Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 66, Issue 12, Pages 9312-9325Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2019.2893867
Keywords
Fuel cell; grey prediction model; lithium-ion battery (LIB); remaining useful life (RUL) estimation; renewable energy storages
Ask authors/readers for more resources
This paper proposes a novel error correction grey prediction model for degradation prediction of renewable energy storages. The proposed approach uses an error correction factor. to eliminate the inherent error of the original grey model (GM), and at the same time retain the original simplicity and fast prototyping. In addition, due to the uncertainty and complexity of failure mechanisms, a trigonometric residual modification is considered in order to well-describe the influence of operating conditions or cyclic fluctuation on the renewable energy storages. Two experimental case studies, including lithium-ion battery and fuel cell aging tests, are performed to validate the performance of the proposed method. In particular, the accuracy of the proposed method is investigated for different prediction horizon lengths, in order to further demonstrate its effectiveness and robustness. It is worth mentioning that the proposed method can ensure the accuracy of the remaining useful life estimation in the case of long-term forecasting, and thus, the maintenance management and corrective action of renewable energy storages can be scheduled earlier, leading to more effective cost minimization and risk mitigation.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available