Customizable smart window technology could improve energy efficiency of buildings

Date:
July 14, 2020
Source:
DOE/Argonne National Laboratory
Summary:
Scientists combined solar cell technology with a novel optimization
approach to develop a smart window prototype that maximizes design
across a wide range of criteria.



FULL STORY ==========================================================================
A customizable smart window harnesses and manipulates solar power to
save energy and cut costs.


========================================================================== Windows play multiple crucial roles in our homes. They illuminate,
insulate and ventilate our spaces while providing views of -- and
protection from -- the outdoors. Smart windows, or windows that use
solar cell technology to convert sunlight into electricity, present the additional opportunity to leverage windows as energy sources.

However, incorporating solar cells into windows while balancing the other complex, and often conflicting, roles of windows proves challenging. For example, juggling luminosity preferences and energy harvesting goals
throughout changing seasons requires complex and strategic approaches
to material design.

Scientists from the U.S. Department of Energy's (DOE) Argonne National Laboratory, Northwestern University, the University of Chicago and
University of Wisconsin-Milwaukee recently combined solar cell technology
with a novel optimization approach to develop a smart window prototype
that maximizes design across a wide range of criteria.

The optimization algorithm uses comprehensive physical models and advanced computational techniques to maximize overall energy usage while balancing building temperature demands and lighting requirements across locations
and throughout changing seasons.

"This design framework is customizable and can be applied to virtually
any building around the world," said Junhong Chen, a scientist at Argonne
and the Crown Family Professor of Molecular Engineering at the Pritzker
School of Molecular Engineering at the University of Chicago. "Whether
you want to maximize the amount of sunlight in a room or minimize heating
or cooling efforts, this powerful optimization algorithm produces window designs that align with user needs and preferences." Advanced approach
to optimization


==========================================================================
The scientists demonstrated a wholistic approach to window design to
maximize the overall energy efficiency of buildings while considering
lighting and temperature preferences.

"We can regulate the sunlight in a room to ensure the desired luminosity
while managing the amount of energy the building uses for heating and
cooling," said Wei Chen, the Wilson-Cook Professor in Engineering Design
at Northwestern Engineering whose research group led the development of
the optimization approach. "Additionally, the sunlight that doesn't pass through is captured by the solar cell in the smart window and converted
into electricity." The approach, called multicriteria optimization,
adjusts thicknesses of solar cell layers in window design to meet the
needs of the user. For example, to reduce the energy required to cool
a building in the summer, the optimal window design might minimize the
amount and type of light passing through while maintaining the desired luminosity inside. On the other hand, when winter savings are a priority,
the design might maximize the amount of sunlight that passes through,
thereby reducing the energy required for heating the building.

"Rather than focusing only on the amount of electricity produced by the
solar cell, we consider the entire building's energy consumption to see
how we can best use solar energy to minimize it," said Wei Chen.

In some scenarios, for example, it might be more energy efficient to
allow a greater amount of light to pass through the window, instead of
being converted into electricity by the solar cell, in order to decrease
the electricity required for lighting and heating the building.



==========================================================================
To determine the optimal design, the algorithm incorporates comprehensive physics-based models of the interactions between light and the materials
in the smart window, as well as how the processes affect energy conversion
and light transmission. The algorithm also takes into account the varying angles at which the sun hits the window throughout the day -- and year --
in different geographical locations.

"The model we created allows for exploration of millions of unique designs
by an algorithm that mimics biological evolution," said Wei Chen. "On
top of the physics-based models, the algorithm uses computational
mechanisms that resemble reproduction and genetic mutation to determine
the optimal combination of each design parameter for a certain scenario." Promising prototype To demonstrate the feasibility of a smart window
capable of this level of customization, the scientists produced a small prototype of the window with an area of a few square centimeters.

The prototype consists of dozens of layers of varying materials that
control the amount and frequency of light passing through, as well as
the amount of solar energy converted into electricity.

One group of layers, made of a type of material called a perovskite,
comprises the window's solar cell, which harvests sunlight for energy conversion. The window prototype also includes a set of layers called
a nanophotonic coating, developed by associate professor of mechanical engineering Cheng Sun and his research group at Northwestern's McCormick
School of Engineering. The coating tunes the frequencies of light that
can pass through the window.

Each layer is tens of microns thick -- thinner than the diameter of a
grain of sand. The scientists chose an aperiodic design for the layers,
meaning each layer varies in thickness. As the angle of the sun's rays
against the window changes throughout the day and year, the aperiodic
design enables the performance of the window to vary in accordance with
the user's preferences.

"The variation in layer thickness is optimized for a wide spectrum of
change in the nature of the sunlight that reaches the window," said
Sun. "This enables us to systematically allow less infrared transmission
in the summertime and more in the wintertime to save energy consumption
for temperature regulation, while optimizing the visible transmission for
the purpose of indoor lighting and energy harvesting." The scientists optimized the prototype used in this study for a 2,000 square foot, single-story home in Phoenix. Based on experimental characterization of
the window prototype, the scientists calculated significant annual energy savings over leading commercially available window technologies. The calculations used the EnergyPlus building model, a software developed
at the National Renewable Energy Laboratory, a DOE Office of Energy
Efficiency and Renewable Energy laboratory, that estimates realistic
power consumption over time.

The synthesis methods the scientists used to produce the window
prototype mimic common industrial-level manufacturing processes, and
the scientists believe that these existing commercial processes would
allow for successful scaling of the window prototype to full-size.

Future considerations include developing the same technology in a
flexible form so that the smart window materials can be retrofitted to
cover preexisting windows.

The work was funded in part by the National Science Foundation.


========================================================================== Story Source: Materials provided by
DOE/Argonne_National_Laboratory. Original written by Savannah
Mitchem. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Chen Wang, Shuangcheng Yu, Xiaoru Guo, Tucker Kearney, Peijun
Guo, Robert
Chang, Junhong Chen, Wei Chen, Cheng Sun. Maximizing Solar Energy
Utilization through Multicriteria Pareto Optimization of Energy
Harvesting and Regulating Smart Windows. Cell Reports Physical
Science, 2020; 100108 DOI: 10.1016/j.xcrp.2020.100108 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/07/200714121744.htm

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