A Context-Free Smart Grid Model Using Complex System Approach
This addresses the optimization problem in smart grid design for energy and pollution management, but appears incremental as it combines existing methods.
The paper tackles the challenge of achieving global optimization in complex smart grid systems by proposing a hybrid modeling approach that combines game theoretical and classical methods at different levels, resulting in a flexible, scalable, and generalizable solution.
Energy and pollution are urging problems of the 21th century. By gradually changing the actual power grid system, smart grid may evolve into different systems by means of size, elements and strategies, but its fundamental requirements and objectives will not change such as optimizing production, transmission, and consumption. Studying the smart grid through modeling and simulation provides us with valuable results which cannot be obtained in real world due to time and cost related constraints. Moreover, due to the complexity of the smart grid, achieving global optimization is not an easy task. In this paper, we propose a complex system based approach to the smart grid modeling, accentuating on the optimization by combining game theoretical and classical methods in different levels. Thanks to this combination, the optimization can be achieved with flexibility and scalability, while keeping its generality.