Development and application of an evolutionary deep learning framework of LSTM based on improved grasshopper optimization algorithm for short-term load …
H Hu, X Xia, Y Luo, C Zhang, MS Nazir… - Journal of Building …, 2022 - Elsevier
Accurate short-term load forecasting (STLF) plays an important role in the daily operation of
a smart grid. In order to forecast short-term load more effectively, this article proposes an …
a smart grid. In order to forecast short-term load more effectively, this article proposes an …
Multivariate rolling decomposition hybrid learning paradigm for power load forecasting
A Xu, J Chen, J Li, Z Chen, S Xu, Y Nie - Renewable and Sustainable …, 2025 - Elsevier
Very-short-term power load forecasting (VSTLF) is essential for supporting government
planning in the transformation and expansion of power grids, as well as in the formulation of …
planning in the transformation and expansion of power grids, as well as in the formulation of …
Short-term electricity demand forecasting via variational autoencoders and batch training-based bidirectional long short-term memory
Electricity load forecasting is a key aspect for power producers to maximize their economic
efficiency in deregulated markets. So far, many solutions have been employed to forecast …
efficiency in deregulated markets. So far, many solutions have been employed to forecast …
A short-term electric load forecast method based on improved sequence-to-sequence GRU with adaptive temporal dependence
Accurate and efficient short-term electric load forecast (STLF) is essential for power systems'
reliable and economical operation. The temporal dependence of actual load exhibits …
reliable and economical operation. The temporal dependence of actual load exhibits …
[HTML][HTML] FedForecast: A federated learning framework for short-term probabilistic individual load forecasting in smart grid
Load forecasting plays a crucial role in the power system operation and planning. However,
with people's increased awareness of privacy, consumers may not be willing to share their …
with people's increased awareness of privacy, consumers may not be willing to share their …
[HTML][HTML] Data-driven cooperative trading framework for a risk-constrained wind integrated power system considering market uncertainties
As wind power continues to integrate into modern power systems, the bidding strategies of
wind power producers are becoming more important than ever. However, the current trading …
wind power producers are becoming more important than ever. However, the current trading …
Multi-energy load forecasting in integrated energy systems: a spatial-temporal adaptive personalized federated learning approach
H Wu, Z Xu - IEEE Transactions on Industrial Informatics, 2024 - ieeexplore.ieee.org
Short-term forecasting of multienergy loads is of paramount significance for integrated
energy systems operation. The central forecasting framework is confronted with the privacy …
energy systems operation. The central forecasting framework is confronted with the privacy …
Combining fuzzy clustering and improved long short-term memory neural networks for short-term load forecasting
F Liu, T Dong, Q Liu, Y Liu, S Li - Electric Power Systems Research, 2024 - Elsevier
Short-term load forecasting (STLF) is a critical component of smart grid operations, yet it is a
challenging task due to the high uncertainty of electrical loads. This paper proposes a novel …
challenging task due to the high uncertainty of electrical loads. This paper proposes a novel …
Short-term electricity-load forecasting by deep learning: A comprehensive survey
Short-Term Electricity-Load Forecasting (STELF) refers to the prediction of the immediate
demand (in the next few hours to several days) for the power system. Various external …
demand (in the next few hours to several days) for the power system. Various external …
[HTML][HTML] A hybrid residential short-term load forecasting method using attention mechanism and deep learning
Development in economics and social society has led to rapid growth in electricity demand.
Accurate residential electricity load forecasting is helpful for the transformation of residential …
Accurate residential electricity load forecasting is helpful for the transformation of residential …