Introductory Chapter: Electric Grid Modernization - Challenges, Solutions, and Opportunities

1. Introduction

Electrical grids worldwide are experiencing major changes in terms of energy generation, transmission, delivery, and distribution in order to enhance the entire system 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.

2. Micro-grids

Distributed energy resources (DERs) and their integration into existing electric grids call for innovations in planning and operation of such resources. Micro-grids facilitate this integration and offer flexibility by providing capability to operate in different modes including grid-connected, stand-alone, and hybrid. Microgrids also improve the system reliability and efficiency by optimizing the interaction of DERs such as battery storage, EVs, renewable generation, etc. Challenges and complications associated with operation, reliability, control, and protection need to be addressed comprehensively in the design phase for the successful implementation of micro-grids throughout the electric grid [1].

3. Smart grids

Unlike traditional electric grids with unidirectional flow of power from generators to consumers, smart grids provide bidirectional flow of both power and data to offer additional benefits including DER integration, data-driven and automated functions such as self-healing actions, and self-awareness, among others.

Smart grid development involves several challenges such as outdated technology, security vulnerabilities in its computation, communication and control sub-systems, and interaction among smart grid main components including software, hardware, network, user, server, and data. In addition, high volume, high velocity, and high variety data generated by sensors, smart meters, phasor measurement units (PMUS), and automated revenue metering systems (ARMs) create big data which requires big data analytics and processing methods, and associated technologies to optimally, securely and reliably store and process such data [2].

4. Energy storage systems

Energy storage systems facilitate integration of intermittent renewable sources such as wind and solar by charging during periods of high renewable generation and discharging when renewable generation is deficient. This provides several benefits such as renewable energy arbitrage, energy, ancillary services, hedge against forecast uncertainty, etc. [3]. However, the charging/discharging of storage systems and their coordination with renewable generation must be optimized in consideration of the system operation.

EVs and their battery storage systems can also be used for renewable integration in modern electric grids [4]. However, the EVs adoption for such service is more complicated than energy storage systems due to their mobility and stochastic driving patterns. Stochastic optimization is therefore required to optimally charge and discharge EVS while providing incentives for EV drivers to participate in such services [5].