Waseem Akram1,
Muaz A. Niazi1,
Laszlo Barna Iantovics2 and
Athanasios V. Vassilakos3

1COMSATS University Islamabad, Computer Science Department
  Islamabad, Pakistan
2Petru Maior University of Tirgu Mures, Informatics Department
  Tirgu Mures, Romania
3Lulea University of Technology, Computer Science Department
  Lulea, Sweden
INDECS 17(3-B), 546-585, 2019
DOI 10.7906/indecs.17.3.14
Full text available here.

Received: 11th June 2019.
Accepted: 25th November 2019.
Regular article


A smart grid can be considered as a complex network where each node represents a generation unit or a consumer, whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling paradigm. The agent-based modeling is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the agent-based modeling paradigm. However, to the best of our knowledge, none of these studies have focused on the specification aspect of the model. The model specification is important not only for understanding but also for replication of the model. To fill this gap, this study focuses on specification methods for smart grid modeling. We adopt two specification methods named as Overview, design concept, and details and Descriptive agent-based modeling. By using specification methods, we provide tutorials and guidelines for model developing of smart grid starting from conceptual modeling to validated agent-based model through simulation. The specification study is exemplified through a case study from the smart grid domain. In the case study, we consider a large set of network, in which different consumers and power generation units are connected with each other through different configuration. In such a network, communication takes place between consumers and generating units for energy transmission and data routing. We demonstrate how to effectively model a complex system such as a smart grid using specification methods. We analyze these two specification approaches qualitatively as well as quantitatively. Extensive experiments demonstrate that Descriptive agent-based modeling is a more useful approach as compared with Overview, design concept, and details method for modeling as well as for replication of models for the smart grid.

agent-based modeling, cognitive agent-based computing, complex networks, smart grid


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