CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12704 > Article
Paper
31 May 2023 Short-term load forecasting model of GRU based on improved sparrow search algorithm optimization
Sheng Gao, Weili Wu
Author Affiliations +
Proceedings Volume 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023); 127043M (2023) https://doi.org/10.1117/12.2680415
Event: 8th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2023), 2023, Hangzhou, China
Abstract
Accurate prediction of short-term power load can ensure the safety of power system and reduce the cost of power generation. Aiming at the problems of large fluctuation, strong randomness and difficulty in peak value forecasting, a short-term load forecasting method of gated recurrent unit (GRU) based on improved sparrow search algorithm optimization is proposed. Firstly, In the process of load forecasting, the influence of temperature, humidity, electricity price and other factors on load forecasting is considered, and they are taken as input variables of the forecasting model. Secondly, the improved Levy Sparrow Search Algorithm (LSSA) is used to optimize the parameters of GRU network and fully mine the characteristic information of load data, thus improving the forecasting performance of the model. Finally, the load power of a place in Australia is analyzed as an example, and compared with similar forecasting algorithms, the results show that the forecasting effect of this method is better than other methods, and the forecasting accuracy of shortterm load is effectively improved.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Sheng Gao and Weili Wu "Short-term load forecasting model of GRU based on improved sparrow search algorithm optimization", Proc. SPIE 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023), 127043M (31 May 2023); https://doi.org/10.1117/12.2680415
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 6 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling
Mathematical optimization
Evolutionary algorithms
Performance modeling
Algorithm development
Neural networks
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top