Research on short-term load forecasting of power system based on IWOA-KELM
A short-term power load forecasting (STPLF) model based on the Improved Whale Optimization Algorithm (IWOA) optimized Kernel Extreme Learning Machine (KELM) is proposed to address the problems of high randomness and low forecasting accuracy of electricity loads. The KELM model is constructed, and th...
Main Authors: | Xuesong Han, Yan Shi, Renjie Tong, Siteng Wang, Yi Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-10-01
|
Series: | Energy Reports |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723009149 |
Similar Items
-
Research on renewable energy power demand forecasting method based on IWOA-SA-BILSTM modeling
by: Minghu Wang, et al.
Published: (2024-01-01) -
Multi-model fusion short-term power load forecasting based on improved WOA optimization
by: Xiaotong Ji, et al.
Published: (2022-09-01) -
Short-Term Load Forecasting of Distributed Energy System Based on Kernel Principal Component Analysis and KELM Optimized by Fireworks Algorithm
by: Yingying Fan, et al.
Published: (2021-12-01) -
Forecasting Short-Term Electricity Load Using Validated Ensemble Learning
by: Chatum Sankalpa, et al.
Published: (2022-11-01) -
Short-term wind power forecasting and uncertainty analysis based on FCM–WOA–ELM–GMM
by: Bo Gu, et al.
Published: (2023-12-01)