TY - GEN
T1 - KNN-ADMM based Online Missing Data Recovery in Electricity Markets
AU - Liu, Jiacheng
AU - Wu, Jiang
AU - Xu, Zhanbo
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper proposes a missing electricity markets data online recovery strategy combining the improved K-Nearest Neighbor clustering(KNN) and Alternating Direction Method of Multipliers(ADMM). Considering the coupling consumption behaviors in different end users, the electricity markets data can be approximated in low-rank feature with singular value decomposition method. Moreover, the sliding time window is adopted as an online repair strategy to realize real-time recovery and improve the speed of recovery. Ultimately, the effectiveness of proposed online KNN-ADMM algorithm is verified through the electricity markets data of four Chinese cities. Results show that the algorithm is suitable for electricity markets data online recovery and the recovery error is within 5% with the 15% missing data.
AB - This paper proposes a missing electricity markets data online recovery strategy combining the improved K-Nearest Neighbor clustering(KNN) and Alternating Direction Method of Multipliers(ADMM). Considering the coupling consumption behaviors in different end users, the electricity markets data can be approximated in low-rank feature with singular value decomposition method. Moreover, the sliding time window is adopted as an online repair strategy to realize real-time recovery and improve the speed of recovery. Ultimately, the effectiveness of proposed online KNN-ADMM algorithm is verified through the electricity markets data of four Chinese cities. Results show that the algorithm is suitable for electricity markets data online recovery and the recovery error is within 5% with the 15% missing data.
KW - Alternating Direction Method of Multipliers(ADMM)
KW - Data Recovery
KW - Electricity Markets Data
KW - K-Nearest Neighbor(KNN)
UR - https://www.scopus.com/pages/publications/85149550445
U2 - 10.1109/CCDC55256.2022.10033577
DO - 10.1109/CCDC55256.2022.10033577
M3 - 会议稿件
AN - SCOPUS:85149550445
T3 - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022
SP - 4030
EP - 4035
BT - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th Chinese Control and Decision Conference, CCDC 2022
Y2 - 15 August 2022 through 17 August 2022
ER -