TY - JOUR
T1 - Online optimization of a multi-conversion-level DC home microgrid for system efficiency enhancement
AU - Boscaino, V.
AU - Guerrero, J. M.
AU - Ciornei, I.
AU - Meng, L.
AU - Riva Sanseverino, E.
AU - Zizzo, G.
PY - 2017/11
Y1 - 2017/11
N2 - In this paper, an on-line management system for the optimal efficiency operation of a multi-bus DC home distribution system is proposed. The operation of the system is discussed with reference to a distribution system with two conversion stages and three voltage levels. In each of the conversion stages, three paralleled DC/DC converters are implemented. A Genetic Algorithm performs the on-line optimization of the DC network’s global efficiency, generating the optimal current sharing ratios of the concurrent power converters. The overall DC/DC conversion system including the optimization section is modelled using MATLAB/Simulink. Thanks to the implemented online algorithm, considering the system modelling as dynamic master/slave configuration, reliability, robustness and flexibility of the whole conversion system is enhanced. Since an online algorithm is implemented, several variables are accounted for, such as: components loss parameters, components ageing, load currents, switching frequency and input voltage. Simulation results considering several case studies are presented and the benefits brought by the optimization algorithm in terms of power saving are widely discussed for each case study.
AB - In this paper, an on-line management system for the optimal efficiency operation of a multi-bus DC home distribution system is proposed. The operation of the system is discussed with reference to a distribution system with two conversion stages and three voltage levels. In each of the conversion stages, three paralleled DC/DC converters are implemented. A Genetic Algorithm performs the on-line optimization of the DC network’s global efficiency, generating the optimal current sharing ratios of the concurrent power converters. The overall DC/DC conversion system including the optimization section is modelled using MATLAB/Simulink. Thanks to the implemented online algorithm, considering the system modelling as dynamic master/slave configuration, reliability, robustness and flexibility of the whole conversion system is enhanced. Since an online algorithm is implemented, several variables are accounted for, such as: components loss parameters, components ageing, load currents, switching frequency and input voltage. Simulation results considering several case studies are presented and the benefits brought by the optimization algorithm in terms of power saving are widely discussed for each case study.
KW - Active droop control
KW - Current sharing
KW - DC microgrids
KW - Genetic algorithm
KW - Master-slave control
KW - Peak shaving
KW - Power conversion efficiency
UR - http://www.scopus.com/inward/record.url?scp=85028454530&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2017.08.014
DO - 10.1016/j.scs.2017.08.014
M3 - Journal article
AN - SCOPUS:85028454530
SN - 2210-6707
VL - 35
SP - 417
EP - 429
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
ER -