DocumentCode :
1539209
Title :
Energy management onboard the Space Station-a rule-based approach
Author :
Bouzguenda, Mounir ; Rahman, Saifur
Author_Institution :
Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
Volume :
27
Issue :
2
fYear :
1991
fDate :
3/1/1991 12:00:00 AM
Firstpage :
302
Lastpage :
310
Abstract :
The logic and the schedule for a rule-based optimization technique useful for energy management onboard the Space Station are presented. A diverse array of experiments is scheduled within the constraints of limited solar energy and battery storage availability, taking into account the uneven energy supply between the sunshine and eclipse periods and the occasional need to serve a peak load and the full battery charging load simultaneously. In addition, the noninterruptible and nonrestartable nature of many experiments has to be accounted for in the schedule. These factors have been accounted for by using various time intervals and priority weighting factors. Supply/demand windows of various durations are tested for the typical load profile. This shows under what circumstances fewer scheduling tasks are needed and how a closer match between the supply and demand can be obtained. The optimal supply/demand is expressed in terms of the excess and shortage of electricity, the peak load, and the time displacement of the individual payloads. This technique is implemented using Prolog and Fortran
Keywords :
aerospace computing; battery storage plants; knowledge based systems; load management; optimisation; power system analysis computing; solar cell arrays; space vehicle power plants; Fortran; Prolog; Space Station; battery charging; battery storage; eclipse; energy management; energy supply; knowledge based system; load profile; noninterruptible power supply; nonrestartable power supply; peak load; priority weighting; rule-based optimization; scheduling; simulation; solar energy; space vehicle; sunshine; supply demand window; time displacement; Batteries; Energy management; Expert systems; Photovoltaic systems; Power system management; Power system modeling; Power system reliability; Processor scheduling; Space stations; Space vehicles;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.78305
Filename :
78305
Link To Document :
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