DocumentCode
151722
Title
Multistage transmission expansion planning via network partitioning and principal variables identification
Author
Duque, Alex ; Escobar, Antonio Hernando ; Gallego, Ramon A.
Author_Institution
Dept. of Electr. Eng., Univ. Tecnol. de Pereira, Pereira, Colombia
fYear
2014
fDate
10-13 Sept. 2014
Firstpage
1
Lastpage
6
Abstract
This paper presents a method to solve multistage transmission expansion planning problem (MTEP) for highly complex systems. The method includes three partition criteria to separate the transmission network into several subsystems and four active power injection mechanisms to keep information from the interaction between subsystems. A principal variables identification process is applied to each subsystem in order to modify the limits of addition of new elements according to the significance of each right-of-way. These new limits are used to solve the MTEP for the original network, which now has a reduced search space. The MTEP is represented by an efficient version of the linear disjunctive model (DM). The obtained results show an outstanding performance in terms of quality of the answer and computation time. The best solutions known for complex test systems are improved thanks to this method.
Keywords
large-scale systems; power transmission planning; MTEP; active power injection mechanisms; complex systems; linear disjunctive model; multistage transmission expansion planning; network partitioning; principal variables identification process; reduced search space; transmission network; Active filters; Complexity theory; Filtering algorithms; Investment; Load flow; Partitioning algorithms; Planning; Multistage transmission expansion planning; network partitioning; optimization; principal variables; search space;
fLanguage
English
Publisher
ieee
Conference_Titel
Transmission & Distribution Conference and Exposition - Latin America (PES T&D-LA), 2014 IEEE PES
Conference_Location
Medellin
Print_ISBN
978-1-4799-6250-1
Type
conf
DOI
10.1109/TDC-LA.2014.6955221
Filename
6955221
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