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Short term power load forecasting using Deep Neural Networks [PDF]
2017 International Conference on Computing, Networking and Communications (ICNC), 2017 Accurate load forecasting greatly influences the planning processes undertaken in operation centres of energy providers that relate to the actual electricity generation, distribution, system maintenance as well as electricity pricing. This paper exploits the applicability of and compares the performance of the Feed-forward Deep Neural Network (FF-DNN ...
Ghulam Mohi Ud Din +1 more
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Sensors, 2022 Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units.
Lichao Sun +4 more
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Short-Term Electrical Load Forecasting Based on Time Augmented Transformer
International Journal of Computational Intelligence Systems, 2022 Electrical load forecasting is of vital importance in intelligent power management and has been a hot spot in industrial Internet application field. Due to the complex patterns and dynamics of the data, accurate short-term load forecasting is still a ...
Guangqi Zhang +3 more
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Industrial Ultra-Short-Term Load Forecasting With Data Completion
IEEE Access, 2020 Accurate and efficient ultra-short-term load forecasting is crucial for industrial power users to have stabilized and optimized operations. In this paper, we develop novel strategies for industrial power users to handle their challenges in ultra-short ...
Haoyu Jiang +4 more
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Short-Term Load Forecasting Method Based on Feature Preference Strategy and LightGBM-XGboost
IEEE Access, 2022 Short term load forecasting is one of the important problems in power system. Accurate forecasting results can improve the flexibility of power market and resource utilization efficiency, which is of great significance to the efficient operation of power
Xiaotong Yao, Xiaoli Fu, Chaofei Zong
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Short-Term Power Load Forecasting Based on VMD-Pyraformer-Adan
IEEE Access, 2023 For the characteristics of fluctuation, periodicity and nonlinearity of power load data, this paper proposes a short-term power load forecasting model based on VMD-Pyraformer-Adan. Firstly, the variational modal decomposition (VMD) algorithm is used to modally decompose the electric load data, the over-zero rate and Pearson correlation coefficient are ...
Yihao Tang, Huafeng Cai
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Deep Forest Regression for Short-Term Load Forecasting of Power Systems [PDF]
IEEE Access, 2020 Deep neural networks of deep learning algorithms can be applied into regressions and classifications. While the regression performances and classification performances of the deep neural networks are depending on the hyper-parameters of the deep neural networks.
Linfei Yin +3 more
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A Deep Learning Framework for Short-term Power Load Forecasting
CoRR, 2017 8 pages, 8 ...
Tinghui Ouyang +4 more
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Energies, 2019 Compared to the load characteristics of normal working days, weekend load characteristics have a low level of load and are sensitive to meteorological conditions, which influences the accuracy of short-term weekend-load forecasting. To solve this problem
Bin Li +3 more
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Frontiers in Environmental Science, 2022 Short-term load forecasting plays a significant role in the management of power plants. In this paper, we propose a multivariate adaptive step fruit fly optimization algorithm (MAFOA) to optimize the smoothing parameter of the generalized regression ...
Feng Jiang, Wenya Zhang, Zijun Peng
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