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2024 | OriginalPaper | Chapter

Research on Electric Load Forecasting Considering Node Marginal Electricity Price Based on WNN

Authors : Xiaolu Li, Jun Li, Shijun Chen, Mingli Li, Bangyong Pan, Jie Luo, Min Liu

Published in: The Proceedings of the 18th Annual Conference of China Electrotechnical Society

Publisher: Springer Nature Singapore

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Abstract

This research suggests an electric load forecasting method that takes into account the marginal price of electricity in order to further increase the forecasting accuracy for electric loads. By including the marginal electricity price, the approach creates the training and test sets for the electric load. The establishment of an electric load prediction model using a Wavelet Neural Network (WNN) is followed by load prediction using the local power grid's current data. By comparing the evaluation indicators with the electric load forecasting case without considering the marginal electricity prices of nodes, the results show that considering marginal electricity prices can improve the accuracy of electric load forecasting.

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Title: Research on Electric Load Forecasting Considering Node Marginal Electricity Price Based on WNN
Authors: Xiaolu Li
Jun Li
Shijun Chen
Mingli Li
Bangyong Pan
Jie Luo
Min Liu
Publisher: Springer Nature Singapore
Book: The Proceedings of the 18th Annual Conference of China Electrotechnical Society
Print ISBN: 978-981-9710-63-8

Electronic ISBN: 978-981-9710-64-5

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-981-97-1064-5_62