Results 21 to 30 of about 8,161 (262)
Energies, 2021 With economic growth, the demand for power systems is increasingly large. Short-term load forecasting (STLF) becomes an indispensable factor to enhance the application of a smart grid (SG).
Yizhen Wang, Ningqing Zhang, Xiong Chen
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Comparison methods of short term electrical load forecasting
MATEC Web of Conferences, 2018 The supply of electricity that exceeds the load requirement results in the occurrence of electrical power losses. To provide the appropriate power supply to these needs, there must be a plan for the provision of electricity by making prediction or ...
Hartono, Marifa Ahmad Arif, Sadikin M.
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Federated Learning for Short-Term Residential Load Forecasting
IEEE Open Access Journal of Power and Energy, 2022 Load forecasting is an essential task performed within the energy industry to help balance supply with demand and maintain a stable load on the electricity grid. As supply transitions towards less reliable renewable energy generation, smart meters will prove a vital component to facilitate these forecasting tasks.
Christopher Briggs +2 more
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A Quantile Regression Random Forest-Based Short-Term Load Probabilistic Forecasting Method
Energies, 2022 In this paper, a novel short-term load forecasting method amalgamated with quantile regression random forest is proposed. Comprised with point forecasting, it is capable of quantifying the uncertainty of power load.
Sanlei Dang +4 more
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Blind Kalman Filtering for Short-Term Load Forecasting [PDF]
IEEE Transactions on Power Systems, 2020 In this work we address the problem of short-term load forecasting. We propose a generalization of the linear state-space model where the evolution of the state and the observation matrices is unknown. The proposed blind Kalman filter algorithm proceeds via alternating the estimation of these unknown matrices and the inference of the state, within the ...
Shalini Sharma +3 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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Short Term Load Forecasting Based Artificial Neural Network [PDF]
Iraqi Journal for Electrical and Electronic Engineering, 2014 Present study develops short term electric load forecasting using neural network; based on historical series of power demand the neural network chosen for this network is feed forward network, this neural network has five input variables ( hour of the ...
Adel M. Dakhil
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Short-term load forecasting using time series clustering
Optimization and Engineering, 2022 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Martins, Ana Alexandra +4 more
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Short-Term Load Forecasting on Individual Consumers
Energies, 2022 Maintaining stability and control over the electric system requires increasing information about the consumers’ profiling due to changes in the form of electricity generation and consumption.
João Victor Jales Melo +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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