Bundled Generation and Transmission Planning Under Demand and Wind Generation Uncertainty Based on a Combination of Robust and Stochastic Optimization

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Arash Baharvandi (Author) Other; Jamshid Aghaei (Author) Other; Taher Niknam (Author) Other; Miadreza Shafie-Khah (Author) Other; Radu Godina (Author) Other; João P. S. Catalão (Author) FEUP

Journal

Title: IEEE Transactions on Sustainable Energy

Vol. 9 No. 3

Pages: 1477-1486

ISSN: 1949-3029

Publisher: IEEE

Indexing

ISI Web of Knowledge - 48 Citations

Scopus - 61 Citations

INSPEC

Other information

Authenticus ID: P-00N-J71

DOI: 10.1109/tste.2018.2789398

Abstract (EN): Bundled generation and transmission expansion planning (BGTEP) aims to solve problems related to ascendant demand of power systems. A BGTEP model is considered in this paper and the optimal planning for a long-term period is obtained such that the cost of installation and operation would be minimized. Also, due to the recent orientation toward renewable energy sources, the influence of wind farms is involved in the methodology. An important aspect of load and wind power is their uncertain nature and the characteristic of being unforeseen. This matter is under consideration by a bounded and symmetric uncertainty optimization approach. In fact, the combination of two uncertainty methods, i.e., robust and stochastic optimization approaches are utilized and formulated in this paper. Besides, to cope with this uncertainty, Weibull distribution (WD) is considered as wind distribution, while load distribution is counted by a normal distribution (ND). A unique approximation approach for WD to be considered as ND is presented. In addition, a linear formulation is obtained by alternative constraints in order to drastically reduce the level of complexity of the formulation. Accordingly, a mixedinteger linear programming formulation is proposed to solve the BGTEP problem. The modified 6-bus and IEEE 24-bus RTS test systems are used to prove the applicability of the proposed method.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10