A synergetic control architecture for the integration of photovoltaic generation and battery energy storage in DC microgrids

2019 ◽  
Vol 20 ◽  
pp. 100250
Author(s):  
N. Eghtedarpour
2017 ◽  
Author(s):  
◽  
William Noah Wills

A method for sizing battery energy storage (BES) systems for use in mitigating voltage flicker caused by solar intermittency in photovoltaic generation was developed. The method creates a "design day" from existing solar data and designs the power and energy requirements for a BES system that can help a photovoltaic facility mitigate flicker caused by solar activity associated with the design day. An economic analysis of lead-acid and lithium-ion options for the BES was also developed. The method was then applied to a proposed photovoltaic project in the Midwestern United States.


Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2289 ◽  
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Edwin Rivas-Trujillo

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).


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