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An adjustable robust optimization approach for the expansion planning of a virtual power plant

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IIT-22-290C.pdf (254.6Kb)
Date
2022-09-28
Author
Baringo Morales, Ana
Baringo Morales, Luis
Arroyo Sánchez, José Manuel
Estado
info:eu-repo/semantics/publishedVersion
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Abstract
 
 
This paper proposes a novel approach based on adjustable robust optimization for the expansion planning of a virtual power plant (VPP) that participates in the energy electricity market. The VPP comprises conventional, renewable, and storage units, as well as flexible demands, and analyzes the possibility of building new conventional, renewable, and storage units with the aim of maximizing its profit. The uncertainty related to future production costs of the conventional generating units, future consumption levels of the flexible demands, and future energy market prices is modeled using confidence bounds and uncertainty budgets. The resulting model is formulated as a trilevel program with lower-level binary variables that is solved using a nested column-and-constraint generation algorithm. Results from a case study show the effective performance of the proposed approach.
 
URI
http://hdl.handle.net/11531/97788
An adjustable robust optimization approach for the expansion planning of a virtual power plant
Tipo de Actividad
Capítulos en libros
Materias/ categorías / ODS
Instituto de Investigación Tecnológica (IIT)
Palabras Clave

Adjustable robust optimization , expansion planning , nested column-and-constraint generation algorithm , uncertainty , virtual power plant
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