Results 21 to 30 of about 127,521 (300)

Short-term Load Forecasting Based On Variational Mode Decomposition And Chaotic Grey Wolf Optimization Improved Random Forest Algorithm

Journal of Applied Science and Engineering, 2022
To enrich short-term load forecasting methods and improve forecasting accuracy, a short-term load forecasting method based on variational mode decomposition and chaotic grey wolf optimization (CGWO) improved random forest (RF) is proposed.
Fan Wang, Chen Chen, Haitao Zhang, Youhua Ma   +3 more
doaj   +1 more source

Short term electricity load forecasting for institutional buildings

Energy Reports, 2019
Peak load demand forecasting is important in building unit sectors, as climate change, technological development, and energy policies are causing an increase in peak demand. Thus, accurate peak load forecasting is a critical role in preventing a blackout
Yunsun Kim, Heung-gu Son, Sahm Kim
doaj   +1 more source

Fractional ARIMA with an improved cuckoo search optimization for the efficient Short-term power load forecasting

Alexandria Engineering Journal, 2020
Short-term power load forecasting plays a key role in power supply systems. Many methods have been used in short-term power load forecasting during the past years. A new short-term power load forecasting method is proposed in this study. First, the study
Fei Wu, Carlo Cattani, Wanqing Song, Enrico Zio   +3 more
doaj   +1 more source

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

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
doaj   +1 more source

An Ultra-Short-Term Electrical Load Forecasting Method Based on Temperature-Factor-Weight and LSTM Model

Energies, 2020
Ultra-short-term electrical load forecasting is an important guarantee for the safety and efficiency of energy system operation. Temperature is also an important factor affecting the changes in electric load.
Dengyong Zhang, Haixin Tong, Feng Li, Lingyun Xiang, Xiangling Ding   +4 more
doaj   +1 more source

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.
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
doaj   +1 more source

GA-ANN Short-Term Electricity Load Forecasting [PDF]

, 2016
This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption,
C-L Huang, C-T Lin, C-T Lin, D Niu, E Kyriakides, H Hahn, HS Hippert, I Guyon, JP Ignizio, K Metaxiotis, L Suganthi, M Sheikhan, M Welsch, SM Vieira, Y Saeys   +14 more
core   +1 more source

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, Zhong Fan, Peter Andras   +2 more
openaire   +3 more sources

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, Angshul Majumdar, Victor Elvira, Emilie Chouzenoux   +3 more
openaire   +3 more sources