 countries.
We envision a cyberinfrastructure that works like an “Energy Minecraft” to inspire and support millions of students to take on the energy challenge at the grassroots level on a global scale. On this platform, students will learn basic science concepts and engineering principles. Equipped with the knowledge and skills, they will then crowd-design an unprecedentedly fine-grained computational model that consists of millions of virtual solar panels, reflecting mirrors, and wind turbines accurately positioned around the world and connected to virtual storages and grids. A multiscale model with all these low-level details does not exist yet, but it may be a holy grail in energy research that can potentially settle the case and even provide a blueprint going forward to a 100% renewable energy future if possible at all.

This article introduces the Solarize Your World program, the first step towards realizing the above vision. Although the program currently focuses on solar energy, it has the essential elements of a computational model capable of supporting both STEM education and energy research. And it can be extended to include other renewables such as wind, hydroelectric, and geothermal energy.

The complexity of modeling solar power in the real world

Fig. 2: Learn, apply, and explore
The sun is a gigantic nuclear fusion reactor in the sky that emits a massive amount of energy. Elon Musk has famously asserted that covering “a fairly small corner” of a state like Nevada with solar panels can generate enough energy for the whole country. This makes you wonder what scientists are really debating about.

It turns out that building a reliable solar infrastructure is not as simple as laying down billions of solar panels in a square of 100×100 miles. There are countless technical, economic, and social constraints for solar deployment in reality. For example, people do not have unlimited space and budgets. Some are concerned about the aesthetics of buildings and landscapes with solar panels in sight. Governmental policies drive the cost of solar energy, hence people’s interest, up and down. Energy storage is needed to overcome solar intermittency to provide electricity after sun-set and grid stability at all time. A significant amount of energy is lost during the transmission from utility-scale solar power plants to population centers. All things considered, we have a problem far more complicated than Musk’s ballpark statement. This is why the National Renewable Energy Laboratory has been conducting research on estimating the solar energy potential of the country (e.g., see "Rooftop Solar Photovoltaic Technical Potential in the United States: A Detailed Assessment" by Pieter Gagnon, Robert Margolis, Jennifer Melius, Caleb Phillips, and Ryan Elmore in 2016).

A crowdsourcing model that integrates education and research

Fig. 3: Photovoltaic solar farms in Energy3D
A more accurate assessment of the planet’s true solar potential is to identify all possible locations where suitable types of solar power can be realistically deployed and compute their minute-by-minute outputs to global grids and storages for a cycle of 24 hours under typical meteorological conditions. To evaluate the cost effectiveness of this giant distributed network, a mix of financing models driven by local economics and policies can be used to estimate the scale of investment that needs to be made over a certain period of time. Creating such a multiscale, time-dependent model with details down to instantaneous outputs and levelized costs of individual solar modules is a daunting task that no single researcher can do. But we can call for help from millions of students who know and care about their corners of the world more than any outsider. The challenge is to teach them the science and empower them with appropriate engineering tools so that they can join the energy quest.

Solarize Your World is based on our Energy3D software, a revolutionary CAD tool for anyone to design any type of solar power system in cyberspace and calculate its hourly, daily, or yearly out-puts based on numerical simulation from first principles. With weather data of nearly 600 regions in 185 countries (Figure 1), Energy3D can produce satisfactory results for most parts of the inhabited world, enabling millions to work on local projects. The ultimate goal of Energy3D is to turn the tedious job of engineering design into a fun game like Minecraft, making learning, discovery, and invention playful experiences for all.

A curriculum for learning and practicing science and engineering

Fig. 4: Concentrated solar power plants in Energy3D
For students to succeed in creating authentic models of solar energy systems valuable to research, Solarize Your World provides comprehensive curriculum materials and classroom-to-afterschool pathways (Figure 2) that lead students to: 1) design solar energy systems for their homes, schools, villages, and cities; 2) design any type of photovoltaic and concentrated solar power plants wherever applicable; and 3) communicate their designs to potential stakeholders whenever appropriate. Figures 3 and 4 show solar power systems of different types and sizes on top of satellite images of the chosen sites from Google Maps (some of these systems were modeled or designed by students in our 2017 pilot tests).

The Solarize Your World curriculum consists of three connected parts. Part I teaches students the needed disciplinary core ideas, crosscutting concepts, and science and engineering practices as defined in the Next Generation Science Standards. The disciplinary core ideas cover earth science, heat transfer, geometric optics, and electric circuits that are fundamental to solar power. The crosscutting concepts include energy and systems that are necessary to understanding how the energy from the sun can be converted into electricity to power the world. This part also strives to familiarize students with the practices of scientific inquiry and engineering design. Part II provides scores of open-ended, real-world projects for students to choose. For instance, students can design solar energy systems for their own homes or schools. If students cannot finish a project within the given timeframe in the classroom or wish to undertake more projects out of school, Part III supports them to continue in an online community, possibly in collaboration with many other participants similar to the case of Minecraft.

The road ahead

The U.S. Department of Energy announced on September 12, 2017 that the 2020 utility-scale solar cost goal set by its SunShot Initiative had been met three years earlier. The price of utility-scale solar energy has now fallen to six cents per kilowatt hour. Despite this phenomenal plummet, the road to a 100% renewable energy future is still unclear and debatable. We invite students and teachers worldwide to join our Solarize Your World initiative to pave the way. Rarely have students been given a chance to help answer a question so crucial to humanity.

Thursday, September 14, 2017

Deciphering a solar array surprise with Energy3D

Fig. 1: An Energy3D model of the SAS solar farm
Fig. 2: Daily production data (Credit: Xan Gregg)
SAS, a software company based in Cary, NC, is powered by a solar farm consisting of solar panel arrays driven by horizontal single-axis trackers (HSAT) with the axis fixed in the north-south direction and the panels rotating from east to west to follow the sun during the day. Figure 1 shows an Energy3D model of the solar farm. Xan Gregg, JMP Director of Research and Development at SAS, posted some production data from the solar farm that seem so counter-intuitive that he called it a "solar array surprise" (which happens to also acronym to SAS, by the way).

The data are surprising because they show that the outputs of solar panels driven by HSAT actually dip a bit at noon when the intensity of solar radiation reaches the highest of the day, as shown in Figure 2. The dip is much more pronounced in the winter than in the summer, according to Mr. Gregg (he only posted the data for April, though, which shows a mostly flat top with a small dip in the production curve).

Fig. 3: Energy3D results for four seasons.
Anyone can easily confirm this effect with an Energy3D simulation. Figure 3 shows the results predicted by Energy3D for 1/22, 4/22, 7/22, and 10/22, which reveal a small dip in April, significant dips in January and October, and no dip at all in July. How do we make sense of these results?

Fig. 4: Change of incident sunbeam angle on 1/22 (HSAT).
One of the most important factors that affect the output of solar panels, regardless of whether or not they turn to follow the sun, is the angle of incidence of sunlight (the angle between the direction of the incident solar rays and the normal vector of the solar panel surface). The smaller this angle is, the more energy the solar panel receives (if everything else is the same). If we track the change of the angle of incidence over time for a solar panel rotated by HSAT on January 22, we can see that the angle is actually the smallest in early morning and gradually increases to the maximum at noon (Figure 4). This is opposite to the behavior of the change of the angle of incidence on a horizontally-fixed solar panel, which shows that the angle is the largest in early morning and gradually decreases to the minimum at noon (Figure 5). The behavior shown in Figure 5 is exactly the reason why we feel the solar radiation is the most intense at noon.

Fig. 5: Change of incident sunbeam angle on 1/22 (fixed)
If the incident angle of sunlight is the smallest at 7 am in the morning of January 22, as shown in Figure 4, why is the output of the solar panels at 7 am less than that at 9 am, as shown in Figure 3? This has to do with something called air mass, a convenient term used in solar engineering to represent the distance that sunlight has to travel through the Earth's atmosphere before it reaches a solar panel as a ratio relative to the distance when the sun is exactly vertically upwards (i.e. at the zenith). The larger the air mass is, the longer the distance sunlight has to travel and the more it is absorbed or scattered by air molecules. The air mass coefficient is approximately inversely proportional to the cosine of the zenith angle, meaning that it is largest when the sun just rises from the horizon and the smallest when the sun is at the zenith. Because of the effect of air mass, the energy received by a solar panel will not be the highest at dawn. The exact time of the output peak depends on how the contributions from the incidental angle and the air mass -- among other factors -- are, relatively to one another.

So we can conclude that it is largely the motion of the solar panels driven by HSAT that is responsible for this "surprise." The constraint of the north-south alignment of the solar panel arrays makes it more difficult for them to face the sun, which appears to be shining more from the south at noon in the winter.

If you want to experiment further, you can try to track the changes of the incident angle in different seasons. You should find that the change of angle from morning to noon will not change as much as the day moves to the summer.

This dip effect becomes less and less significant if we move closer and closer to the equator. You can confirm that the effect vanishes in Singapore, which has a latitude of one degree. The lesson learned from this study is that the return of investment in HSAT is better at lower latitudes than at higher latitudes. This is probably why we see solar panel arrays in the north are typically fixed and tilted to face the south.

The analysis in this article should be applicable to parabolic troughs, which follow the sun in a similar way to HSAT.