LAPSE:2019.1381
Published Article
LAPSE:2019.1381
An N-k Analytic Method of Composite Generation and Transmission with Interval Load
Shaoyun Hong, Haozhong Cheng, Pingliang Zeng
December 10, 2019
N-k contingency estimation plays a very important role in the operation and expansion planning of power systems, the method of which is traditionally based on heuristic screening. This paper stringently analyzes the best and worst states of power systems given the uncertainties of N-k contingency and interval load. For the sake of simplification and tractable computation, an approximate direct current (DC) power flow model was used. Rigorous optimization models were established for identifying the worst and best scenarios considering the contingencies of generators and transmission lines together with their uncertain loads. It is very useful to identify the worst N-k contingencies with interval loads. If the worst existing scenario meets security standards, all scenarios must satisfy it. The mathematical model established for finding the worst N-k contingency with interval load is a bi-level optimization model. In this paper, strong duality theory and mathematical linearization were applied to the solution of bi-level optimization. The computational results of standard cases validate the effectiveness of the proposed method and illustrate that generator contingency has more impact on minimum load shedding than transmission line contingency.
Keywords
interval load, minimum load shedding, mixed integer linear programming, the worst contingency of power system, transmission expansion planning
Suggested Citation
Hong S, Cheng H, Zeng P. An N-k Analytic Method of Composite Generation and Transmission with Interval Load. (2019). LAPSE:2019.1381
Author Affiliations
Hong S: Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China [ORCID]
Cheng H: Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Zeng P: Electric Power Research Institute of China, Beijing 100192, China
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Journal Name
Energies
Volume
10
Issue
2
Article Number
E168
Year
2017
Publication Date
2017-01-29
Published Version
ISSN
1996-1073
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Original Submission
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PII: en10020168, Publication Type: Journal Article
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LAPSE:2019.1381
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doi:10.3390/en10020168
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Dec 10, 2019
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Dec 10, 2019
 
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Dec 10, 2019
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Calvin Tsay
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