Chapter 1 - Introduction

Abstract

Smart energy grid (SEG) infrastructures will provide efficient bidirectional energy supply with reduced greenhouse gas emissions. SEG includes distributed energy generation (DEG) capabilities, such as thermal, electricity, and gas, with smart components, which will allow scalable architecture as integrated with interconnected micro energy grids (MEGs). In order to facilitate the design and implementation of such dynamic superstructures with local and global performance optimization, it is important to provide an intelligent modeling and simulation environment with distributed decision-making capabilities to manage data gathering and analysis functions and map to static and dynamic models of SEG components. This will support the design, control, and operation of SEG in a distributed and coordinated way, along with the integrated intelligent applications and data analytics. As SEG is a multiplayer domain, this requires collaborative decision making and control with a distributed knowledge base to support different views (eg, utilities, original equipment manufacturer, hybrid electric vehicle, consumers). This will support the automatic and dynamic identification and evaluation of control and protection boundaries and operational scenarios of MEGs with renewable DEG nodes. In addition, it supports the design and operation of SEG technological architectures as integrated within practical business models related to practical implementation of different components within the SEG architecture. The proposed intelligent and distributed modeling and simulation environment will provide functionalities to support these views. To facilitate the engineering design and operation of SEGs, energy semantic network is introduced to model all layers in SEG infrastructures. The proposed solution will enable and support the practical implementation of SEGs with proven low carbon and improved efficiency and reliability of energy supply infrastructures.