Preface

Electrical grids worldwide are experiencing major changes in terms of energy generation, transmission, delivery, and distribution in order to enhance the entire system's control, reliability, efficiency, and safety. Advanced energy systems and technologies such as renewable sources of energy, energy storage systems, and electric vehicles (EVs) as well as equipment such as sensors, smart meters, and communication devices along with innovations in computing technologies, machine learning, and data analytics are used to modernize the electric grid and the way it is planned, operated, and managed.

This book provides an overview of several aspects of grid modernization including micro-grids, smart grids, energy storage, and communication systems.

The book is organized into six chapters.

Chapter 1 is the introductory chapter that highlights the editor's perspectives on the most important features of electric grid modernization. The chapter includes three main sections regarding micro-grids, smart grids, and energy storage systems and their associated challenges that need to be addressed within the context of grid modernization.

Chapter 2 presents recent trends and applications of smart grids. A comprehensive grid modernization technique is proposed that incorporates the following characteristics:


In addition, an integrated mechanism is introduced to resolve grid modernization complications. Future perspectives of grid modernization are also discussed in this chapter.

Chapter 3 presents a Smart Grid Architecture Model (SGAM) for grid modernization planning. It also discusses the integration of a pilot project into the SGAM reference model. The integration is achieved by identifying key performance indicators that generate the most value and impact for the pilot project in the context of smart grids.

Multi-criteria analysis (MCA) in combination with cost-benefit analysis (CBA) is used to facilitate the decision-making and evaluation of smart grid projects. In addition, a case study is presented for distribution grid planning for rural smart grids. The application of the SGAM reference model and combined MCA–CBA for the case study is demonstrated to increase local economic development and reduce CO2 emission among other values.

Chapter 4 introduces advanced communication and control methods for smart grids. Intelligent electronic devices (IEDs) and their performances are tested and compared from the reliability perspective. This chapter explains IEC 61850 standard for communication systems and its extension to IEC 61850-7-420, which facilitates communication among various distributed energy resources (DERs) in micro-grids. A lightweight IED is developed and implemented on a microcontroller as well as on an FPGA. The performance is evaluated through Hardware-in-the-Loop (HIL) testing in terms of communication latency, processing time, and control action. The chapter concludes that FPGA performs better than other microcontrollers and, as such, is better suited as a micro-grid controller.

Chapter 5 reviews different energy storage technologies including pumped hydro, supercapacitors, flywheel, thermal, and battery storage systems, and their role in renewable integration. Applications of energy storage systems for energy and capacity, ancillary services, transmission and distribution services as well as end-use applications such as power quality, demand charge management, time-of-use, and real-time pricing are also discussed. In addition, challenges and opportunities of storage systems applications for renewable integration are presented.

Chapter 6 evaluates the capabilities of the emerging 5G cellular technologies and their integration with a xIoT application such as a smart grid to develop a xIoT-ICT infrastructure. Challenges of communication among various smart grid components are presented, which include grid communications network possession, associated standards, and interoperability. Two 5G-based business and architectural models are proposed for a converged power grid–ICT infrastructure to enable seamless end-to-end interoperability among various communication devices within the smart grid. The proposed models are concluded to facilitate the integration of DERs and enhance grid resiliency.

> **Mahmoud Ghofrani** School of Science, Technology, Engineering and Mathematics (STEM), University of Washington Bothell, Bothell, USA
