A Context-Free Smart Grid Model Using Complex System Approach

A Context-Free Smart Grid Model Using Complex System Approach Soufian Ben Amor University of Versailles SQY Versailles, France Email: soufian.benamor@uvsq.fr Alain Bui University of Versailles SQY Versailles, France Email: alain.bui@uvsq.fr Guillaume Gu´erard University of Versailles SQY Versailles, France Email: guillaume.guerard@prism.uvsq.fr 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. I. INTRODUCTION Our society is electrically dependent. The electrical grid supply energy to households, businesses, and industries, but disturbances and blackouts are becoming common. With the pressure from ever increasing energy demand and climate change, finding new energy resources and enhancing energy efficiency have become priority of many nations in the 21st century. The term smart grid is coined by Amin in 2005 [2]. Smart grid is a type of electrical grid which attempts to predict and intelligently respond to the behavior and actions of all electric power users connected to it - suppliers, consumers and those that do both - in order to efficiently deliver reliable, economic, and sustainable electricity services. Then, The expression “Smart Grid” has expanded into different dimensions: some see it as a numerical solution for downstream counter and mostly residential customers, while others believe that it is a global system vision that transcends the current structure of the energy market to generate economic, environmental, and social benefits for everyone. Thus, Smart Grid is a fuzzy concept with various defi- nitions in literature. However, Smart Grid could be defined according to the main requirements of an energy network. Smart Grid should integrate information and communication technologies to generate, transport, distribute, and consume energy more efficiently. In addition, the network should have mainly the following properties: self-healing, flexibility, pre- dictability, interactivity, optimality, and safety [13]. Moreover, the Smart Grid should improve reliability, reduce peak demand, and equalize energy consumption. Research works are being conducted to attain the objec- tives, but many problems of modeling and coordination hamper advancements. However each model offers its own vision of the smart grid, putting aside theoretical and technological ad- vancement of others. Cooperation between smart technologies and existing infrastructure is often neglected in scientific and industrial studies [21]. In [6], authors argued that an electrical grid which allows the adjustments on both supply and demand will improve efficiency, reduce costs on both sides and will be beneficial for the environment. Taking into account all these internal and external features, the Smart Grid is defined as a complex system [1], [11], [13]. Contribution of our approach consists in treating the smart grid as a complex system, locating the problems at local as well as global levels, and solving them with coordinated methods. In other words, through studying and analyzing smart grid, we isolate homogeneous parts with similar behaviors or objectives, and apply classical optimization algorithms at different levels with coordination. Thanks to combining those interdependent methods, our approach guarantees the flexibility in terms of system size. Besides that, generality of our approach allows its applicability in different scenarios and models. This paper is organized as following: in the next section, the concept of complex system is introduced and theoretical approaches in their modeling are discussed. In Section 3, we present the details of our global Smart Grid model based on the complex system approach, and in section 4, we present the research of a global consensus between supply and demand. We also discuss our perspectives and first results in section 5. II. COMPLEX SYSTEM APPROACH A system which consists of large populations of connected agents, or collections of interacting elements, is said to be complex if there exists an emergent global dynamics resulting from the actions of its parts rather than being imposed by a central controller. That is a self-organizing

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