Congestion-aware robust security constrained unit commitment model for AC-DC grids

• Published in: Applied energy 2021-12, Vol.304, p.117392, Article 117392
• Main Authors: Jiang, Sufan, Gao, Shan, Pan, Guangsheng, Liu, Yu, Wu, Chuanshen, Wang, Sicheng
• Format: Article
• Language: English
• Subjects: Congestion management; Congestion-aware factors; High Voltage Direct Current (HVDC) system; security constrained unit commitment (SCUC); Wind uncertainty budget sets
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2021.117392

•The proposed SCUC model exploits the congestion management capabilities of the HVDC system.•Uncertainty budget sets are more adaptive to the plausible contingencies owing to the formulation of congestion-aware factors.•The proposed SCUC model eliminates the local optimal solution due to the optimality cut planes.•The novel three-level Benders Decomposition algorithm solves the mix-integer linear problem.•The proposed model captures improved economic benefits when ensuring the model’s robustness. Due to the increasing penetration of wind energy, their natural volatility may cause power flow congestions by blocking some key transmission interfaces. To further reduce energy violations induced by uncertainty issues and ensure the system reliability, the controllability of High Voltage Direct Current (HVDC) system should be exploited in AC-DC grids. By leveraging the congestion management capabilities of HVDC, we propose a congestion-aware robust security constrained unit commitment (SCUC) model, to preemptively consider the plausible congestion circumstances in a more adaptive way in the day-ahead (DA) market. In our model, the conventional uncertainty budget sets are modified by the proposed congestion-aware factors, where the typical operational characteristics of traditional corrective actions and HVDC regulations in real-time (RT) market are formulated adaptively. Moreover, the feasibility region of proposed problem is further pruned by the optimality cut planes where more pertinent real-time information are included, thus the local optimal solution is eliminated and the superior economic benefits are obtained in our model. To solve this mix-integer linear problem (MILP), the model is divided into three parts including the DA decision model, the traditional corrective dispatch model, and the HVDC regulation dispatch model. Correspondingly, an improved three-level Benders Decomposition algorithm is developed to solve the model. The enhanced performance of the proposed model was validated in a modified IEEE 118-bus test case. The results show that, in our model, the flexible regulation of HVDC system optimally allocate the operational burdens between DA and RT markets, thus the congestion-aware robust SCUC model further captures the economic benefits when ensuring the model’s robustness.