About the paper
| Title |
Genetic Algorithm Based Energy Demand-Side Management |
| Book |
ICIST 2014 Proceedings |
| Pages |
61-66 |
| Abstract: Application of demand-side management (DSM)
plays today an important role in energy management both
in industrial and residential domain. This paper proposes a
generic approach to DSM which is based on the genetic
algorithm (GA), as one of the powerful search heuristics
inspired by the process of natural evolution. The proposed
approach was defined flexibly enough to be capable of
discovering an optimal load distribution (e.g. from the
financial perspective) in practically any multiple energy
supply/multiple load facility infrastructure. Optimization of
the demand side was carried out by taking into account the
forecasted energy demand and applied tariff schemes as
well. Furthermore, a performance of the proposed approach
was verified at a multiple supply/multiple load use case
scenario. Based on the optimization results, it was concluded
that the proposed GA based solution could be successfully
utilized to facilitate decision making of energy managers
regarding the appropriate DSM measure selection. |
Full citation
Tomašević, N.,
Batić, M.,
Vraneš, S.
Genetic Algorithm Based Energy Demand-Side Management. In:
Zdravković, M.,
Trajanović, M.,
Konjović, Z.
(Eds.)
ICIST 2014 Proceedings, pp.61-66, Belgrade, Serbia, 2014
Keywords
Energy Management Systems
Machine learning