Results 21 to 30 of about 14,317 (308)

Short-term power load forecasting based on I-GWO-KELM algorithm [PDF]

MATEC Web of Conferences, 2021
In this paper, I-GWO-KELM algorithm is used for short-term power load forecasting. Normalize the power data and meteorological data of the short-term power load, and use GWO to optimize the regularization coefficient of KELM and the RBF kernel parameters.
Chen Xiaoyu, Dong Xiangli, Shi Li
doaj   +1 more source

Guest Editorial: Special Issue on Short-Term Load Forecasting 2019, Results and Future Perspectives [PDF]

, 2022
In December 2018, the call for the Special Issue “Short-Term Load Forecasting 2019” of the journal Energies was launched [...
Gabaldón, Antonio [0000-0002-0952-4607], Ruiz-Abellón, María Carmen [0000-0002-0639-2688], Ruiz Abellón, María Carmen, Gabaldón Marín, Antonio, Fernández Jiménez, Luis Alfredo, María Carmen Ruiz-Abellón, Antonio Gabaldón, Luis Alfredo Fernández-Jiménez, Fernández-Jiménez, Luis Alfredo [0000-0002-5633-4849]   +8 more
core   +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

Spatial‐temporal learning structure for short‐term load forecasting

IET Generation, Transmission & Distribution, 2023
In the power system operational/planning studies, it is a crucial task to provide the load consumption information in the look‐ahead times. The huge variation of the power system infrastructure in recent years has led to significant changes in the ...
Mahtab Ganjouri, Mazda Moattari, Ahmad Forouzantabar, Mohammad Azadi   +3 more
doaj   +1 more source

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

Data Selection for Short Term load forecasting

CoRR, 2019
Power load forecast with Machine Learning is a fairly mature application of artificial intelligence and it is indispensable in operation, control and planning. Data selection techniqies have been hardly used in this application. However, the use of such techniques could be beneficial provided the assumption that the data is identically distributed is ...
Nestor Pereira, Miguel Ángel Hombrados-Herrera, Vanessa Gómez-Verdejo, Andrea A. Mammoli, Manel Martínez-Ramón   +4 more
openaire   +2 more sources

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

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

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

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