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A Modeling Method to Develop Goal-oriented Adaptive Agents in Modeling and Simulation for Smart Grids by Hyo-Cheol Lee; Hee-Soo Kim; Seok-Won Lee is a scholarly article available to read on EtoBox.

What is A Modeling Method to Develop Goal-oriented Adaptive Agents in Modeling and Simulation for Smart Grids about?

Agent-based modeling and simulation is a useful method to analyze and predict the complex and dynamic behavior of a smart grid which consists of diverse stakeholders and components such as devices, services and policies. A smart grid adaptively behaves in its dynamically changed environment and evolves over time as introducing new components and modifying (or removing) the existing components. Therefore, the model of the grid also has to be adaptive and evolutionary for users to obtain meaningful analysis. In this work, we propose a goal-oriented modeling and simulation framework to systematically model and simulate an adaptive and evolutionary smart grid. In this framework, we concentrate on the activity to design agents for the grid. This activity is based on a goal-oriented organizational agent model which goal-oriented requirement language, belief-desire-intention architecture and agent-group-role model are integrated into. This model helps modelers to design adaptive agents from their simulation requirements and to revise their models with the already developed agents like as a smart grid evolves. Further, we demonstrate the benefits of our modeling method in designing agents

Author

Hyo-Cheol Lee; Hee-Soo Kim; Seok-Won Lee

Publisher

ACM

Published

2014

Language

EN