Load forecasting analysis based on the residential electricity consumption data of BP neural network

Junhao Xiao; Nan Zhang; Zhu Liu; Yumin Liu; Meng Ming; Xuerui Chen; Shuai Zhang

doi:10.1117/12.3007000

10 October 2023 Load forecasting analysis based on the residential electricity consumption data of BP neural network

Junhao Xiao, Nan Zhang, Zhu Liu, Yumin Liu, Meng Ming, Xuerui Chen, Shuai Zhang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127990I (2023) https://doi.org/10.1117/12.3007000
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Due to the expansion in scale, complexity in structure, and intelligence in functionality of the power system in recent years, the amount of data generated has been increasing daily, leading the power system into a "data explosion" era. Considering the unique properties of electric energy, load forecasting plays an extremely important role in power production. In the current environment, traditional load forecasting methods are difficult to meet the operational requirements of the power system. Therefore, it has become a top priority in the field of load forecasting to effectively establish models for processing large data to improve the accuracy of load forecasting. Based on the current research status both domestically and internationally, this article proposes a method for processing big data by building an artificial neural network using the backpropagation algorithm.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Junhao Xiao, Nan Zhang, Zhu Liu, Yumin Liu, Meng Ming, Xuerui Chen, and Shuai Zhang "Load forecasting analysis based on the residential electricity consumption data of BP neural network", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127990I (10 October 2023); https://doi.org/10.1117/12.3007000

ACCESS THE FULL ARTICLE

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