Results 31 to 40 of about 29,272 (313)

Classification of load forecasting studies by forecasting problem to select load forecasting techniques and methodologies

CoRR, 2018
arXiv ...
Dumas, Jonathan, Cornélusse, Bertrand
openaire   +3 more sources

Construction and Application of Short-Term and Mid-Term Power System Load Forecasting Model Based on Hybrid Deep Learning

IEEE Access, 2023
Power system load forecasting model plays an important role in all aspects of power system planning, operation and control. Therefore, accurate power load forecasting provides an important guarantee for the stable operation of the power grid system. This
Hongsheng Xu, Ganglong Fan, Guofang Kuang, Yanping Song   +3 more
doaj   +1 more source

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, Long Peng, Jingming Zhao, Jiajie Li, Zhengmin Kong   +4 more
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Research on Intelligent Power Load Forecasting Algorithm Based on Empirical Mode Decomposition

Chemical Engineering Transactions, 2017
The load forecasting of power system is related to the dispatching operation and production planning of power system. Accurate load forecasting can improve the safety and stability of the system and reduce the cost of power generation. The load variation
Qinghua Chen
doaj   +1 more source

Forecasting of Electric Load Using a Hybrid LSTM-Neural Prophet Model

Energies, 2022
Load forecasting (LF) is an essential factor in power system management. LF helps the utility maximize the utilization of power-generating plants and schedule them both reliably and economically.
Md Jamal Ahmed Shohan, Md Omar Faruque, Simon Y. Foo   +2 more
doaj   +1 more source

Short-Term Load-Forecasting Method Based on Wavelet Decomposition With Second-Order Gray Neural Network Model Combined With ADF Test

IEEE Access, 2017
Improving the accuracy of power system load forecasting is important for economic dispatch. However, a load sequence is highly nonstationary and hence makes accurate forecasting difficult. In this paper, a method based on wavelet decomposition (WD) and a
Bowen Li, Jing Zhang, Yu He, Yang Wang
doaj   +1 more source

A review of research on spatial-temporal forecasting of power load based on spatial-temporal data mining

International Journal of Electrical Power & Energy Systems
Lately, in the context of global energy crisis and economic recovery after the COVID-19 epidemic, the contradiction between power supply and demand has become more prominent, showing a tight balance.
Zhanshuo Hu, Pengfei Zhang, Jianning Cai, Hengyu Liu, Gaohan Wang, Zhe Chen   +5 more
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Improving Load Forecasting Process for a Power Distribution Network Using Hybrid AI and Deep Learning Algorithms

IEEE Access, 2019
Load forecasting is useful for various applications, including maintenance planning. The study of load forecasting using recent state-of-the-art hybrid artificial intelligence (AI) and deep learning (DL) techniques is limited in South Africa (SA) and ...
Sibonelo Motepe, Ali N. Hasan, Riaan Stopforth   +2 more
doaj   +1 more source

A Multi-Level Collaborative Load Forecasting Method for Distribution Networks Based on Distributed Optimization

Shanghai Jiaotong Daxue xuebao, 2021
At present, new elements such as distributed new energy and electric vehicles have emerged in the distribution network, which changes the composition of loads, enriches the connotation of loads, and poses severe challenges to load forecasting.
TAN Jia, LI Zhiyi, YANG Huan, ZHAO Rongxiang, JU Ping
doaj   +1 more source

Residential Power Load Forecasting

Procedia Computer Science, 2014
AbstractThe prepaid electric power metering market is being driven in large part by advancements in and the adoption of Smart Grid technology. Advanced smart meters facilitate the deployment of prepaid systems with smart prepaid meters. A successful program hinges on the ability to accurately predict the amount of energy consumed on a daily basis for ...
Patrick Day, Michael Fabian, Don Noble, George Ruwisch, Ryan Spencer, Jeff Stevenson, Rajesh Thoppay   +6 more
openaire   +1 more source