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  4. Assessment of a multi-agent mixed-integer optimization algorithm for battery scheduling
 
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Assessment of a multi-agent mixed-integer optimization algorithm for battery scheduling

Publikationstyp
Conference Paper
Date Issued
2018-06-12
Sprache
English
Author(s)
Murray, Alexander
Faulwasser, Timm  
Hagenmeyer, Veit  
TORE-URI
https://hdl.handle.net/11420/46281
Start Page
453
End Page
455
Citation
Proceedings of the 9th ACM International Conference on Future Energy Systems, e-Energy 2018: 453-455 (2018)
Contribution to Conference
9th ACM International Conference on Future Energy Systems, e-Energy 2018  
Publisher DOI
10.1145/3208903.3212058
Scopus ID
2-s2.0-85050179571
Publisher
ACM
ISBN
9781450357678
In the present paper, the problem of scheduling populations of energy storage systems including asymmetric charging and discharging e ciencies is formulated as a mixed integer program. The problem is solved using both a novel distributed local mixed integer solution scheme and a global mixed integer solver. We draw upon a detailed numerical comparison of both methods via a simulation example built using real PV generation data consisting of 54 energy storage systems over a horizon of 48 time steps leading to 2640 integer variables. Our results indicate that the distributed local solution method delivers values comparable to the centralized global solver but in significantly reduced time.
DDC Class
004: Computer Sciences
333.7: Natural Resources, Energy and Environment
510: Mathematics
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