Power Systems Resilience

Electric power distribution networks are constructed and expanded among wide geographical areas. Traditionally the focus of distribution networks planning is mainly on network reliability improvement with minimum cost considering the technical constraints. The aim of such vision is based-on the fact that distribution network outages occurred on the network component because of conventional faults with high frequency and low impact characteristics. Nowadays the power distribution networks encounter with unwanted weather conditions and natural disasters facing the network with high impact low probability events on distribution network that can be damage the network components widely and permanently. It can cause costumer interruption and loss of load with high financial cost. The aim of this chapter is the optimal planning of conventional electric distribution network based-on distribution network resiliency enhancement. In this work the optimal size and site of network component and its topology is determined using optimization algorithm. A resilient-based fitness function is proposed to meet the resilient network requirement. To model the effect of the natural disasters on resilient based distribution network planning, the geographical data for hurricane as a natural disaster is combined to create a spatial risk index map. In this work a new methodology is proposed to establish a rational relation between network component fragility curves, component geographical location and hurricane spatial risk index. The proposed method is tested on a real large scale distribution network.

This chapter presents the role of power system connectivity and resiliency under the conditions of vulnerability to natural disasters and deliberate attacks. The importance of introducing the Internet of Things (IoT) concept in developing smart grids will be shown, as well as the methods of increasing the power system resiliency. Case studies from the Romanian power system will be included. At the same time, the authors underline the necessity of introducing standards and developing the protection systems of Big Data in order to design the future smart power system.

The flexibility of the power system can be described with its ability on providing dynamic and adaptable structure against the various circumstances. It requires balancing the power supply and demand in terms of intervals such as minute or hourly. The flexibility of power system, which is a critical driver, is the fast and assorted deployment of distributed sources such as hydro, wind, solar etc. The early challenges of the flexibility researches are focused on rapid deployment of distributed generation while the followings are related to pricing, standards, policies, and microgrid (MG) integration to power system that includes customer adoption. The environmental policies, subsidies and similar factors may constrain the power system management in terms of generation. Therefore, the power system characteristic changes to distributed generation searches instead of conventional generation. It may also shift consumers to energy generators by using their micro sources as solar plants, hybrid electric vehicles and smart appliances. The alteration to more flexible power system involves novel technologies and methods to sustain the security of the network. On the other hand, the resiliency of a power system requires the ability to increase the security of power system against extreme conditions. The main interest on resiliency is caused by significant weather conditions such as hurricanes, earthquakes and floods. Such weather events are defined as high impact and low frequency events. Moreover, increased communication and monitoring infrastructures have raised the cyber security concerns in the aspects of resiliency. Therefore, the resiliency of power systems requires to be handled in terms of physical and cyber damages. The resiliency is researched in three main topics as damage prevention, system recovery, and survivability of power system. These topics are studied in generation, transmission, distribution and consumer sections with its all drivers.

The purpose of this chapter is to explain the metrics were used for quantifying the resiliency of power system. Also, will determine how which metrics are calculated for which system under what conditions. Distribution and transmission infrastructure that is expanded over a wide geographic area, is always affected by weather-related disasters which occur continuously. Therefore, a safe and reliable operation is essential to have a resilient power system, which survives in hard conditions. The metrics investigated in this chapter are quantitative, which are defined based on the topology, hardware, and the efficiency of the system, reliability indices, and also the type and severity of the threat. The accurate assessment of each of these metrics can help to properly understand the concept of resilience in power systems. Also, we can obtain an appropriate assessment of the power network resilience by selecting the proper set of these metrics according to the type of threat and our goal.

Currently the number of Microgrids (MGs) is continuously increased in distribution network. In this view, the future advanced distribution network can be regarded as clusters of MGs. Hence the MGs is the building blocks of smart distribution networks. There are many technical, economic and social reason for MGs implementation. One of the main advantages of MGs is the ability to encounter with abnormal conditions in the network such as occurrence of natural disasters with island operation capability. Based on the above discussion, the problem of optimal planning of distribution network based-on MGs is an interesting topic. In this chapter the optimal MG-based smart distribution grid planning problem is formulated and tested on a planning area. While the natural disasters are low probability and high impact phenomena, there are not enough historical data to extract an accurate component failure model. In this chapter the initial geographical area of MGs is supposed as input data in a large scale Greenfield study area and based on the resiliency constraints and index, the optimal configuration of total distribution network including MGs is determined. The distribution network configuration is planned such that all MGs meet the predefined requirement based on definition and supply the predefined critical loads within each MGs. In this work the optimal size and site of network elements and its configuration is determined by a multi-objective optimization algorithm. The effect of the natural disasters on resilient MG-based distribution network planning, the geographical data for disasters is modelled to give a geographical map that joins the spatial risk index with distribution network component location. The main goal of this work is to propose a framework for optimal MG-based resilient distribution networks.

By increasing the penetration of distributed energy resources (DERs) and developing the microgrids (MGs) due to its implication for the existing circumstance of power system, Networked-Microgrid (NMG) approach is becoming an important issue in smart distribution grids. On the other hand, low probability but extreme events like natural disasters or the fuel interruption can threaten the grid security. For this end resiliency problem is discussed in this paper for the MMG structure of distribution network. The main objective of this chapter is to globally reach the minimum cost operation of microgrids in normal condition while meeting the adequacy in resiliency operation mode. The dispatchable unit status, energy storage and adjustable loads scheduling and the energy trade status between microgrids in each hour are evaluated with stochastic modeling of load and renewable power generations. It is of important because these microgrids have energy exchange between each other under control of energy management system (EMS) in addition of energy drawing from main grid. This can prepare an option to count on DER capacity of other microgrids in resiliency mode of system operation when the main grid is disconnected.

Economic issues of power systems are formulated as optimization problems to enhance reliable operation and safe security of the real-time and hierarchical systems including complex control structures. The optimization problems have been formulated as combination of objective functions and constraints which Optimal Power Flow (OPF) must be increased to combine security constraints. The OPF problem is basically a network analysis challenge and the main objective of this challenge is to plan and to predict the undesirable situations that may arise by adding various assumptions to the account. This challenge can be solved using well-known numerical approaches, however these include derivatives and the solution of them is relatively difficult. However, the Evolutionary Computation (EC) based optimization algorithms provide more easy solutions for the OPF. In this chapter, the algorithms that contain the heuristic methods used on EC based algorithms and their applications on OPF are described.

This chapter presents an approach for Resilient Distribution System Expansion Planning (RDSEP) considering gas-fired Non-utility DGs (NUDGs) and Demand Side Providers (DRPs). The RDSEP method explores the NUDGs and DRPs impacts on the planning paradigm. The RDSEP problem is decomposed into multi sub-problems that optimize investment, operational and reliability costs. The RDSEP is a complicated problem, and the resilience criteria may encounter different planning schemes that can also be included in the problem modeling. The resilience of a distribution system is the capacity to tolerate the external shocks that may be imposed on the network, and the distribution system must be able to deliver electricity continuously to its consumers. The distribution system may have NUDGs and DRPs that interchange electricity with Distribution System Operator (DSO) and they can dynamically change the distribution system resources. The NUDG and DRP contribution scenarios can significantly change the state space of RDSEP, and they can be utilized for different preventive/corrective measures against internal and external shocks. The RDSEP model is a non-linear programming problem, and a heuristic optimization method is utilized. A nine-bus test system and an urban electric system are used to assess the introduced method.

Modern embedded systems control sensitive data and information depending where these systems are installed to accomplish required tasks. Due to this aspect, cyber criminals or hackers are motivated and determined to rob intellectual property of these systems through more and more sophisticated attacks. A huge problem in defending against these massive and various types of attacks is that in the last years attacks increased their complexity while the knowledge of an attacker decreased significantly because of the tools and devices they can find in the online world and free market. The most important challenges to defend against an attack are represented by these factors: speed of the attack, complexity of the attack and the simplicity of the tools that attackers used. A very often question that most of designers and developers of embedded systems ask is: Why cyber criminals commit attacks and what motivates them? Is it money? Is it celebrity? The answer starts with simple entertainment and extends to material benefits and finding, very often, valuable sensitive information that can cause serious damages to a system and its dependencies or even terrorism acts. Best case scenario is when the attacker is exactly the owner/the developer of the system or when he is demanding various attacks in order to figure out how defense mechanisms resist when facing attacks, how these can be improved and what are the challenges in building new ones. Therefore, this chapter is focused on two main ideas considering modern embedded systems based on Field Programmable Gate Array (FPGA) technology such as communication networks or cryptographic systems. The first idea refers to malicious and deliberate attacks performed against embedded systems starting with risks, threats and vulnerabilities that motivated hackers find and exploit and the second idea is about power system resilience and how attacked systems respond and decide what to do next. This chapter is organized in six parts as follows. The first part of this chapter is an introduction about attacks on embedded systems and a background that provides all the necessary information of how attackers and attacks evolved in the last years. The second part is focused on who performs these attacks and how systems are attacked. The third part refers to the main attacks on embedded systems and how these are classified depending on different criteria such as interlinking features, integration level or programmability level. The fourth part of this chapter is about power system resilience and how actual systems react or how they should react in case of malicious attacks. The fifth part refers, with examples, to the vulnerabilities existing in modern equipment that surrounds us and how these are or can be attacked such as mobile and communication systems and social apps that we use every day. The last part concludes the chapter and draws some goals for future research directions. The main purposes of this chapter are: to review and categorize all types of attacks against embedded systems based on FPGA, to show how attacks evolved from their beginnings until present, to bring to light who are the attackers as well as what motivates these hackers and to picture how “resiliency” feature should operate or operates during life-cycle of embedded systems when someone wants to perform an attack or succeeds one. Another important goal that this chapter aims for is to find and show others vulnerabilities existing in modern systems, especially communications, that most of us can not live without them.

This chapter presents a theoretical analysis of the impact of the extreme weather events and deliberate attacks on the power systems, which is accompanied by several examples taken from existing reports. The power systems resiliency for these cases are presented and the used practices are being assessed. Optimized models to improve the power system reaction time to these new risks are also discussed and proposed.

Cyber-Physical Systems (CPS) represent a complex class of systems that are implied in electric power generation and delivery, as well as in critical infrastructure operations, traffic flow management or healthcare services. CPS consist of a robust combination of computational and physical components, that implement modern technologies such as wireless sensor networks (WSN), Internet of Things and recently Internet of Everything, machine to machine (M2M) communication, smart devices and even smart everything. Cyber-Physical Systems integrate heterogeneous equipment with computing power, which represent an attractive target for various attackers. Successful attacks can lead not only to data breaches, but also to interruption of CPS functioning, hence reducing their availability. CPS are affected also by technical failures and accidents. In order to enhance the CPS resilience, the proposed methods should mitigate the security risks by implementing powerful and robust security measures, in the same time increasing the fault tolerance and redundancy of the system. In this chapter, the authors analyze the state of the art methods for enhancing resilience of Cyber-Physical Systems. In the first section of the chapter the authors review the threats and vulnerabilities that can affect systems functioning. In the second part of the chapter the existing methods for resilience enhancement (redundancy, fault tolerance, security) are presented based on an extensive literature study.

Computer facilities and microprocessor-based technology have been successfully used in the energy industry. For protection and equipment control, this technology has been used in SCADA, remote control and monitoring applications. Particular attention is paid to the cyber security sector for automation and control systems. Protective application of the equipment and control, SCADA, monitoring and remote control, uses the technology with microprocessor. Due to the great importance of the power supply process, there is no question of being left in a state of vulnerability and neglect. Security is not perfect and will never be. For this reason, there will always be security breaches and incidents. Also, for this reason, not only protection mechanisms are in place, but also mechanisms for rapid detection of incidents and which are able to react effectively to the isolation of problems and to ensuring security. Processes security for systems will continue to evolve in the future. By definition, there are no communication systems that are 100% safe. Attacks against critical industrial infrastructures marked an increase not only in terms of number but also of the level of complexity. The destruction of the industrial control system (ICS) and critical processes were interrupted. For many organizations, the security improvement in ICS systems is great. The extreme sensitivity to ensure the availability and performance of industrial processes has led to a more conservative and rigorous approach to how security measures are implemented. Cyber-attacks that could compromise the availability, integrity, and confidentiality of ICS systems may come from within systems or from outside ICS systems. Among the ICS system infection vectors from the perspective of the SANS Institute (2014) include: external threats (state attacks, hacking etc.), malware, exploiting tools, phishing, internal attacks, cyber security protocols, and industrial espionage. This chapter addresses the cyber security issues required for the protection, automation, control and communications systems of transformation stations as well as methods that could be used to prevent computer attacks that can have a significant impact on the availability of the system Electro-energetic effect with serious consequences on extended area interruptions.

The chapter consists of five parts as follows:

The power quality in supplying the consumers is very important taking into consideration the plants’ diversity. In fact, the quality of electricity includes two components: The Performance Standard imposes the quality of the distributed power in distribution service and establishes performance indicators in the provision of the distribution service, “the quality of distribution service is measured with respect to the supply continuity to the end users”. The Performance Standard sets out the performance indicators for: The chapter aims to present an analysis of one of the components of the electricity quality, the continuity in the electricity supply of the consumers, indicating possibilities for improvement of the electricity. The indicated improvement is related to the installation of remote-controlled equipment for the rapid isolation of defects in the medium voltage network, correlated with the identification of the mounting location, which brings maximum benefits in terms of reducing the continuity indicators, especially: Beside the definitions of the continuity indicators, it also presents the formulas based on which they are calculated as required by the regulations in force, ways of continuously decreasing them, how to predict the targets of these indicators, both for planned interruptions and for unplanned interruptions. A case study is presented as a “self-healing” automation to isolate faults on a medium voltage line through reclosers and a General Packet Radio Service (GPRS) as a packet oriented mobile data service on the 2G/3G/4G cellular communication system’s global system for mobile communications (GSM), communication using a protocol specific to data transfer.

The contents of the chapter will be structured as follows: