Support vector regression with asymmetric loss for optimal electric load forecasting
Journal article
Wu, Ryan, Wang, You-Gan, Tian, Yu-Chu, Burrage, Kevin and Cao, Taoyun. (2021). Support vector regression with asymmetric loss for optimal electric load forecasting. Energy. 223, p. Article 119969. https://doi.org/10.1016/j.energy.2021.119969
Authors | Wu, Ryan, Wang, You-Gan, Tian, Yu-Chu, Burrage, Kevin and Cao, Taoyun |
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Abstract | In energy demand forecasting, the objective function is often symmetric, implying that over-prediction errors and under-prediction errors have the same consequences. In practice, these two types of errors generally incur very different costs. To accommodate this, we propose a machine learning algorithm with a cost-oriented asymmetric loss function in the training procedure. Specifically, we develop a new support vector regression incorporating a linear-linear cost function and the insensitivity parameter for sufficient fitting. The electric load data from the state of New South Wales in Australia is used to show the superiority of our proposed framework. Compared with the basic support vector regression, our new asymmetric support vector regression framework for multi-step load forecasting results in a daily economic cost reduction ranging from 42.19% to 57.39%, depending on the actual cost ratio of the two types of errors. |
Keywords | asymmetric loss; cost-orientation; machine learning; statistical modeling; load forecasting |
Year | 2021 |
Journal | Energy |
Journal citation | 223, p. Article 119969 |
Publisher | Elsevier Ltd |
ISSN | 0360-5442 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.energy.2021.119969 |
Scopus EID | 2-s2.0-85101019931 |
Open access | Published as green open access |
Page range | 1-12 |
Funder | Australian Research Council (ARC) |
Guangdong Basic and Applied Basic Research Foundation | |
Guangdong universities | |
Author's accepted manuscript | License File Access Level Open |
Publisher's version | License All rights reserved File Access Level Controlled |
Output status | Published |
Publication dates | |
Online | 10 Feb 2021 |
Publication process dates | |
Accepted | 22 Jan 2021 |
Deposited | 07 Dec 2022 |
ARC Funded Research | This output has been funded, wholly or partially, under the Australian Research Council Act 2001 |
Grant ID | DP160104292 |
CE140100049 | |
2020A1515011580 | |
2018GKTSCX010 |
https://acuresearchbank.acu.edu.au/item/8y8q2/support-vector-regression-with-asymmetric-loss-for-optimal-electric-load-forecasting
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Author's accepted manuscript
AM_Wu_2021_Support_vector_regression_with_asymmetric_loss.pdf | |
License: CC BY-NC-ND | |
File access level: Open |
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