Smart Microgrid Energy Management Using a Novel Artificial Shark Optimization
Joint Authors
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-22, 22 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-08
Country of Publication
Egypt
No. of Pages
22
Main Subjects
Abstract EN
At present, renewable energy sources (RESs) integration using microgrid (MG) technology is of great importance for demand side management.
Optimization of MG provides enhanced generation from RES at minimum operation cost.
The microgrid optimization problem involves a large number of variables and constraints; therefore, it is complex in nature and various existing algorithms are unable to handle them efficiently.
This paper proposed an artificial shark optimization (ASO) method to remove the limitation of existing algorithms for solving the economical operation problem of MG.
The ASO algorithm is motivated by the sound sensing capability of sharks, which they use for hunting.
Further, the intermittent nature of renewable energy sources is managed by utilizing battery energy storage (BES).
BES has several benefits.
However, all these benefits are limited to a certain fixed area due to the stationary nature of the BES system.
The latest technologies, such as electric vehicle technologies (EVTs), provide all benefits of BES along with mobility to support the variable system demands.
Therefore, in this work, EVTs incorporated grid connected smart microgrid (SMG) system is introduced.
Additionally, a comparative study is provided, which shows that the ASO performs relatively better than the existing techniques.
American Psychological Association (APA)
Singh, Pawan& Khan, Baseem. 2017. Smart Microgrid Energy Management Using a Novel Artificial Shark Optimization. Complexity،Vol. 2017, no. 2017, pp.1-22.
https://search.emarefa.net/detail/BIM-1142628
Modern Language Association (MLA)
Singh, Pawan& Khan, Baseem. Smart Microgrid Energy Management Using a Novel Artificial Shark Optimization. Complexity No. 2017 (2017), pp.1-22.
https://search.emarefa.net/detail/BIM-1142628
American Medical Association (AMA)
Singh, Pawan& Khan, Baseem. Smart Microgrid Energy Management Using a Novel Artificial Shark Optimization. Complexity. 2017. Vol. 2017, no. 2017, pp.1-22.
https://search.emarefa.net/detail/BIM-1142628
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142628