DocumentCode :
174559
Title :
A biological approach for energy management in smart grids and hybrid energy storage systems
Author :
Delgado-Gomes, Vasco ; Borza, Paul Nicolae
Author_Institution :
Fac. of Electr. Eng. & Comput., Transilvania Univ. of Brasov, Brasov, Romania
fYear :
2014
fDate :
22-24 May 2014
Firstpage :
1082
Lastpage :
1086
Abstract :
The concept of smart grid has evolved during the last years. Smart grid is now a collection of power devices, Distributed Energy Sources (DES), Renewable Energy Sources (RES), and monitoring devices using Information and Communication Technology (ICT) to interact between them. A proper power network management needs to be resilient, reliable, and redundant to prevent malfunctions in the power network operation. This paper presents a biological approach to manage smart grids using characteristics such as self healing, different types of control strategies (feedback, feed forward), learning algorithms, different types of energetic storage, and a hierarchical architecture. These characteristics are present in living beings and are important in the smart grid management. An analogy between biological systems and technological systems is made and the similarities between these two systems are presented. A particular case of biological approach applicability in a Hybrid Energy Storage System (HESS) is presented to demonstrate how this approach can be scaled from a single energy cell to an entire power network.
Keywords :
control engineering computing; energy management systems; energy storage; hybrid power systems; power engineering computing; power system control; power system management; smart power grids; HESS; biological systems; control strategies; distributed energy sources; energy management; hierarchical architecture; hybrid energy storage systems; information-and-communication technology; learning algorithms; monitoring devices; power devices; power network management; power network operation; renewable energy sources; smart grid management; technological systems; Biological systems; Energy storage; Power system stability; Reliability; Smart grids; Standards;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Optimization of Electrical and Electronic Equipment (OPTIM), 2014 International Conference on
Conference_Location :
Bran
Type :
conf
DOI :
10.1109/OPTIM.2014.6851039
Filename :
6851039
Link To Document :
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