Dynamic Vulnerability Assessment and Intelligent Control

For Sustainable Power Systems

José Luis Rueda-Torres, Francisco González-Longatt, José Luis Rueda-Torres, Francisco González-Longatt

• Publisher: Wiley-IEEE Press
• Year: 2018
• Print ISBN: 9781119214953
• eBook ISBN: 9781119214960
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks.

Key features:

• Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management.
• Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability assessment methods, supported by the underpinning mathematics.
• Develops expertise in mitigation techniques using intelligent protection and control, controlled islanding, model predictive control, multi-agent and distributed control systems
• Illustrates implementation in smart grid and self-healing applications with examples and real-world experience from the WAMPAC (Wide Area Monitoring Protection and Control) scheme.

Dynamic Vulnerability Assessment and Intelligent Control for Power Systems is a valuable reference for postgraduate students and researchers in power system stability as well as practicing engineers working in power system dynamics, control, and network operation and planning.

Chapter 1
Introduction: The Role of Wide Area Monitoring Systems in Dynamic Vulnerability Assessment

Jaime C. Cepeda¹ and José Luis Rueda-Torres²

¹Head of Research and Development and University Professor, Technical Development Department and Electrical Energy Department, Operador Nacional de Electricidad CENACE, and Escuela Politécnica Nacional EPN, Quito Ecuador

²Assistant professor of Intelligent Electrical Power Systems, Department of Electrical Sustainable Energy, Delft University of Technology, The Netherlands

1.1 Introduction

Currently, most social, political, and economic activities depend on the reliability of several energy infrastructures. This fact has established the necessity of improving the security and robustness of Electric Power Systems [1]. In addition, the lack of investment, the use of congested transmission lines, and other technical reasons, such as environmental constraints, have been pushing Bulk Power Systems dangerously close to their physical limits [2]. Under these conditions, certain sudden perturbations can cause cascading events that may lead to system blackouts [1, 3]. It is crucial to ensure that these perturbations do not affect security, so the development of protection systems that guarantee service continuity is required. In this regard, Special Protection Schemes (SPS) are designed in order to detect abnormal conditions and carry out corrective actions that mitigate possible consequences and allow an acceptable system performance [4].

However, the conditions that lead the system to a blackout are not easy to identify because the process of system collapse depends on multiple interactions [5, 6]. Vulnerability assessment (VA) is carried out by checking the system performance under the severest contingencies with the purpose of detecting the conditions that might initiate cascading failures and may provoke system collapse [7]. A vulnerable system is a system that operates with a “reduced level of security that renders it vulnerable to the cumulative effects of a series of moderate disturbances” [7]. The concept of vulnerability involves a system's security level (static and dynamic security) and the tendency of its conditions changing to a critical state [8] that is called the “Verge of Collapse State” [5]. In this context, vulnerability assessment assumes the function of detecting the necessity of performing global control actions (e.g., triggering of SPSs).

In recent years, emerging technologies such as Phasor Measurement Units (PMUs), which provide voltage and current phasor measurements with updating periods of a few milliseconds, have allowed the development of modern approaches that come closer to the target of real time vulnerability assessment [6, 7]. Most of these real time applications have been focused on identifying signals that suggest a possibly insecure steady state. This kind of VA is capable of alerting the operator to take appropriate countermeasures, with the goal of bringing the system to a more secure operating condition (i.e., preventive control) [9]. Nevertheless, the use of PMUs has great potential to allow the performance of post-contingency Dynamic Vulnerability Assessment (DVA) that could be used to trigger SPSs in order to implement corrective control actions. In this connection, a Wide Area Monitoring System (WAMS), based on synchrophasor technology, constitutes the basic infrastructure for implementing a comprehensive scheme for carrying out real time DVA and afterwards executing real time protection and control actions. This comprehensive scheme is called a Wide Area Monitoring, Protection, and Control system (WAMPAC) [10]. This chapter presents a general overview of concepts related to power system vulnerability assessment and phasor measurement technology and subsequently highlights the fundamental relationship between these in modern control centers.

1.2 Power System Vulnerability

A vulnerable system is a system that operates with a “reduced level of security that renders it vulnerable to the cumulative effects of a series of moderate disturbances.” Vulnerability is a measure of system weakness regarding the occurrence of cascading events [7].

The concept of vulnerability involves a system's security level (i.e., static and dynamic security) and its tendency to change its conditions to a critical state [8] that is called the “Verge of Collapse State” [5].

A vulnerable area is a specific section of the system where vulnerability begins to develop. The occurrence of an abnormal contingency in vulnerable areas and a highly stressed operating condition define a system in the verge of collapse state [5].

In this chapter, vulnerability is defined as “the risk level presented by a power system during a specific static or dynamic operating condition regarding the occurrence of cascading events.” This concept makes vulnerability an essential indicator of system collapse proximity.

Although there are a lot of vulnerability causes, which vary from natural disasters to human failures, system vulnerability is characterized by four different symptoms of system stress: angle instability, voltage instability, frequency instability, and overloads [5]. So, vulnerability assessment should be performed through analyzing the system status as regards these symptoms of system stress.

1.2.1 Vulnerability Assessment

Vulnerability assessment has the objective of preventing the occurrence of collapses due to catastrophic perturbations [11]. Performing VA requires specific mathematical models capable of analyzing the multiple interactions taking place between the different power system components [11]. These models have to consider the varied phenomena involved in the vulnerability condition and also the diverse timeframes in which the corresponding phenomena occur.

Many methods have been proposed for vulnerability assessment, which have been classified based on various criteria [6, 7]. However, in terms of their potential implementation in control centers, the techniques to assess vulnerability can be classified into off-line, on-line, and real time methods. Figure 1.1 depicts the proposed classification of vulnerability assessment methods.

Figure 1.1 Power system vulnerability assessment methods.

• Off-line assessment: Off-line assessment is done using conventional methods that are based on different complex model simulations; these usually involve time-consuming tasks, which restricts on-line applications. The high complexity is provoked by the huge number and diversity of the components that constitute an electric power system and their particular performance during dynamic phenomena. Among t...

Table of contents

• Cover
• Title Page
• Copyright
• Table of Contents
• List of Contributors
• Foreword
• Preface
• Chapter 1: Introduction: The Role of Wide Area Monitoring Systems in Dynamic Vulnerability Assessment
• Chapter 2: Steady-State Security
• Chapter 3: Probabilistic Indicators for the Assessment of Reliability and Security of Future Power Systems
• Chapter 4: An Enhanced WAMS-based Power System Oscillation Analysis Approach
• Chapter 5: Pattern Recognition-Based Approach for Dynamic Vulnerability Status Prediction
• Chapter 6: Performance Indicator-Based Real-Time Vulnerability Assessment
• Chapter 7: Challenges Ahead Risk-Based AC Optimal Power Flow Under Uncertainty for Smart Sustainable Power Systems
• Chapter 8: Modeling Preventive and Corrective Actions Using Linear Formulation
• Chapter 9: Model-based Predictive Control for Damping Electromechanical Oscillations in Power Systems
• Chapter 10: Voltage Stability Enhancement by Computational Intelligence Methods
• Chapter 11: Smart Control of Offshore HVDC Grids
• Chapter 12: Model Based Voltage/Reactive Control in Sustainable Distribution Systems
• Chapter 13: Multi-Agent based Approach for Intelligent Control of Reactive Power Injection in Transmission Systems
• Chapter 14: Operation of Distribution Systems Within Secure Limits Using Real-Time Model Predictive Control
• Chapter 15: Local Control of Distribution Networks
• Chapter 16: Electric Power Network Splitting Considering Frequency Dynamics and Transmission Overloading Constraints
• Chapter 17: High-Speed Transmission Line Protection Based on Empirical Orthogonal Functions
• Chapter 18: Implementation of a Real Phasor Based Vulnerability Assessment and Control Scheme: The Ecuadorian WAMPAC System
• Index
• End User License Agreement