Applications of Non-Markovian Hybrid Petri-Nets in Power Engineering


This paper is focused on simulation and graphical stochastic modeling of electrical power systems. The main goal of this paper is to develop a tool for modeling and simulation of very large systems with probabilistic incidents. For this purpose, a new extension of Petri nets is introduced in this paper. Using this extension which is suitable for power engineering applications, a large system with stochastic transitions can be studied and analyzed. After a preliminary introduction of Petri nets, the proposed extension is introduced. In order to clarify the modeling process, a case study regarding modeling and analyzing long-term behavior of a Plug-in Hybrid Electric Vehicle (PHEV) is studied and simulated. The simulation results demonstrate the long-term stochastic dynamics of a charging station without any requirement for rigorous analytical studies of the overall stochastic process.

Meeting Name

40th Annual Conference of the IEEE Industrial Electronics Society (IECON) (2014: Oct. 29-Nov. 1, Dallas, TX)


Electrical and Computer Engineering

Keywords and Phrases

Electric Power Systems; Hybrid Vehicles; Industrial Electronics; Intelligent Systems; Monte Carlo Methods; Petri Nets; Random Processes; Reliability; Stochastic Systems; Charging Station; Electrical Power System; Long-Term Behavior; Model and Simulation; Plug in Hybrid Electric Vehicles; Stochastic Dynamics; Stochastic Transitions; Very Large Systems; Plug-In Hybrid Vehicles; Monte-Carlo Simulation

International Standard Book Number (ISBN)


International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version


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© 2014 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Oct 2014