Smart windows — windows that use solar cell technology to convert sunlight into electricity — present the opportunity to leverage windows as energy sources. 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 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.
The design framework is customizable and can be applied to virtually any building to maximize the amount of sunlight in a room or minimize heating or cooling efforts. The scientists demonstrated a holistic approach to window design to maximize the overall energy efficiency of buildings while considering lighting and temperature preferences. 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. In some scenarios, 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 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 algorithm uses computational mechanisms that resemble reproduction and genetic mutation to determine the optimal combination of each design parameter for a certain scenario.
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 that 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. This enables the window to systematically allow less infrared transmission in the summer and more in the winter to save energy consumption for temperature regulation while optimizing the visible transmission for the purpose of indoor lighting and energy harvesting.
The synthesis methods the scientists used to produce the window prototype mimic common industrial-level manufacturing processes that 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 pre-existing windows.
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