Results 31 to 40 of about 108,774 (242)

Short-Term Power Load Forecasting: An Integrated Approach Utilizing Variational Mode Decomposition and TCN–BiGRU

Energies, 2023
Accurate short-term power load forecasting is crucial to maintaining a balance between energy supply and demand, thus minimizing operational costs. However, the intrinsic uncertainty and non-linearity of load data substantially impact the accuracy of ...
Zhuoqun Zou, Jing Wang, Ning E, Can Zhang, Zhaocai Wang, Enyu Jiang   +5 more
doaj   +1 more source

Short term Load Forecasting Considering Demand Response under virtual power plant mode [PDF]

E3S Web of Conferences, 2021
In order to better manage demand response resources of user side and reduce short-term load forecasting error, a short-term load forecasting method considering demand response in virtual power plant mode is proposed.
Du Zhendong, Wu Di, Bai Hua, Wang Zhengyong, Guo Yizong, Guo Chuangxin   +5 more
doaj   +1 more source

Short-term Power Load Forecasting Based on Balanced KNN

IOP Conference Series: Materials Science and Engineering, 2018
To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene ...
Xianlong Lv, Xingong Cheng, null YanShuang, Yan-mei Tang   +3 more
openaire   +1 more source

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

Energies, 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, Wei-Zhen Zheng, Jian-Lei Kong, Xiao-Yi Wang, Yu-Ting Bai, Ting-Li Su, Seng Lin   +6 more
doaj   +1 more source

Short-term power load interval forecasting based on nonparametric Bootstrap errors sampling

Energy Reports, 2022
Short-term power load forecasting plays a vital role in the planning of distribution network and the development of social economy. Many researchers have devoted their attention to construct point forecasting models.
Ling Xiao, Miaotong Li, Shenghui Zhang
doaj   +1 more source

Development of Neurofuzzy Architectures for Electricity Price Forecasting [PDF]

, 2020
In 20th century, many countries have liberalized their electricity market. This power markets liberalization has directed generation companies as well as wholesale buyers to undertake a greater intense risk exposure compared to the old centralized ...
Alshejari, A, Alshejari, A, Kodogiannis, V., Kodogiannis, V., Leonidis, S, Leonidis, S   +5 more
core   +1 more source

Short Term load forecasting by means of Load Time Series Decomposition and Neural Network [PDF]

مجله مدل سازی در مهندسی, 2008
             Abstract   The importance of short term load forecasting has been increasing lately. Artificial Neural Network (ANN) Method is applied to forecast the short term load forecasting for a large power system.
روح‌الله فیروزنیا, نیما امجدی   +1 more
doaj   +1 more source

Load Forecasting Based Distribution System Network Reconfiguration-A Distributed Data-Driven Approach

, 2017
In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load ...
Gu, Yi, Jiang, Huaiguang, Muljadi, Eduard, Solis, Francisco J., Zhang, Jun Jason, Zhang, Yingchen   +5 more
core   +1 more source

A novel forward operator-based Bayesian recurrent neural network-based short-term net load demand forecasting considering demand-side renewable energy

Frontiers in Energy Research, 2022
Currently, traditional electricity consumers are now shifting to a new role of prosumers since more integration of renewable energy to demand side. Accurate short-term load demand forecasting is significant to safe, stable, and reliable operation of a ...
Jiying Wen, Zhongye Xian, Kai Chen, Wei Luo   +3 more
doaj   +1 more source

An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting

, 2017
The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective ...
Bianchi, Filippo Maria, Jenssen, Robert, Kampffmeyer, Michael C., Maiorino, Enrico, Rizzi, Antonello   +4 more
core   +1 more source