On the Optimal Selection and Integration of Batteries in DC Grids through a Mixed-Integer Quadratic Convex Formulation

• Published in: Electronics (Basel) 2021-10, Vol.10 (19), p.2339
• Main Authors: Serra, Federico Martin, Montoya, Oscar Danilo, Alvarado-Barrios, Lázaro, Álvarez-Arroyo, Cesar, Chamorro, Harold R.
• Format: Article
• Language: English
• Subjects: Branch and bound methods; Convexity; Costs; Efficiency; Energy storage; Genetic algorithms; Hyperplanes; Linear programming; Mathematical models; Mixed integer; Optimization; Quadratic programming
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics10192339

This paper deals with the problem of the optimal selection and location of batteries in DC distribution grids by proposing a new mixed-integer convex model. The exact mixed-integer nonlinear model is transformed into a mixed-integer quadratic convex model (MIQC) by approximating the product among voltages in the power balance equations as a hyperplane. The most important characteristic of our proposal is that the MIQC formulations ensure the global optimum reaching via branch & bound methods and quadratic programming since each combination of the binary variables generates a node with a convex optimization subproblem. The formulation of the objective function is associated with the minimization of the energy losses for a daily operation scenario considering high renewable energy penetration. Numerical simulations show the effectiveness of the proposed MIQC model to reach the global optimum of the optimization model when compared with the exact optimization model in a 21-node test feeder. All the validations are carried out in the GAMS optimization software.