Reliability Evaluation of Composite Power Systems Including the Effects of Hurricanes

Adverse weather such as hurricanes can significantly affect the reliability of composite power systems. Predicting the impact of hurricanes can help utilities for better preparedness and make appropriate restoration arrangements. In this dissertation, the impact of hurricanes on the reliability of composite power systems is investigated. Firstly, the impact of adverse weather on the long-term reliability of composite power systems is investigated by using Markov cut-set method. The Algorithms for the implementation is developed. Here, two-state weather model is used. An algorithm for sequential simulation is also developed to achieve the same goal. The results obtained by using the two methods are compared. The comparison shows that the analytical method can obtain comparable results and meantime it can be faster than the simulation method. Secondly, the impact of hurricanes on the short-term reliability of composite power systems is investigated. A fuzzy inference system is used to assess the failure rate increment of system components. Here, different methods are used to build two types of fuzzy inference systems. Considering the fact that hurricanes usually last only a few days, short-term minimal cut-set method is proposed to compute the time-specific system and nodal reliability indices of composite power systems. The implementation demonstrates that the proposed methodology is effective and efficient and is flexible in its applications. Thirdly, the impact of hurricanes on the short-term reliability of composite power systems including common-cause failures is investigated. Here, two methods are proposed to archive this goal. One of them uses a Bayesian network to alleviate the dimensionality problem of conditional probability method. Another method extends minimal cut-set method to accommodate common-cause failures. The implementation results obtained by using the two methods are compared and their discrepancy is analyzed. Finally, the proposed methods in this dissertation are also applicable to other applications in power systems

An Analytical Approach to Evaluate the Reliability of Offshore Wind Power Plants Considering Environmental Impact

The accurate quantitative reliability evaluation of off-shore wind power plants (OWPPs) is an important part in planning and helps to obtain economic optimization. However, loop structures in collector systems and large quantities of components with correlated failures caused by shared ambient influences are significant challenges in the reliability evaluation. This paper proposes an ana-lytical approach to evaluate the reliability of OWPPs considering environmental impact on failures and solve the challenges by protection zone models, equivalent power unit models and common cause failure (CCF) analysis. Based on investigation of the characteristics of OWPP and related failures mechanisms, the components are divided into three CCF subsets. With the aid of the protection zone model and equivalent power unit model merged with CCF, the faulty collector system state eval-uation is applied to reduce the computational burden. The case studies present the necessity and improved per-formance of merging CCF analysis into modeling via the comparison with other two simplified methods. A sensi-tivity analysis is also carried out to account for inaccu-racy of failure data. The results show that the assump-tion of independent failures in the conventional method might lead to over-optimistic or over-pessimistic evalua-tion depending on the CCF style

Application of the Analogue Method to Modeling Heat Waves: A Case Study With Power Transformers

Large power transformers (LPTs) are critical yet increasingly vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and thereby increase the premature failure risk. Without adequate preparedness, a widespread situation would ultimately lead to prolonged grid disruption and incur excessive economic costs. In this study, we investigate the impact of climate warming and corresponding shifts in heat waves on a selected LPT located in the Northeast corridor of the United States. We apply an analogue method, which detects the occurrence of heat waves based on the salient, associated large-scale atmospheric conditions (“composites”), to assess the risk of future change in heat wave occurrence. Compared with the more conventional approach that relies on climate model-simulated daily maximum temperature, the analogue method produces model medians of late twentieth-century heat wave frequency that are more consistent with observation and have stronger inter-model consensus. Under the future climate warming scenarios, multi-model medians of both model daily maximum temperature and the analogue method indicate strong decadal increases in heat wave frequency by the end of the 21st century, but the analogue method improves model consensus considerably. We perform a preliminary assessment on the decrease of transformer lifetime with temperature increase. Future work will focus on using more advanced algorithms to quantify the impact of more frequent heat waves on the transformer’s expected lifetime and associated additional costs. The improved inter-model consensus of the analogue method is viewed as a promising step toward providing actionable information for a more stable, reliable, and environmentally responsible national grid.This work was funded by MIT Lincoln Lab (DE-FOA-0000768)

A survey on power grid faults and their origins: A contribution to improving power grid resilience

UID/EEA/00066/2019One of the most critical infrastructures in the world is electrical power grids (EPGs). New threats affecting EPGs, and their different consequences, are analyzed in this survey along with different approaches that can be taken to prevent or minimize those consequences, thus improving EPG resilience. The necessity for electrical power systems to become resilient to such events is becoming compelling; indeed, it is important to understand the origins and consequences of faults. This survey provides an analysis of different types of faults and their respective causes, showing which ones are more reported in the literature. As a result of the analysis performed, it was possible to identify four clusters concerning mitigation approaches, as well as to correlate them with the four different states of the electrical power system resilience curve.publishe

Safe-To-Fail Infrastructure for Resilient Cities under Non-Stationary Climate

abstract: Motivated by the need for cities to prepare and be resilient to unpredictable future weather conditions, this dissertation advances a novel infrastructure development theory of “safe-to-fail” to increase the adaptive capacity of cities to climate change. Current infrastructure development is primarily reliant on identifying probable risks to engineered systems and making infrastructure reliable to maintain its function up to a designed system capacity. However, alterations happening in the earth system (e.g., atmosphere, oceans, land, and ice) and in human systems (e.g., greenhouse gas emission, population, land-use, technology, and natural resource use) are increasing the uncertainties in weather predictions and risk calculations and making it difficult for engineered infrastructure to maintain intended design thresholds in non-stationary future. This dissertation presents a new way to develop safe-to-fail infrastructure that departs from the current practice of risk calculation and is able to manage failure consequences when unpredicted risks overwhelm engineered systems. This dissertation 1) defines infrastructure failure, refines existing safe-to-fail theory, and compares decision considerations for safe-to-fail vs. fail-safe infrastructure development under non-stationary climate; 2) suggests an approach to integrate the estimation of infrastructure failure impacts with extreme weather risks; 3) provides a decision tool to implement resilience strategies into safe-to-fail infrastructure development; and, 4) recognizes diverse perspectives for adopting safe-to-fail theory into practice in various decision contexts. Overall, this dissertation advances safe-to-fail theory to help guide climate adaptation decisions that consider infrastructure failure and their consequences. The results of this dissertation demonstrate an emerging need for stakeholders, including policy makers, planners, engineers, and community members, to understand an impending “infrastructure trolley problem”, where the adaptive capacity of some regions is improved at the expense of others. Safe-to-fail further engages stakeholders to bring their knowledge into the prioritization of various failure costs based on their institutional, regional, financial, and social capacity to withstand failures. This approach connects to sustainability, where city practitioners deliberately think of and include the future cost of social, environmental and economic attributes in planning and decision-making.Dissertation/ThesisDoctoral Dissertation Sustainability 201

POWER DISTRIBUTION SYSTEM RELIABILITY AND RESILIENCY AGAINST EXTREME EVENTS

The objective of a power system is to provide electricity to its customers as economically as possible with an acceptable level of reliability while safeguarding the environment. Power system reliability has well-established quantitative metrics, regulatory standards, compliance incentives and jurisdictions of responsibilities. The increase in occurrence of extreme events like hurricane/tornadoes, floods, wildfires, storms, cyber-attacks etc. which are not considered in routine reliability evaluation has raised concern over the potential economic losses due to prolonged and large-scale power outages, and the overall sustainability and adaptability of power systems. This concern has motivated the utility planners, operators, and policy makers to acknowledge the importance of system resiliency against such events. However, power system resiliency evaluation is comparatively new, and lacks widely accepted standards, assessment methods and metrics. The thesis presents comparative review and analysis of power system resilience models, methodologies, and metrics in present literature and utility applications. It presents studies on two very different types of extreme events, (i) man-made and (ii) natural disaster, and analyzes their impacts on the resiliency of a distribution system. It draws conclusions on assessing and improving power system resiliency based on the impact of the extreme event, response from the distribution system, and effectiveness of the mitigating measures to tackle the extreme event. The advancement in technologies has seen an increasing integration of cyber and physical layer of the distribution system. The distribution system operators avails from the symbiotic relation of the cyber-physical layer, but the interdependency has also been its Achilles heel. The evolving infrastructure is being exposed to increase in cyber-attacks. It is of paramount importance to address the aforementioned issue by developing holistic approaches to comprehensibly upgrade the distribution system preventing huge financial loss and societal repercussions. The thesis models a type of cyber-attack using false data injection and evaluates its impact on the distribution system. It does so by developing a resilience assessment methodology accompanied by quantitative metrics. It also performs reliability evaluation to present the underlying principle and differences between reliability and resiliency. The thesis also introduces new indices to demonstrate the effectiveness of a bad-data detection strategy against such cyber-attacks. Extreme events like hurricane/tornadoes, floods, wildfires, storm, cyber-attack etc. are responsible for catastrophic damage to critical infrastructure and huge financial loss. Power distribution system is an important critical infrastructure driving the socio-economic growth of the country. High winds are one of the most common form of extreme events that are responsible for outages due to failure of poles, equipment damage etc. The thesis models effective extreme wind events with the help of fragility curves, and presents an analysis of their impacts on the distribution system. It also presents infrastructural and operational resiliency enhancement strategies and quantifies the effectiveness of the strategy with the metrics developed. It also demonstrates the dependency of resiliency of distribution system on the structural strength of transmission lines and presents measures to ensure the independency of the distribution system. The thesis presents effective resilience assessment methodology that can be valuable for distribution system utility planners, and operators to plan and ensure a resilient distribution system

Quantifizierung der Zuverlässigkeit und Komponentenbedeutung von Infrastrukturen unter Berücksichtigung von Naturkatastropheneinwirkung

The central topic is the quantification of the reliability of infrastructure networks subject to extreme wind loads. Random fields describe the wind distributions and calibrated fragility curves yield the failure probabilities of the components as a function of the wind speed. The network damage is simulated taking into account possible cascading component failures. Defined "Importance Measures" prioritize the components based on their impact on system reliability - the basis for system reliability improvement measures.Zentrales Thema ist die Quantifizierung der Zuverlässigkeit von Infrastrukturnetzen unter Einwirkung extremer Windlasten. Raumzeitliche Zufallsfelder beschreiben die Windverteilungen und spezifisch kalibrierte Fragilitätskurven ergeben die Versagenswahrscheinlichkeiten der Komponenten. Der Netzwerkschaden wird unter Berücksichtigung von kaskadierenden Komponentenausfällen simuliert. Eigens definierte „Importance Measures“ priorisieren die Komponenten nach der Stärke ihres Einflusses auf die Systemzuverlässigkeit - die Basis für Verbesserungen der Systemzuverlässigkeit

The role of safety barrier performance depletion in the escalation of Natech scenarios

Natural hazards can cause severe damages to chemical and process facilities, triggering technological scenarios involving hazardous materials. The risk related to this type of cascading events, defined Natech accidents, is expected to grow in the foreseeable future due to the enhanced severity of some categories of natural phenomena brought by climate change. A critical feature of Natech events is that the safety systems implemented might undergo some extent of depletion and performance reduction due to the natural event, and this might heavily influence the likelihood and the features of accident escalation. While methodologies have been proposed to perform a quantitative assessment of Natech risk, the role of the concurrent depletion of the safety systems has been only recently investigated and has not been addressed systematically yet. Hence, a comprehensive framework to assess the risk related to the escalation of Natech scenarios and to possible domino effects due to concurrent safety barrier depletion is presented. A specific three-level approach was conceived to evaluate barrier performance according to system complexity and uncertainty in the impact of natural events. A straightforward analysis (L0) based on a Boolean approach is applied for simple barriers when their missing action can be assessed with a low uncertainty. A more detailed analysis (L1) leveraging specific performance modification factors to express the likelihood that similar reference barriers will fail is applied in case of relevant uncertainty. For the analysis of complex barriers and situations when system architecture differs from reference configurations, a further level (L2) based on fault tree analysis is introduced to consider barrier subsystem failure during natural events and to update the overall unavailability of the system. A dedicated event tree approach is then used to embed barrier performance into the quantitative risk assessment of Natech scenarios. The methodology was applied to a test case demonstrating that the quantification of the updated performance of the considered set of safety barriers during natural hazards leads to a relevant increase in overall Natech risk figures