Results 21 to 30 of about 9,504 (261)

ProLoaF: Probabilistic load forecasting for power systems

open access: yesSoftwareX, 2023
Published by Elsevier, Amsterdam [u.a.]
Gonca Gürses-Tran   +2 more
openaire   +3 more sources

Research on power load forecasting model of economic development zone based on neural network

open access: yesEnergy Reports, 2021
The power load forecasting model can calculate the predicted value accurately and quickly, which will be helpful to distribute the power reasonably and improve the stability of the power grid.
Qiming Feng, Suping Qian
doaj   +1 more source

Deep-Learning Forecasting Method for Electric Power Load via Attention-Based Encoder-Decoder with Bayesian Optimization

open access: yesEnergies, 2021
Short-term electrical load forecasting plays an important role in the safety, stability, and sustainability of the power production and scheduling process.
Xue-Bo Jin   +6 more
doaj   +1 more source

Fusion of Improved Sparrow Search Algorithm and Long Short-Term Memory Neural Network Application in Load Forecasting

open access: yesEnergies, 2021
Load forecasting (LF) is essential in enabling modern power systems’ safety and economical transportation and energy management systems. The dynamic balance between power generation and load in the optimization of power systems is receiving increasing ...
Gwo-Ching Liao
doaj   +1 more source

Load Classification and Forecasting for Temporary Power Installations [PDF]

open access: yes2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2018
Temporary Power Installations (TPIs) serve energy at events (e.g., festivals), typically from on-site generation. As they become more prominent, there is a greater need for efficient configuration and optimal usage. Predictive modeling can help in this regard, however, this is particularly challenging due to limited data and high configuration ...
A.M. Kotriwala (Arzam Muzaffar)   +2 more
openaire   +2 more sources

A Hybrid Double Forecasting System of Short Term Power Load Based on Swarm Intelligence and Nonlinear Integration Mechanism

open access: yesApplied Sciences, 2020
Accurate and reliable power load forecasting not only takes an important place in management and steady running of smart grid, but also has environmental benefits and economic dividends.
Ping Jiang, Ying Nie
doaj   +1 more source

A Short-Term Residential Load Forecasting Model Based on LSTM Recurrent Neural Network Considering Weather Features

open access: yesEnergies, 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
doaj   +1 more source

Residential Power Load Forecasting

open access: yesProcedia 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   +6 more
openaire   +1 more source

A Bottom-up Method for Probabilistic Short-Term Load Forecasting Based on Medium Voltage Load Patterns

open access: yesIEEE Access, 2021
Load forecasting has always been an essential part of power system planning and operation. In recent decades, the competition of the market and the requirements of renewable integration lead more attention to probabilistic load forecasting methods, which
Zhengbang Jiang   +6 more
doaj   +1 more source

Research on Intelligent Power Load Forecasting Algorithm Based on Empirical Mode Decomposition

open access: yesChemical 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

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