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An improved weighted mean of vectors algorithm for microgrid energy management considering demand response.

Authors :
Alamir, Nehmedo
Kamel, Salah
Hassan, Mohamed H.
Abdelkader, Sobhy M.
Source :
Neural Computing & Applications. Oct2023, Vol. 35 Issue 28, p20749-20770. 22p.
Publication Year :
2023

Abstract

The integration of demand response programs (DRPs) into the energy management (EM) system of microgrids (MGs) helps in improving the load characteristics by allowing consumers to interoperate for achieving techno-economic advantages. In this paper, an improved algorithm is called LINFO is proposed for modifying search ability of the original weIghted meaN oF vectOrs (INFO) algorithm as well as avoiding its weaknesses like trapping in a local optima. The improved algorithm's efficiency is confirmed by comparing its results with those obtained by the original INFO and other optimization techniques using different standard benchmark test functions. Moreover, this improved algorithm and the original version are applied for solving the EM problem with the aim of optimizing the operation cost of the MGs in the presence DRPs. They are used to solve day-ahead EM problem for optimal operation of renewable energy resources, the optimal generation from a conventional diesel engines (DEs); taking into account the participation of customers in DRP for minimizing MG operating cost, which includes the cost of DEs fuel and the power transactions cost with the main grid. To demonstrate the efficacy of the proposed LINFO, simulation results are compared with the results of well-known and newly developed optimization techniques. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09410643
Volume :
35
Issue :
28
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
170899841
Full Text :
https://doi.org/10.1007/s00521-023-08813-5