Title :
Transmission network expansion planning with wind energy integration: A stochastic programming model
Author :
Guo Chen ; ZhaoYang Dong ; Hill, D.J.
Author_Institution :
Sch. of Electr. & Inf. Eng., Univ. of Sydney, Sydney, NSW, Australia
Abstract :
The growing penetration of wind energy has introduced increasing uncertainties to power grids. As a result, it is necessary to develop new models and algorithms in transmission network expansion planning (TNEP) so as to deal with the risks. In this paper a stochastic programming model is proposed to carry out the TNEP. Moreover, an effective hybrid algorithm, which is the combination of evolutionary algorithms (EA) and Benders´ Decomposition (BD) technique, is developed to solve the formed programming model. Theoretically, the EAs have the advantage of rapidly locating a high-quality region and the BD can accelerate the search to find the optimal solution within the region. In addition, the hybrid method is tested by the modified Garver´s system and the IEEE 14 bus system. Promising results are obtained to validate its effectiveness.
Keywords :
evolutionary computation; power grids; power transmission planning; stochastic programming; wind power; BD technique; Benders decomposition technique; EA; IEEE 14 bus system; TNEP; effective hybrid algorithm; evolutionary algorithms; modified Garver system; power grids; stochastic programming model; transmission network expansion planning; wind energy integration; Load modeling; Mathematical model; Planning; Programming; Sociology; Statistics; Stochastic processes; Hybrid algorithm; Stochastic programming; Transmission network expansion planning; Wind power; evolutionary computation;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6344752