Blackstart Capability Planning For Power System Restoration
Keywords
Blackstart capability; Integer programming; Power system restoration; Restoration planning; Transmission path search
Abstract
Blackstart capability is essential for power system restoration following a blackout. System restoration planners determine the restoration sequences to provide cranking power from blackstart units (BSUs) to non-blackstart units (NBSUs), pick up critical loads, and energize the necessary transmission paths. This paper proposes a new algorithm for optimization of the restoration actions. An optimal search algorithm is proposed to determine the plan to crank NBSUs through the selected paths of transmission lines. Assuming that the generation capability of a BSU is constant, the method is used to optimize the overall system MWHr generation capabilities from NBSUs. To reduce the computational complexity of system restoration planning, a new generator model is proposed that results in a linear integer programming (IP) formulation. Linearity of the IP problem formulation ensures that the global optimality is achieved. The optimal power flow (OPF) is used to examine the feasibility of planned restoration actions. Test cases from the IEEE 39-bus system, ISO New England system, and Duke-Indiana system are used to validate the proposed algorithm. Numerical simulations demonstrate that the proposed method is computationally efficient for real-world power system cases.
Publication Date
3-1-2017
Publication Title
International Journal of Electrical Power and Energy Systems
Volume
86
Number of Pages
127-137
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.ijepes.2016.10.008
Copyright Status
Unknown
Socpus ID
84999635233 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84999635233
STARS Citation
Jiang, Yazhou; Chen, Sijie; Liu, Chen Ching; Sun, Wei; and Luo, Xiaochuan, "Blackstart Capability Planning For Power System Restoration" (2017). Scopus Export 2015-2019. 5186.
https://stars.library.ucf.edu/scopus2015/5186