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A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids
by
Montoya, Oscar Danilo
, Chamorro, Harold R.
, Gil-González, Walter
, Alvarado-Barrios, Lazaro
, Garces, Alejandro
in
Approximation
/ combinatorial optimization
/ Convex analysis
/ convex approximations
/ Expected values
/ Generators
/ heuristic algorithm
/ Load
/ microgrids
/ Optimization
/ phase-balancing
/ unbalanced power distribution grids
2021
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A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids
by
Montoya, Oscar Danilo
, Chamorro, Harold R.
, Gil-González, Walter
, Alvarado-Barrios, Lazaro
, Garces, Alejandro
in
Approximation
/ combinatorial optimization
/ Convex analysis
/ convex approximations
/ Expected values
/ Generators
/ heuristic algorithm
/ Load
/ microgrids
/ Optimization
/ phase-balancing
/ unbalanced power distribution grids
2021
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids
by
Montoya, Oscar Danilo
, Chamorro, Harold R.
, Gil-González, Walter
, Alvarado-Barrios, Lazaro
, Garces, Alejandro
in
Approximation
/ combinatorial optimization
/ Convex analysis
/ convex approximations
/ Expected values
/ Generators
/ heuristic algorithm
/ Load
/ microgrids
/ Optimization
/ phase-balancing
/ unbalanced power distribution grids
2021
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A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids
Journal Article
A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids
2021
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Overview
Phase balancing is a classical optimization problem in power distribution grids that involve phase swapping of the loads and generators to reduce power loss. The problem is a non-linear integer and, hence, it is usually solved using heuristic algorithms. This paper proposes a mathematical reformulation that transforms the phase-balancing problem in low-voltage distribution networks into a mixed-integer convex quadratic optimization model. To consider both conventional secondary feeders and microgrids, renewable energies and their subsequent stochastic nature are included in the model. The power flow equations are linearized, and the combinatorial part is represented using a Birkhoff polytope B3 that allows the selection of phase swapping in each node. The numerical experiments on the CIGRE low-voltage test system demonstrate the use of the proposed formulation.
Publisher
MDPI AG
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