Multi-objective transmission expansion planning considering uncertainty in wind power and demand

Carlos Adrian Correa-Florez; Alejandro Sanchez Salcedo; Andres Felipe Panesso

doi:10.1109/TDC-LA.2016.7805681

Multi-objective transmission expansion planning considering uncertainty in wind power and demand

Carlos Adrian Correa-Florez, Alejandro Sanchez Salcedo, Andres Felipe Panesso

Producción: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

This paper presents a multi-objective methodology for the Transmission Expansion Planning (TEP) problem when uncertainty in demand and large wind generation is considered. The proposed scheme is based on Reduced Scenario Methodology (RSM) to represent the uncertainty set. An enhanced NSGA-II multi-objective algorithm is used to minimize expansion costs and wind power curtailment, so that a set of Pareto optimal expansion plans are obtained. The performance of the expansion plans is evaluated and compared with previous work to demonstrate the robustness of the proposed approach. Test are carried out on Garver and the IEEE 24-bus RTS systems.

Idioma original	Inglés
Título de la publicación alojada	2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781509028757
DOI	https://doi.org/10.1109/TDC-LA.2016.7805681
Estado	Publicada - 04 ene. 2017
Publicado de forma externa	Sí
Evento	2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016 - Morelia, México Duración: 20 sep. 2016 → 24 sep. 2016

Serie de la publicación

Nombre	2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016

Conferencia

Conferencia	2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016
País/Territorio	México
Ciudad	Morelia
Período	20/09/16 → 24/09/16

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1109/TDC-LA.2016.7805681

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Correa-Florez, C. A., Salcedo, A. S., & Panesso, A. F. (2017). Multi-objective transmission expansion planning considering uncertainty in wind power and demand. En 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016 Artículo 7805681 (2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TDC-LA.2016.7805681

Correa-Florez, Carlos Adrian ; Salcedo, Alejandro Sanchez ; Panesso, Andres Felipe. / Multi-objective transmission expansion planning considering uncertainty in wind power and demand. 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc., 2017. (2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016).

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title = "Multi-objective transmission expansion planning considering uncertainty in wind power and demand",

abstract = "This paper presents a multi-objective methodology for the Transmission Expansion Planning (TEP) problem when uncertainty in demand and large wind generation is considered. The proposed scheme is based on Reduced Scenario Methodology (RSM) to represent the uncertainty set. An enhanced NSGA-II multi-objective algorithm is used to minimize expansion costs and wind power curtailment, so that a set of Pareto optimal expansion plans are obtained. The performance of the expansion plans is evaluated and compared with previous work to demonstrate the robustness of the proposed approach. Test are carried out on Garver and the IEEE 24-bus RTS systems.",

keywords = "Multi-objective optimization, Robust expansion plans, Transmission planning, Uncertainty, Wind generation",

author = "Correa-Florez, {Carlos Adrian} and Salcedo, {Alejandro Sanchez} and Panesso, {Andres Felipe}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016 ; Conference date: 20-09-2016 Through 24-09-2016",

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Correa-Florez, CA, Salcedo, AS & Panesso, AF 2017, Multi-objective transmission expansion planning considering uncertainty in wind power and demand. En 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016., 7805681, 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016, Morelia, México, 20/09/16. https://doi.org/10.1109/TDC-LA.2016.7805681

Multi-objective transmission expansion planning considering uncertainty in wind power and demand. / Correa-Florez, Carlos Adrian; Salcedo, Alejandro Sanchez; Panesso, Andres Felipe.
2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7805681 (2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016).

Producción: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Multi-objective transmission expansion planning considering uncertainty in wind power and demand

AU - Correa-Florez, Carlos Adrian

AU - Salcedo, Alejandro Sanchez

AU - Panesso, Andres Felipe

PY - 2017/1/4

Y1 - 2017/1/4

N2 - This paper presents a multi-objective methodology for the Transmission Expansion Planning (TEP) problem when uncertainty in demand and large wind generation is considered. The proposed scheme is based on Reduced Scenario Methodology (RSM) to represent the uncertainty set. An enhanced NSGA-II multi-objective algorithm is used to minimize expansion costs and wind power curtailment, so that a set of Pareto optimal expansion plans are obtained. The performance of the expansion plans is evaluated and compared with previous work to demonstrate the robustness of the proposed approach. Test are carried out on Garver and the IEEE 24-bus RTS systems.

AB - This paper presents a multi-objective methodology for the Transmission Expansion Planning (TEP) problem when uncertainty in demand and large wind generation is considered. The proposed scheme is based on Reduced Scenario Methodology (RSM) to represent the uncertainty set. An enhanced NSGA-II multi-objective algorithm is used to minimize expansion costs and wind power curtailment, so that a set of Pareto optimal expansion plans are obtained. The performance of the expansion plans is evaluated and compared with previous work to demonstrate the robustness of the proposed approach. Test are carried out on Garver and the IEEE 24-bus RTS systems.

KW - Multi-objective optimization

KW - Robust expansion plans

KW - Transmission planning

KW - Uncertainty

KW - Wind generation

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AN - SCOPUS:85016184768

T3 - 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016

BT - 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016

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Correa-Florez CA, Salcedo AS, Panesso AF. Multi-objective transmission expansion planning considering uncertainty in wind power and demand. En 2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7805681. (2016 IEEE PES Transmission and Distribution Conference and Exposition-Latin America, PES T and D-LA 2016). doi: 10.1109/TDC-LA.2016.7805681

Multi-objective transmission expansion planning considering uncertainty in wind power and demand

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