An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty

Zipeng Liang, Haoyong Chen, Xiaojuan Wang, Idris Ibn Idris, Bifei Tan and Cong Zhang
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Zipeng Liang: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Haoyong Chen: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Xiaojuan Wang: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Idris Ibn Idris: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Bifei Tan: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Cong Zhang: School of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Energies, 2018, vol. 11, issue 8, 1-22

Abstract: The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluctuations. A Benders’ decomposition algorithm is developed to solve the proposed two-stage model. Finally, extensive numerical studies are conducted with Garver’s 6-bus system, a modified IEEE RTS79 system and IEEE 118-bus system, and the computational results demonstrate the effectiveness and practicability of the proposed method.

Keywords: transmission network expansion planning; wind power; uncertainty; load shedding; benders’ decomposition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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