Markov Jump System Modeling and Control of Inverter-Fed Remote Area Weak Grid via Quantized Sliding Mode
Power grids located in the remote areas mostly show the features of high inverter-fed energy penetration, low grid strength, weak maintenance forces and high natural disaster risks. Therefore, enhancing the safety and resilience of remote area weak grid is crucial for the long term operation and expansion of the total power system. In this paper, a Markov Jump System (MJS) based modeling approach for the remote area weak grid is proposed, which is capable of accurately reflecting the system dynamics after the happening of major contingencies, including tripping of distributed generators, damages of transmission lines and short circuit incident. Meanwhile, a MJS based quantized sliding mode control is proposed to stabilize the system after the happening of contingencies, where the finite time stability of the control approach is also ensured such that the system can recover to the stabilized status in a faster manner. Case studies are conducted to verify the validity of the MJS modeling approach and the superior performance of the developed quantized sliding mode control scheme.
Authors
- Sunhua Huang (ORCID: https://orcid.org/0000-0002-0641-818X)
- Ruikai Song (ORCID: https://orcid.org/0000-0002-0855-2040)
- Penghan Li (ORCID: https://orcid.org/0000-0001-7295-5728)
- Changyu Ban (ORCID: https://orcid.org/0009-0006-2540-4361)
- Muhammad Khurram Khan (ORCID: https://orcid.org/0000-0001-6636-0533)
- Linyun Xiong (ORCID: https://orcid.org/0000-0001-8524-8256)
- Tao Niu (ORCID: https://orcid.org/0000-0003-4461-9481)
- Ziqiang Wang (ORCID: https://orcid.org/0000-0002-6883-8569)
Institutions
- King Fahd University of Petroleum and Minerals (SA)
- Hong Kong Polytechnic University (HK)
- Chongqing University (CN)
- State Grid Corporation of China (China) (CN)
Publication Details
- Journal
- IEEE Transactions on Power Systems
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1109/tpwrs.2024.3494857
- Citations
- 30
- Primary Topic
- Microgrid Control and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 9.85