2020-03-262020-03-262019Montoya O.D., Gil-González W., Grisales-Norena L., Orozco-Henao C. y Serra F. (2019) Economic dispatch of BESS and renewable generators in DC microgrids using voltage-dependent load models. Energies; Vol. 12, Núm. 2319961073https://hdl.handle.net/20.500.12585/9253This paper addresses the optimal dispatch problem for battery energy storage systems (BESSs) in direct current (DC) mode for an operational period of 24 h. The problem is represented by a nonlinear programming (NLP) model that was formulated using an exponential voltage-dependent load model, which is the main contribution of this paper. An artificial neural network was employed for the short-term prediction of available renewable energy from wind and photovoltaic sources. The NLP model was solved by using the general algebraic modeling system (GAMS) to implement a 30-node test feeder composed of four renewable generators and three batteries. Simulation results demonstrate that the cost reduction for a daily operation is drastically affected by the operating conditions of the BESS, as well as the type of load model used. © 2019 MDPI AG. All rights reserved.Recurso electrónicoapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/Economic Dispatch of BESS and renewable generators in DC microgrids using voltage-dependent load modelsinfo:eu-repo/semantics/article10.3390/en12234494Artificial neural networksBattery energy storage systemEconomic dispatch problemBattery storageCost reductionData storage equipmentElectric batteriesElectric machine theoryNeural networksNonlinear programmingSchedulingBattery energy storage systemsEconomic dispatch problemsOperating conditionOperational periodsPhotovoltaic sourcesRenewable generatorsShort term predictionVoltage dependent load modelsElectric load dispatchinginfo:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 InternacionalUniversidad Tecnológica de BolívarRepositorio UTB5691956410057191493648557919912005548854940037104976300