Electric energy transmission is essential for the operation of competitive energy markets. Transmission expansion planning has been defined as a complex combinatorial optimization problem. This work puts forward a description of the solution techniques and alternatives to implement the transmission system's expansion. A model that considers Multi-objective Optimization - MOO - criteria is proposed under the concepts of Tabu Search - TS - Ordinal Optimization - OO - and Pareto optimality. The model proposed generates expansion plans under the Pareto optimality approach. It shows acceptable solutions under robustness and algorithmic speed criteria. The results obtained in the test systems show that the model developed is effective to find the solution for the combinatorial problem. Multi-objective optimization defines a set of feasible solutions that establishes expansion plans scenarios.
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Autor | Molina Castro, Juan David Rudnick Van de Wyngard, Hugh |
Título | Transmission expansion plan: Ordinal and metaheuristic multiobjective optimization |
ISBN | 978-1424484188 |
Fecha de publicación | 2011 |
Resumen | Electric energy transmission is essential for the operation of competitive energy markets. Transmission expansion planning has been defined as a complex combinatorial optimization problem. This work puts forward a description of the solution techniques and alternatives to implement the transmission system's expansion. A model that considers Multi-objective Optimization - MOO - criteria is proposed under the concepts of Tabu Search - TS - Ordinal Optimization - OO - and Pareto optimality. The model proposed generates expansion plans under the Pareto optimality approach. It shows acceptable solutions under robustness and algorithmic speed criteria. The results obtained in the test systems show that the model developed is effective to find the solution for the combinatorial problem. Multi-objective optimization defines a set of feasible solutions that establishes expansion plans scenarios. |
Derechos | acceso restringido |
DOI | 10.1109/PTC.2011.6019175 |
Editorial | IEEE |
Enlace | https://doi.org/10.1109/PTC.2011.6019175 https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6019175 |
Palabra clave | Optimization Investments Planning Genetic algorithms Robustness Load flow |
Publicado en / Colección | IEEE Trondheim PowerTech (2011 : Trondheim, Noruega) |
Tipo de documento | comunicación de congreso |