Evaluation of Power Systems Resilience to Extreme Weather Events: A Review of Methods and Assumptions (original) (raw)
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Multi-phase assessment and adaptation of power systems resilience to natural hazards
Electric Power Systems Research, 2016
Extreme weather hazards, as high-impact low-probability events, have catastrophic consequences on critical infrastructures. As a direct impact of climate change, the frequency and severity of some of these events is expected to increase in the future, which highlights the necessity of evaluating their impact and investigating how can systems withstand a major disruption with limited degradation and recover rapidly. This paper first presents a multi-phase resilience assessment framework that can be used to analyze any natural threat that may have a severe single, multiple and/or continuous impact on critical infrastructures, such as electric power systems. Namely, these phases are (i) threat characterization, (ii) vulnerability assessment of the system's components, (iii) system's reaction and (iv) system's restoration. Second, multi-phase adaptation cases, i.e. making the system more robust, redundant and responsive are explained to discuss different strategies to enhance the resilience of the electricity network. To illustrate the above, this time-dependent framework is applied to assess the impact of potential future windstorms and floods on a reduced version of the Great Britain's power network. Finally, the adaptation cases are evaluated to conclude in what situations a stronger, bigger or smarter grid is preferred against the uncertain future.
IEEE Access
The electric power system plays an integral part in the well-being of the modern society. Because of climate change, the ageing power system infrastructure is under threat due to the ever-increasing intensity and frequency of high-impact, low-probability (HILP) events. Although, in most cases, these events are area-specific, the impact of such events, if unaddressed, can lead to cascading failures. Therefore, it is vital for the grid of tomorrow to not only be reliable but also be resilient in view of the broad inter-dependencies. Despite being a widely researched topic, the applicability of the concept of resilience, especially in power systems terms, is not a straightforward task due to the lack of consensus on a consistent definition, or a set of robust metrics. This paper starts with an analysis of different definitions, frameworks, and metrics related to resilience proposed by multiple researchers and research organizations which is then followed by determination of the damage cost and risk associated with an extreme event which is pivotal in resilience enhancement decisions. We then present two case studies: 1) for determining the customer damage cost that underpins the increase in customer cost as a result of major event, 2) for estimating the risk index of the network that helps support resilience-oriented decision making. We also summarize some of the guidelines and standard practices followed by electric utility companies concerning extreme weather events in terms of preparedness and recovery actions, resilience improvement plans, etc. Moreover, to ascertain the improvement in the grid resilience indices, as a result of resilience enhancement application, a case study (Case Study 3) that evaluates three resilience improvement techniques is presented. INDEX TERMS High-impact, low-probability (HILP) events, power system reliability and resilience, customer damage cost, risk index, electric utility response.
IEEE Access
Over the years, power systems have been severely affected by extreme events. This situation has worsened given that climate change has proven to exacerbate their frequency and magnitude. In this context, resilience assessments have proved crucial to prevent and tackle the effects of these events on power systems. Some resilience studies have taken advantage of the so-called fragility curves (FCs) to evaluate the vulnerability of the system components against these natural hazards. Conceptually, FCs provide the failure probability of a particular grid asset according to the intensity of an extreme event, which can be determined based on the hazard intensity inherently dictated by the nature of the event. The probability of failure can be obtained following diverse methodologies and criteria. Thus, the resilience assessment of the event may vary significantly depending on how the probability of failure was determined. This paper provides, for the first time, a comprehensive review of the FCs used to model the vulnerability of the power system components, classifying them according to the physical magnitude and the system element subject to each type of event. Furthermore, a comparison of results obtained applying different FCs is developed to show the relevance of their modelling. The content of this paper can be used as a hands-on guide for researchers and power systems engineers to perform resilience studies. INDEX TERMS Resilience, fragility curves (FCs), distribution networks (DNs), transmission networks (TNs), natural hazards, resilience assessments.
Book Chapter, 2023
In Great Britain, 70% of wind-related faults on the transmission power network are attributed to the top 1% gusts. These faults cause outages to millions of customers and have extensive cascading impacts. This study illustrated the application of historical ground measured wind data in a multi-phase resilience analysis process by: (i) projecting an extreme wind event, (ii) assessing components' vulnerabilities, (iii) analysing system's response, (iv) quantifying baseline resilience, and (v) evaluating the effectiveness of selected adaptation measures. The extreme event was modelled as a ubiquitous 100-year return gust event impacting upon the operations of the Reduced Great Britain transmission network test case. The results show an unmet demand of about 569 GWh/Week. Adaptation measures were necessary for 60% of transmission corridors with responsiveness improving resilience by 70%, robustness by 55%, and redundancy by 35%. The study implies that resilience enhancement can be prioritized within high potency corridors and organisational resilience could prove to be more effective than infrastructural and operational resilience. Keywords Critical infrastructure • Outage • Blackout • High impact low probability • Windstorm
Power System Resilience: Current Practices, Challenges, and Future Directions
IEEE Access, 2020
The frequency of extreme events (e.g., hurricanes, earthquakes, and floods) and manmade attacks (cyber and physical attacks) has increased dramatically in recent years. These events have severely impacted power systems ranging from long outage times to major equipment (e.g., substations, transmission lines, and power plants) destructions. This calls for developing control and operation methods and planning strategies to improve grid resilience against such events. The first step toward this goal is to develop resilience metrics and evaluation methods to compare planning and operation alternatives and to provide techno-economic justifications for resilience enhancement. Although several power system resilience definitions, metrics, and evaluation methods have been proposed in the literature, they have not been universally accepted or standardized. This paper provides a comprehensive and critical review of current practices of power system resilience metrics and evaluation methods and discusses future directions and recommendations to contribute to the development of universally accepted and standardized definitions, metrics, evaluation methods, and enhancement strategies. This paper thoroughly examines the consensus on the power system resilience concept provided by different organizations and scholars and existing and currently practiced resilience enhancement methods. Research gaps, associated challenges, and potential solutions to existing limitations are also provided. INDEX TERMS Critical review; extreme events; power system resilience; resilience definitions, metrics, and enhancement strategies.
Probabilistic Assessment of Power Systems Resilience Under Natural Disasters
Maǧallaẗ Kulliyyaẗ Dār Al-ʿulūm, 2023
Extreme weather can have a substantial influence on a power system's operational resilience since they are highimpact, low-probability (HILP) events. Therefore, power systems must be resilient to HILP incidents in addition to being reliable against widely spread and credible threats. Despite the rarity of such events, the severity of their potential impact necessitates the development of appropriate resilience assessment tools to capture their implications and enhance the resilience of energy infrastructure systems. In this paper, a probabilistic strategy is proposed to assess and evaluate the operational resilience of power distribution networks against the impacts of HILP events depending on value-at-risk and conditionally value-at-risk quantitative risk-based assessments. With several scenarios built on sequentially Monte Carlo simulations, the consequence of a windstorm on a distribution network can be assessed using a probability-based resilience assessment methodology. The presented method is examined on an IEEE 37-bus system. Different case studies based on detailed data are presented and analyzed to demonstrate the proposed method's usefulness.
2020
The frequency of disruptive and newly emerging threats (e.g. man-made attacks—cyber and physical attacks; extreme natural events—hurricanes, earthquakes, and floods) has escalated in the last decade. Impacts of these events are very severe ranging from long power outage duration, major power system equipment (e.g. power generation plants, transmission and distribution lines, and substation) destruction, and complete blackout. Accurate modeling of these events is vital as they serve as mathematical tools for the assessment and evaluation of various operations and planning investment strategies to harden power systems against these events. This paper provides a comprehensive and critical review of current practices in modeling of extreme events, system components, and system response for resilience evaluation and enhancement, which is a important stepping stone toward the development of complete, accurate, and computationally attractive modeling techniques. The paper starts with revie...
Energies, 2021
Nowadays, distribution network operators are urged by regulatory authorities to reduce the load disruptions due to extreme weather events, i.e., to enhance network resilience: in particular, in Italy they are required to present a yearly plan (called “resilience plans”) describing the interventions aimed to improve network resilience. To this purpose, they need new methodologies and tools to assess the network resilience and to quantify the benefits of countermeasures. This paper proposes the application of a risk-based framework and tool to assess the impacts of extreme weather events in T&D grids, which anticipate critical network situations in presence of incumbent weather threats. To do this, the forecasting of weather events is combined with the component vulnerability models in order to predict which components are more prone to fail. Based on this set of components, the set of most risky contingencies is identified and their impacts on the distribution network in terms of uns...
Spatial Risk Analysis of Power Systems Resilience During Extreme Events
The increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real-time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on proba-bilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience-based decisions for risk mitigation. The IEEE 24-bus Reliability Test System has been used to demonstrate the effectiveness of the proposed on-line risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method.