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Please use this identifier to cite or link to this item: https://dspace.ucuenca.edu.ec/handle/123456789/34307
Title: AC transmission expansion planning considering uncertainty
Authors: Sanchez Cueva, Richard Mauricio
Castro, Carlos Alberto
Torres Contreras, Santiago Patricio
Villacres Enriquez, Luis Ricardo
Keywords: AC model
Simheuristic
Transmission Expansion Planning
AC Model
Uncertainty
Uncertainty
Transmission Expansion Planning
Simheuristic
Montecarlo
Montecarlo
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 2. Ingeniería y Tecnología
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 2.2.1 Ingeniería Eléctrica y Electrónica
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 2.2 Ingenierias Eléctrica, Electrónica e Información
metadata.dc.ucuenca.areaconocimientounescoamplio: 07 - Ingeniería, Industria y Construcción
metadata.dc.ucuenca.areaconocimientounescodetallado: 0713 - Electricidad y Energia
metadata.dc.ucuenca.areaconocimientounescoespecifico: 071 - Ingeniería y Profesiones Afines
Issue Date: 2019
metadata.dc.ucuenca.embargoend: 14-May-2050
metadata.dc.ucuenca.volumen: Volumen 0
metadata.dc.source: Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
metadata.dc.identifier.doi: 10.1109/ISGTEurope.2019.8905689
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.description.city: 
Bucharest
metadata.dc.type: ARTÍCULO DE CONFERENCIA
Abstract: 
© 2019 IEEE. Taking into account uncertainty into the Transmission Expansion Planning (TEP) problem is an important and complex issue. So far, the literature has proposed only simplified models in order to solve this problem. In this research work, a formulation and solution method to solve the Transmission System Expansion Planning problem considering uncertainty and using the AC network model is proposed. A simheuristic technique that combines simulation with an Ant Colony Optimization algorithm is used. The Montecarlo Simulation (MS) technique to handle the stochastic behavior of demand and generation, and the Ant Colony Optimization algorithm for continuous domains (ACOR) to find the optimal solution of the problem were employed. The results were obtained for different test scenarios on the Garver 6-bus and the IEEE 24-bus test systems.
Description: 
© 2019 IEEE. Taking into account uncertainty into the Transmission Expansion Planning (TEP) problem is an important and complex issue. So far, the literature has proposed only simplified models in order to solve this problem. In this research work, a formulation and solution method to solve the Transmission System Expansion Planning problem considering uncertainty and using the AC network model is proposed. A simheuristic technique that combines simulation with an Ant Colony Optimization algorithm is used. The Montecarlo Simulation (MS) technique to handle the stochastic behavior of demand and generation, and the Ant Colony Optimization algorithm for continuous domains (ACOR) to find the optimal solution of the problem were employed. The results were obtained for different test scenarios on the Garver 6-bus and the IEEE 24-bus test systems.
URI: http://dspace.ucuenca.edu.ec/handle/123456789/34307
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85075895453&origin=inward
metadata.dc.ucuenca.urifuente: https://ieeexplore.ieee.org/document/8905614
ISBN: 9781538682180
ISSN: 000-000-000-0
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