Results 21 to 30 of about 215,326 (298)

Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

IEEE Transactions on Smart Grid, 2019
As the power system is facing a transition toward a more intelligent, flexible, and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers ...
Weicong Kong, Z. Dong, Youwei Jia, D. Hill, Yan Xu, Yuan Zhang   +5 more
semanticscholar   +1 more source

An Ensemble Framework for Short-Term Load Forecasting Based on TimesNet and TCN

Energies, 2023
Accurate and efficient short-term power load forecasting is crucial for ensuring the stable operation of power systems and rational planning of electricity resources. However, power load data are often characterized by nonlinearity and instability due to
Chuanhui Zuo, Jialong Wang, Ming Liu, Suhui Deng, Qingnian Wang   +4 more
semanticscholar   +1 more source

Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution

Data Science and Engineering, 2023
An accurate short-term load forecasting plays an important role in modern power system’s operation and economic development. However, short-term load forecasting is affected by multiple factors, and due to the complexity of the relationships between ...
Chenchen Sun, Yan Ning, Derong Shen, Tiezheng Nie   +3 more
semanticscholar   +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

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

Short-Term Load Forecasting Method Based on Feature Preference Strategy and LightGBM-XGboost

IEEE Access, 2022
Short term load forecasting is one of the important problems in power system. Accurate forecasting results can improve the flexibility of power market and resource utilization efficiency, which is of great significance to the efficient operation of power
Xiaotong Yao, Xiaoli Fu, Chaofei Zong
semanticscholar   +1 more source

A Secure Federated Learning Framework for Residential Short-Term Load Forecasting [PDF]

IEEE Transactions on Smart Grid, 2022
Smart meter measurements, though critical for accurate demand forecasting, face several drawbacks including consumers’ privacy, data breach issues, to name a few.
Muhammad Akbar Husnoo, A. Anwar, N. Hosseinzadeh, S. Islam, A. Mahmood, R. Doss   +5 more
semanticscholar   +1 more source

Regression Model-Based Short-Term Load Forecasting for University Campus Load

IEEE Access, 2022
Load forecasting is a critical aspect for power systems planning, operation and control. In this paper, as part of research efforts of an ambitious project at Memorial University of Newfoundland in St. John’s, Canada, to achieve more energy efficient and
M. Madhukumar, Albino Sebastian, Xiaodong Liang, Mohsin Jamil, Md. Nasmus Sakib Khan Shabbir   +4 more
semanticscholar   +1 more source

Short-term load forecasting using time series clustering

Optimization and Engineering, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Martins, Ana Alexandra, Lagarto, João, Canacsinh, Hiren, Reis, Francisco, Cardoso, Maria Margarida   +4 more
openaire   +3 more sources

Short-term electric load forecasting using computational intelligence methods [PDF]

, 2013
Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence
Cortez, Paulo, Jurado, Sergio, Mugica, Francisco, Nebot, Àngela, Peralta, J.   +4 more
core   +1 more source