Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids

This paper deals with the problem of optimal location and reallocation of battery energy storage systems (BESS) in direct current (dc) microgrids with constant power loads. The optimization model that represents this problem is formulated with two objective functions. The first model corresponds to...

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Main Authors: Oscar Danilo Montoya, Walter Gil-González, Edwin Rivas-Trujillo
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/9/2289
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spelling doaj-e66d1fb0952a48dcb45982ebd23cf6e52020-11-25T02:01:33ZengMDPI AGEnergies1996-10732020-05-01132289228910.3390/en13092289Optimal Location-Reallocation of Battery Energy Storage Systems in DC MicrogridsOscar Danilo Montoya0Walter Gil-González1Edwin Rivas-Trujillo2Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá D.C. 11021, ColombiaLaboratorio Inteligente de Energía, Universidad Tecnológica de Bolívar, Cartagena 131001, ColombiaFacultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá D.C. 11021, ColombiaThis paper deals with the problem of optimal location and reallocation of battery energy storage systems (BESS) in direct current (dc) microgrids with constant power loads. The optimization model that represents this problem is formulated with two objective functions. The first model corresponds to the minimization of the total daily cost of buying energy in the spot market by conventional generators and the second to the minimization of the costs of the daily energy losses in all branches of the network. Both the models are constrained by classical nonlinear power flow equations, distributed generation capabilities, and voltage regulation, among others. These formulations generate a nonlinear mixed-integer programming (MINLP) model that requires special methods to be solved. A dc microgrid composed of 21-nodes with existing BESS is used for validating the proposed mathematical formula. This system allows to identify the optimal location or reallocation points for these batteries by improving the daily operative costs regarding the base cases. All the simulations are conducted via the general algebraic modeling system, widely known as the General Algebraic Modeling System (GAMS).https://www.mdpi.com/1996-1073/13/9/2289battery energy storage systemeconomic dispatch problemnonlinear programming formulationoptimal reallocation of batteriesmathematical optimization
collection DOAJ
language English
format Article
sources DOAJ
author Oscar Danilo Montoya
Walter Gil-González
Edwin Rivas-Trujillo
spellingShingle Oscar Danilo Montoya
Walter Gil-González
Edwin Rivas-Trujillo
Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
Energies
battery energy storage system
economic dispatch problem
nonlinear programming formulation
optimal reallocation of batteries
mathematical optimization
author_facet Oscar Danilo Montoya
Walter Gil-González
Edwin Rivas-Trujillo
author_sort Oscar Danilo Montoya
title Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
title_short Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
title_full Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
title_fullStr Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
title_full_unstemmed Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids
title_sort optimal location-reallocation of battery energy storage systems in dc microgrids
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-05-01
description This paper deals with the problem of optimal location and reallocation of battery energy storage systems (BESS) in direct current (dc) microgrids with constant power loads. The optimization model that represents this problem is formulated with two objective functions. The first model corresponds to the minimization of the total daily cost of buying energy in the spot market by conventional generators and the second to the minimization of the costs of the daily energy losses in all branches of the network. Both the models are constrained by classical nonlinear power flow equations, distributed generation capabilities, and voltage regulation, among others. These formulations generate a nonlinear mixed-integer programming (MINLP) model that requires special methods to be solved. A dc microgrid composed of 21-nodes with existing BESS is used for validating the proposed mathematical formula. This system allows to identify the optimal location or reallocation points for these batteries by improving the daily operative costs regarding the base cases. All the simulations are conducted via the general algebraic modeling system, widely known as the General Algebraic Modeling System (GAMS).
topic battery energy storage system
economic dispatch problem
nonlinear programming formulation
optimal reallocation of batteries
mathematical optimization
url https://www.mdpi.com/1996-1073/13/9/2289
work_keys_str_mv AT oscardanilomontoya optimallocationreallocationofbatteryenergystoragesystemsindcmicrogrids
AT waltergilgonzalez optimallocationreallocationofbatteryenergystoragesystemsindcmicrogrids
AT edwinrivastrujillo optimallocationreallocationofbatteryenergystoragesystemsindcmicrogrids
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