Two-Stage MILP Model for Optimal Skeleton-Network Reconfiguration of Power System for Grid-Resilience Enhancement
Publication: Journal of Energy Engineering
Volume 148, Issue 1
Abstract
Skeleton-network reconfiguration is an important task and plays a most important role during power system restoration (PSR) after a blackout. By determining the skeleton network, the power system can be restored as soon as possible to minimize the burden of network reconfiguration. In this paper, a resilience-based skeleton-network reconfiguration (NR) strategy, i.e., a two-stage mixed-integer linear programming (MILP)–based NR strategy for grid-resilience enhancement, is proposed to minimize the impact of emergency power outages on power systems. The start-up sequence for non-black-start generators (NBSGs) and line energization sequences are determined in the first-stage optimization model. A serial restoration constraint and a transient frequency constraint are considered to achieve the serial restoration scheme of NBSGs. Except for the generator power, all the variables attained during the first stage are assumed fixed in the second stage. The second-stage optimization model determines the optimal skeleton network by determining the target transmission lines and critical load pickup during the NR phase. Furthermore, the sets of metrics (i.e., system flexibility, power loss ratio, and recovery time resilience) are presented to determine the grid operational resilience in the skeleton-network reconfiguration. Then, two stages of skeleton-NR are formulated as MILP, and the branch-and-bound method is presented to solve both models. Finally, simulation studies are performed on the two modified power system test cases and the results validate that the proposed strategy can efficiently determine the robust skeleton network for practical and detailed PSR planning.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request:
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Modified data of IEEE 30-bus power system,
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Modified data of IEEE 118-bus power system, and
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MATLAB code for generator start-up sequence of IEEE 30-bus power system.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (51777185).
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Journal of Energy Engineering
Volume 148 • Issue 1 • February 2022
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© 2021 American Society of Civil Engineers.
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Received: Apr 1, 2021
Accepted: Sep 22, 2021
Published online: Oct 30, 2021
Published in print: Feb 1, 2022
Discussion open until: Mar 30, 2022
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