A Context-Free Smart Grid Model Using Complex System Approach

TL;DR

This paper introduces a complex system approach to model smart grids, combining game theory and classical methods to enhance optimization flexibility, scalability, and generality amid the system's inherent complexity.

Contribution

It presents a novel modeling framework for smart grids that integrates game theoretical and classical optimization techniques within a complex system paradigm.

Findings

Enhanced optimization flexibility and scalability.

Effective modeling of complex smart grid dynamics.

Potential for improved global optimization strategies.

Abstract

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.