A mixed-integer second-order cone model for optimal siting and sizing of dynamic reactive power compensators in distribution grids

The problem of the optimal placement and sizing of dynamic reactive power compensators in AC distribution networks is addressed in this paper from convex optimization. The exact mixed-integer nonlinear programming (MINLP) model is transformed into a mixed-integer second-order cone programming (MISOC...

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Autores:
Gil González, Walter Julián
Montoya, Oscar Danilo
Grisales-Noreña, Luis Fernando
Leonardo Trujillo, Cesar
Giral-Ramírez, Diego Armando
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/11122
Acceso en línea:
https://hdl.handle.net/20.500.12585/11122
https://doi.org/10.1016/j.rineng.2022.100475
Palabra clave:
Dynamic reactive power compensators
Mixed-integer convex optimization
Radial distribution networks
Second-order cone programming
Branch optimal power flow
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description
Summary:The problem of the optimal placement and sizing of dynamic reactive power compensators in AC distribution networks is addressed in this paper from convex optimization. The exact mixed-integer nonlinear programming (MINLP) model is transformed into a mixed-integer second-order cone programming (MISOCP) model. The main advantage of the MISOCP formulation is the possibility of finding a global optimum with branch & cut combined with interior-point method due to the convex structure of the continuous part of the problem, i.e., the multi-period branch optimal power flow. The dynamic reactive power compensators are sized and dimensioned considering daily load curves and variable reactive power injections. Numerical validations are tested in the 33- and 69-bus test feeders using the CVX tool available for MATLAB with the MOSEK solver. These simulations demonstrate the effectiveness and robustness of the MISOCP approach when compared with the solution of the exact MINLP obtained in the GAMS software.