TY - JOUR
T1 - Multi-objective transmission expansion planning considering multiple generation scenarios
AU - Correa Florez, Carlos A.
AU - Bolaños Ocampo, Ricardo A.
AU - Escobar Zuluaga, Antonio H.
PY - 2014/11
Y1 - 2014/11
N2 - This paper shows a methodology for solving the Transmission Expansion Planning (TEP) problem when Multiple Generation Scenarios (MGS) are considered. MGS are a result of the multiple load flow patterns caused by realistic operation of the network, such as market rules, availability of generators, weather conditions or fuel prices. The solution to this problem is carried out by using multiobjective evolutionary strategies for the optimization process, implementing a new hybrid modified NSGA-II/Chu-Beasley algorithm and taking into account variable demand and generation. The proposed methodology is validated using the 6-bus Garver system and the IEEE-24 bus system. The TEP is based on the DC model of the network and non-linear interior point method is used to initialize the population. A set of Pareto optimal expansion plans with different levels of cost and load shedding is found for each system, showing the robustness of the proposed approach.
AB - This paper shows a methodology for solving the Transmission Expansion Planning (TEP) problem when Multiple Generation Scenarios (MGS) are considered. MGS are a result of the multiple load flow patterns caused by realistic operation of the network, such as market rules, availability of generators, weather conditions or fuel prices. The solution to this problem is carried out by using multiobjective evolutionary strategies for the optimization process, implementing a new hybrid modified NSGA-II/Chu-Beasley algorithm and taking into account variable demand and generation. The proposed methodology is validated using the 6-bus Garver system and the IEEE-24 bus system. The TEP is based on the DC model of the network and non-linear interior point method is used to initialize the population. A set of Pareto optimal expansion plans with different levels of cost and load shedding is found for each system, showing the robustness of the proposed approach.
KW - Generation scenarios
KW - Market
KW - Multiobjective optimization
KW - Pareto front
KW - Transmission planning
UR - http://www.scopus.com/inward/record.url?scp=84901921588&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2014.04.063
DO - 10.1016/j.ijepes.2014.04.063
M3 - Article
AN - SCOPUS:84901921588
SN - 0142-0615
VL - 62
SP - 398
EP - 409
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
ER -