"Our developed technology has achieved an impressive 18.1% efficiency in QD solar cells," stated Professor Jang. "This remarkable achievement represents the highest efficiency among quantum...
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To address these gaps, this study develops a Quantum-Inspired Robust Optimization (QRO) framework that coordinates PV-H2 microgrid scheduling by dynamically adapting to real-time
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Advancements in quantum technologies holds promising solution for dealing with demanding computational complexity of power system related applications. In this article, we lay out
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This study introduces an improved quantum-behavior particle swarm optimization (IQPSO), tailored for the task of maximum power point tracking (MPPT) within photovoltaic
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Obtaining electrical power from solar energy through photovoltaic (PV) cell is an excellent alternative to harvesting energy from fossil fuels. However, efficiency is one of the main concerns as the
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Researchers have discovered that adjusting the size of quantum dots allows for tuning the wavelength of light they absorb, thus optimizing energy capture. Moreover, the arrangement of
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One way to exploit it is to use semiconductor technology through solar panels to generate clean, sustainable, and controllable energy. However, the use of such solutions must be optimised
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This study explores a quantum algorithm based on Quantum Particle Swarm Optimization (QPSO) for maximizing photovoltaic energy production under varying environmental conditions.
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In summary, this review highlights both the promise and limitations of quantum computing for power system optimization.
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Abstract: In this article, we have derived an expression for the generation rate to include critical multiple exciton generation (MEG) parameters, namely, MEGth and MEG efficiency, for a
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