Complex computer systems and electric power grids share many properties of how they behave and how they are structured. A microgrid is a smaller electric grid that contains several homes, energy storage units, and distributed generators. The main idea behind microgrids is the ability to work even if the main grid is not supplying power. That is, the energy storage unit and distributed generation will supply power in that case, and if there is excess in power production from renewable energy sources, it will go to the energy storage unit. Therefore, the electric grid becomes decentralized in terms of control and production. To deal with this change, one needs to interpret the electrical grid as a system of systems (SoS) and build new models that capture the dynamic behavior of the microgrid. In this paper, different models of electric components in a microgrid are presented. These models use complex system modeling techniques such as agent-based methods and system dynamics, or a combination of different methods to represent various electric elements. Examples show the simulation of the solar microgrid is presented to show the emergent properties of the interconnected system. Results and waveforms are discussed.

Meeting Name

Complex Adaptive Systems Conference: Engineering Cyber Physical Systems (2017: Oct. 30-Nov. 1, Chicago, IL)


Electrical and Computer Engineering

Second Department

Engineering Management and Systems Engineering

Research Center/Lab(s)

Intelligent Systems Center

Keywords and Phrases

Adaptive Systems; Complex Networks; Distributed Power Generation; Embedded Systems; Energy Storage; Large Scale Systems; Models; Neural Networks; Renewable Energy Resources; Systems Engineering; Wind; Intelligence; Micro Grid; Simulation; Solar; SoSs; Electric Power Transmission Networks; Microgrid; Modeling

International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2017 Elsevier, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publication Date

01 Nov 2017