Probabilistic transmission expansion planning for increasing wind power penetration

Jing Qiu; Junhua Zhao; Zhao Yang Dong

Probabilistic transmission expansion planning for increasing wind power penetration

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Author(s): Jing Qiu ¹ ; Junhua Zhao ² ; Zhao Yang Dong ³
- Affiliations: 1: The Commonwealth Scientific and Industrial Research Organization (CSIRO), University of Newcastle, Newcastle, Australia ;
  2: School of Science and Engineering, Chinese University of Hong Kong, Shenzhen, Guangdong, People's Republic of China ;
  3: School of Electrical and Information Engineering, University of Sydney, Sydney NSW2006, Australia
Source: Volume 11, Issue 6, 10 May 2017, p. 837 – 845
DOI: 10.1049/iet-rpg.2016.0794 , Print ISSN 1752-1416, Online ISSN 1752-1424

Received 13/09/2016, Accepted 14/02/2017, Revised 20/12/2016, Published 22/02/2017

Wind power is one of the promising renewable energy resources to achieve energy sustainability. Its growth poses increasing financial and technical challenges to power systems, mainly due to the wind intermittency. Existing transmission networks may require infrastructure investment, in order to maintain the economical, secure and reliable operations of power systems with increasing wind power penetration. This study proposes a stochastic transmission expansion planning (TEP) framework to assess the impacts of wind power penetration and demand response incorporation. A risk constraint on load curtailment is introduced and its effect on TEP solutions is investigated. Also, to reduce the complexity and size the formulated TEP problem, a decomposition-based approach is adopted. According to the numerical results on the Garver's six-bus and the modified IEEE 30-bus systems, the solutions of TEP are subject to the variation of wind power characteristics and cannot be determined straightforward. Hence risk-analysis should be carried out to guide transmission investment with increased flexibility. The incorporation of wind power uncertainty increases the total cost and expected energy not supplied, which can be mitigated by the proposed TEP approach.

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