- Title
- Network reinforcement for grid resiliency under extreme events
- Creator
- Qiu, Jing; Reedman, Luke J.; Dong, Zhao Yang; Meng, Ke; Tian, Huiqiao; Zhao, Junhua
- Relation
- 2017 IEEE Power & Energy Society General Meeting. Proceedings of the 2017 IEEE Power & Energy Society General Meeting (Chicago, IL 16-20 July, 2017)
- Publisher Link
- http://dx.doi.org/10.1109/PESGM.2017.8273985
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2017
- Description
- To enhance the energy grid resiliency under extreme events (EEs), this paper presents a multi-objective transmission expansion planning (TEP) framework. Rather than using the conventional deterministic reliability criterion, a risk component is used to capture the stochastic nature of power systems. The formulation of risk value after risk aversion is explicitly given, and it aims to provide network planners with the flexibility to select a more resilient plan according to their individual risk preferences. In addition, a relatively new multi-objective evolutionary algorithm called the MOEA/D is introduced and employed to find Pareto optimal solutions, and tradeoffs between overall cost and unreliability risk are provided. The proposed approach is numerically verified on the IEEE Garver's 6-bus system. Case study results demonstrate that the proposed approach can effectively improve network resiliency under EEs.
- Subject
- power system planning; grid resiliency; extreme events; multi-objective optimization
- Identifier
- http://hdl.handle.net/1959.13/1390736
- Identifier
- uon:33119
- Identifier
- ISBN:9781538622131
- Identifier
- ISSN:1944-9933
- Language
- eng
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