This chapter initially explains how dependencies are established when at least a part of an infrastructure system requires the provision of the service to function. Although the focus is on functional dependencies, this chapter also explores physical and conditional dependencies. Resilience metrics presented in previous chapters are broadened in order to represent the effect of dependencies on resilience levels. Dependencies established within an infrastructure system are also explained. The concept of buffer as a local storage of the resources related to the depending service is defined as part of these expanded metrics, and then it is exemplified by examining a practical application of such buffers: power plants for information and communication network (ICN) sites. After introducing the main concepts and ideas related to dependencies, this chapter takes a broader view by discussing interdependencies when those are established both directly and indirectly. The study of interdependencies for electric power grids and ICN also explores the relationship with other infrastructures, such as transportation networks and water distribution systems, and with community social systems.

The increased interest that the topic of critical infrastructure resilience is attracting in academia, government, commerce, services, and industry is creating an alternative engineering field that could be called resilience engineering. However, the views of the meaning of resilience have varied, and even in some very relevant world languages, an exact translation of the word “resilience” has only recently been introduced – for example, the word “resiliencia” was added to the dictionary of the Royal Academy of Spanish Language in 2014 – or it still does not exist, as happens in Japanese. Thus, this chapter introduces the main concepts associated with the study of resilience engineering applicable to critical infrastructure systems with a focus on electric power grids and information and communication networks (ICNs) because these are the infrastructures that are identified as “uniquely critical” in US Presidential Policy Directive 21, which is the source for the definition of resilience that is used in this book.

Although today’s power grids have their own sensing and control communications infrastructure in dedicated networks operating separate from the publicly used information and communication networks (ICNs), technological advances may lead to more integrated electric power and ICN infrastructures. Some of the motivating technological changes that may act as catalysts for such increased integration of both infrastructures include the need for much higher power supply resilience for ICN sites, development of an “Internet of Things,” and the increased communication needs for electric power devices at users’ homes or at the power distribution level of the grid as part of power systems’ evolution into “smarter” grids. Hence, this chapter explores the implications in terms of resilience of integrated electric power and ICN infrastructures. In particular, the use of integrated power management to facilitate the use of renewable energy sources is discussed. Fundamental concepts about cybersecurity are also presented.

As was introduced in Chapter 1, adaptation is a fundamental attribute of resilient systems. Adaptation could occur by identifying changes in the physical and social environment with the potential to affect a community system operation or by reacting after a disruptive event happens. Part of a positive reaction in the latter of these adaptation mechanisms involves learning about which factors contributed to improving resilience and which factors caused a lower resilience. This chapter focuses on an important tool that is part of such a learning process for improved resilience: disaster forensics. Disaster forensics are based on a postdisaster investigation, in which field investigations and postevent data collection are important components. Hence, the first part of this chapter will focus on explaining the steps and procedures involved with a disaster forensic investigation, including a description of how to perform field investigations. This chapter then describes power grids’ and information and communication networks’ performance in recent natural disasters based on lessons obtained during past forensic investigations.

This chapter is dedicated to examining technologies and strategies for improved resilience of information and communications networks. Initially, this chapter describes typical service requirements for information and communications networks by discussing services provision expectations. These expectations are presented in context by describing typical regulatory environments observed in the United States and other countries, placing special attention on emergency 911 regulations. The second part of this chapter provides an overview of most commonly observed strategies and technologies used to improve resilience. These strategies and technologies include resources management approaches, as well as hardware- and software-based technologies.

This chapter provides an overview of the main infrastructure systems that are the focus of this book as well as describing fundamental concepts and information about network theory, reliability and availability, and disruptive events that are also applicable to the rest of this book.

This chapter is divided into two main parts. The first part presents various resilience modeling approaches for critical infrastructures, with a focus on power grids and communication networks. However, as is explained, a main modeling framework relying on graph theory is applicable to most other critical infrastructure systems. The second part discusses various resilience metric approaches, with special attention to those applied to power grids. Metrics for concepts related to resilience that have also been used in the literature are also discussed in this chapter. Discussion of both resilience modeling and metrics is expanded in later chapters, particularly in Chapter 4, where dependencies and interdependencies are taken into consideration.

This chapter explains problems associated with planning infrastructure systems in order to improve resilience. Understanding the concept and basic methods for planning infrastructure investments is an important aspect for studying resilience because planning is a key process that contributes to resilience preparedness and adaptation attributes. Initially, the chapter discusses the fundamental problems and issues found when making decisions about investment allocations amid uncertain conditions. Then, probabilistic risk assessment (PRA) as still the main tool used in industry in planning processes is explained. Because characterizing intensity and other relevant attributes of disruptive events is an important component of planning processes for enhancing resilience, this chapter continues by exploring how these events – and especially hurricanes – can be characterized in order to obtain information that can be used as input for the planning process. Finally, the chapter concludes by discussing economic concepts and tools related to infrastructure resilience enhancement planning processes.

This chapter is dedicated to examining strategies and technologies for improving power grids’ resilience. The first part of this chapter focuses on traditional power grids by presenting technologies and management approaches for improved resilience at the power generation, transmission, and distribution levels and by discussing strategies for enhanced withstanding capability or reduced restoration speed. The second part of this chapter explores the effect that the evolution of power grids into “smart” grids may likely have in the future. Advanced technologies that have already been implemented at all levels of power grids are discussed. Alternative power distribution approaches implemented at the load level, such as microgrids, able to significantly improve resilience with respect to traditional power grids, are also described in this chapter.

Introduction

This chapter discusses key concepts and evaluation metrics used to describe and quantify the value proposition of a local area power and energy system (LAPES). Often the engineer is asked to evaluate multiple options and create a justification for a recommendation. Concepts of techno-economic analysis explored in this chapter are useful to compare the LAPES to a traditional system as well as to explore the cost-benefit tradeoff of various LAPES designs, configurations, and operating modes. Higher power quality, energy availability, and reliability of small-scale and distributed power systems are often touted as significant advantages over a conventional utility electrical system. While LAPES may indeed offer technological advantages, in order for it to be a practical engineering solution a comprehensive economic valuation of these benefits must occur in order to build the business case for a LAPES system. That is, higher availability and reliability may come at a cost that is unaffordable for a given application. Thus, this chapter explores tools and techniques to perform a techno-economic analysis that considers both the technological merits and the economic costs.

A LAPES is expected to provide decades of service with comparable or better availability than a commercial, large-scale, wide-area electrical utility. The downside of a decentralized, distributed system is that propagating intelligence and control to the edge of the grid tends to increase the number of components required and creates new failure modes. Consider a solid-state transformer (SST) compared to a traditional line-frequency transformer (LFT). Certainly the SST can perform more functions than the LFT, including real and reactive power control and volt-var control, harmonic current compensation, among others. Juxtapose this enhanced feature set against the fact that the LFT routinely provides decades of service life with minimal if any operation and maintenance costs (O&M) and that the purchase price of the SST far exceeds the price of the LFT. Techno-economic analysis provides a data-driven, fact-based way to evaluate the cost-benefit of these competing engineering solutions. Further, consider that the SST is comprised of a large plurality of individual electrical components, each with associated failure and wear-out modes.