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UID:pretalx-amfc2026-TNTZZ7@modelica.simtek.cc
DTSTART;TZID=CST:20260922T115500
DTEND;TZID=CST:20260922T122000
DESCRIPTION:SOFC/battery/PV hybrid energy system is widely used to generate
  electricity. However\, it is challenging to manage output power of each d
 evices while regulating the bus voltage within a safe range. To this end\,
  this paper proposes an optimal droop control strategy for the hybrid syst
 em\, which consists of solid oxide fuel cell (SOFC)\, lithium-ion battery 
 and photovoltaic (PV) array. First\, a group of nonlinear and implicit dif
 ferential equations including different sources and controllers is develop
 ed. Then\, multi-objective genetic algorithm is adopted to minimize the ou
 tput power error and the electricity loss simultaneously\, deriving the op
 timal droop control parameters as well as the feedback PI parameters. Fina
 lly\, the optimal solution is chosen from the Pareto front. Numerical expe
 riments demonstrate that the control performance of the proposed method is
  better than the single objective method while the electricity loss can be
  reduced by 96.26%..
DTSTAMP:20261004T070537Z
LOCATION:(Electric) Mobility & Buildings (R2003)
SUMMARY:Optimal Droop Control for SOFC/battery/PV Hybrid System Based on Mu
 lti-objective Genetic Algorithm - Zongrun Wang\, Li Sun
URL:https://modelica.simtek.cc/amfc2026/talk/TNTZZ7/
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