A Novel Short-Term Power-Load Forecasting Method Based on High-Dimensional Meteorological Data Dimensionality Reduction and Hybrid Deep Neural Network

IF 2 4区 工程技术 Q4 ENERGY & FUELS Journal of Energy Engineering Pub Date : 2023-12-01 DOI:10.1061/jleed9.eyeng-5009
Yan Shi, SiTeng Wang, Luxi Zhang, Fengjiu Yang, Xin Luo
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基于高维气象数据降维与混合深度神经网络的新型短期电力负荷预测方法
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来源期刊
Journal of Energy Engineering
Journal of Energy Engineering 工程技术-工程:土木
CiteScore
4.10
自引率
13.60%
发文量
61
审稿时长
3.1 months
期刊介绍: The Journal of Energy Engineering reports on the scientific and engineering knowledge in the planning, development, management, and finances of energy-related programs. The journal is dedicated to civil engineering aspects of the issues, sources, and programs that are either directly related to, or can ultimately contribute to, the production, distribution, and storage of energy. Multidisciplinary subjects are especially encouraged. Original contributions are encouraged in, but not limited to, the following areas: generation of electric power; nuclear power issues; energy planning (planning for generation capacity expansions, hydropower planning, network and transmission planning, reliability); energy policy and economics (financial and customer markets, regulatory and financial issues); energy development (solar power, renewable energy, waste-to-energy systems); energy systems operation (thermal and hydropower operation and optimization, scheduling, load forecasting, demand-side management); energy efficiency, reducing consumption of or conservation of energy; energy sustainability as related to energy and power production, distribution, and usage; waste management and environmental issues; and energy infrastructure issues (power plant safety, security of infrastructure network).
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