Abstract
Power dispatch is a core problem for smart grid operations. It aims to provide optimal operating points within a transmission network while power demands are changing over space and time. This function needs to be run every few minutes throughout the day; thus, a fast, accurate solution is of vital importance. However, due to the complexity of the problem, reliable and computationally efficient solutions are still under development. This issue will become more urgent and complicated as the integration of intermittent renewable energies increases and the severity of uncertain disasters gets worse. With the recent success of artificial intelligence in various industries, deep learning becomes a promising direction for power engineering as well, and the research community begins to rethink the problem of power dispatch. This paper reviews the recent progress in smart grid dispatch from a deep learning perspective. Through this paper, we hope to advance not only the development of smart grids but also the ecosystem of artificial intelligence.
摘要
电力调度是智能电网运行的一大核心问题, 其目的是在满足时空变化的电力负荷条件下提供电网的最优运行点。这一功能需要在一天内每隔几分钟运行一次, 因此快速、准确的调度决策方法至关重要。但是, 由于问题的复杂性, 可靠且高效的决策方法仍在不断探索的过程中。随着可再生能源的大规模并网以及灾害性气候的不断恶化, 智能电网对调度决策方法提出了更为严苛的要求。近年来, 以深度学习为代表的人工智能方法在不少领域取得巨大成功, 因此深度学习也被电气工程领域寄予厚望, 国内外研究者开始重新思考智能电网的调度决策问题。本文即从深度学习这一角度对智能电网调度决策相关研究进行综述, 旨在促进智能电网领域发展的同时促进人工智能生态的发展。
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Project supported by the National Natural Science Foundation of China (Nos. 52007173 and U19B2042), the Zhejiang Provincial Natural Science Foundation of China (No. LQ20E070002), and Zhejiang Lab’s Talent Fund for Young Professionals (No. 2020KB0AA01)
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Gang HUANG drafted the paper. Gang HUANG, Fei WU, and Chuangxin GUO revised and finalized the paper.
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Gang HUANG, Fei WU, and Chuangxin GUO declare that they have no conflict of interest.
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Huang, G., Wu, F. & Guo, C. Smart grid dispatch powered by deep learning: a survey. Front Inform Technol Electron Eng 23, 763–776 (2022). https://doi.org/10.1631/FITEE.2000719
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DOI: https://doi.org/10.1631/FITEE.2000719