Results 271 to 280 of about 14,317 (308)

Studies on the forecasting errors of the short term load forecast

Proceedings. International Conference on Power System Technology, 2003
A deep research on the short-term load forecasting error has been given in this paper according to the time series theory. The relationship between the model and forecasting error has been investigated. A method proposed could be used to direct how to improve the forecasting accuracy. Instances of different methods test its feasibility.
G. Mu, Y.H. Chen, null Liu ZF, W.D. Fan
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Short-term load forecasting using a long short-term memory network

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2017
Load forecasting is an essential part of a power system. It enhances the energy-efficiency and reliable operation of the power system. As depicted in the proposal of the smart grid, an increasing number of smart meters have been being installed in many utilities on a global scale.
Chang Liu, Zhijian Jin, Jie Gu 0005, Robert Caiming Qiu   +3 more
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Long short term memory networks for short-term electric load forecasting

2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017
Short-term electricity demand forecasting is critical to utility companies. It plays a key role in the operation of power industry. It becomes all the more important and critical with increasing penetration of renewable energy sources. Short-term load forecasting enables power companies to make informed business decisions in real-time.
Apurva Narayan, Keith W. Hipel
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Local Regression-Based Short-Term Load Forecasting

Journal of Intelligent and Robotic Systems, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Load forecasting based on short-term correlation clustering

2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2017
Load forecasting is the basis not only of power system stable and safe operation, but also of power demand side intelligent electricity management. Short-term correlation analysis can be used to mine the electricity consumption of a period of time. The analysis of similar electricity consumption can improve the effect of load forecasting.
Shun Tao, Yongtong Li, Xiangning Xiao, Liting Yao   +3 more
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Short-Term Load Forecasting based on ResNet and LSTM

2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2018
Recent development of artificial intelligence (AI) makes AI applicable to diverse fields, and the smart grid is not an exception. In particular, there have been extensive researches on load forecasting using deep learning. Most existing studies have been conducted on deep neural network (DNN) and recurrent neural network (RNN).
Hyungeun Choi, Seunghyoung Ryu, Hongseok Kim   +2 more
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Convolutional residual network to short-term load forecasting

Applied Intelligence, 2020
Since their inception, convolutional neural networks (CNNs) have been shown to have powerful feature extraction and learning capabilities, and the creation of deep residual networks (DRNs) was a milestone in the development of CNNs. However, residual networks mostly use convolution structures, which are widely applied to image recognition and ...
Ziyu Sheng, Huiwei Wang, Guo Chen 0002, Bo Zhou 0021, Jian Sun 0014   +4 more
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A hierarchical neural model in short-term load forecasting

Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks, 2002
This paper proposes a novel neural model for the short-term load forecasting problem. The neural model is made up of two self-organizing map nets-one on top of the other. It has been successfully applied to domains in which the context information given by former events plays a primary role. The model was trained and assessed on the load data extracted
Otávio Augusto Salgado Carpinteiro, Alexandre P. Alves da Silva   +1 more
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Interactive short-Term Load Forecasting

1982
The general objective of planning in power system utilities is to ensure a secure and economic energy supply. The prediction of the load curve, usually for one or more days in advance provides the basis of the short-term operation planning.
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Adaptive Weather-Sensitive Short Term Load Forecast

IEEE Transactions on Power Systems, 1987
This paper introduces an adaptive, weather sensitive, short term load forecast algorithm that has been developed for two South Carolina Power Systems: CEPCI (Central Electric Power Cooperatives, Inc., Central for short) and Combined System. The model is based on a State Space formulation specially tailored for this application.
R. Campo, P. Ruiz
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