Resilient robust model predictive load frequency control for smart grids with air conditioning loads

Abstract This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two‐area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi‐area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances.

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Publication Details

Journal
IET Renewable Power Generation
Published
2024-08-25
DOI
https://doi.org/10.1049/rpg2.13075
Citations
2
Primary Topic
Frequency Control in Power Systems
Type
article
Field-Weighted Citation Impact
0.42

Funders

Controls
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article

Resilient robust model predictive load frequency control for smart grids with air conditioning loads

Haiya Qian, Mengxia Zhou, Guobao Liu, Qi Wang et al.
2 citations
IET Renewable Power Generation
Frequency Control in Power Systems
0.42
article

Resilient robust model predictive load frequency control for smart grids with air conditioning loads

Haiya Qian, Mengxia Zhou, Guobao Liu, Qi Wang, Feng Li, Changyu Zhang, Shiluo Jike
article en
2 citations

Abstract

Abstract This paper investigates the robust model predictive load frequency control problem for smart grids with wind power under cyber attacks. To accommodate intermittent power generation, the demand response of the system is considered by involving the air conditioning loads in the frequency regulation. In addition, the system uncertainties produced by the air conditioning load users and wind turbines when replacing traditional generator sets are considered. By using the cone complementary linearization algorithm and the linear matrix inequality technique, a resilience robust model predictive control strategy with mixed performance indexes is proposed. Furthermore, a rigorous derivation of the recursive feasibility of robust model predictive control is given. Finally, the simulation results of the two‐area load frequency control scheme show that the proposed model predictive control strategy is capable of realizing the load frequency control of the multi‐area smart grid and is robust to the parameter uncertainties and frequency regulation of the system. The results also show that the proposed model predictive control strategy has some resistance to cyber attacks and external disturbances.

IET Renewable Power GenerationVol. 18(14)
Nanjing Normal University (CN), Southeast University (CN)
National Natural Science Foundation of China, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province
Affordable and clean energy
Openalex Percentile: Top 38%
Frequency Control in Power Systems
0.42
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