A microgrid formation-based restoration model for resilient distribution systems using distributed energy resources and demand response programs

In recent years, resilience enhancement of electricity distribution systems has attracted much attention due to the significant rise in high-impact rare (HR) natural event outages. The performance of the post-event restoration after an HR event is an effective measure for a resilient distribution network. In this paper, a multi-objective restoration model is presented for improving the resilience of an electricity distribution network. In the first objective function, the load shedding in the restoration process is minimized. As the second objective function, the restoration cost is minimized which contradicts the first objective function. Microgrid (MG) formation, distributed energy resources (DERs), and demand response (DR) programs are employed to create the necessary flexibility in distribution network restoration. In the proposed model, DERs include fossil-fueled generators, renewable wind-based and PV units, and energy storage system while demand response programs include transferable, curtailable, and shiftable loads. The proposed multi-objective model is solved using ɛ-constraint method and the optimal solution is selected using the fuzzy satisfying method. Finally, the proposed model was successfully examined on 37-bus and 118-bus distribution networks. Numerical results verified the efficacy of the proposed method as well.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Risk-based Probabilistic Quantification of Power Distribution System Operational Resilience

It is of growing concern to ensure the resilience in electricity infrastructure systems to extreme weather events with the help of appropriate hardening measures and new operational procedures. An effective mitigation strategy requires a quantitative metric for resilience that can not only model the impacts of the unseen catastrophic events for complex electric power distribution networks but also evaluate the potential improvements offered by different planning measures. In this paper, we propose probabilistic metrics to quantify the operational resilience of the electric power distribution systems to high-impact low-probability (HILP) events. Specifically, we define two risk-based measures: Value-at-Risk ($VaR_\alpha$) and Conditional Value-at-Risk ($CVaR_\alpha$) that measure resilience as the maximum loss of energy and conditional expectation of a loss of energy, respectively for the events beyond a prespecified risk threshold, $\alpha$. Next, we present a simulation-based framework to evaluate the proposed resilience metrics for different weather scenarios with the help of modified IEEE 37-bus and IEEE 123-bus system. The simulation approach is also extended to evaluate the impacts of different planning measures on the proposed resilience metrics.Comment: 12 pages, 11 figures, journa

Resilience of data centre power system: modelling of sustained operation under outage, definition of metrics, and application

A novel criterion for quantifying the resilience of power systems supplying data centres is formulated to measure the system's ability to sustain functionality even during an outage. By comparative analysis of two alternative data centre power systems covering apparatus of electrical power supply and environmental control, it is shown that reliability and availability alone are insufficient as metrics to gauge different designs. The gap is bridged by the proposed resilience analysis to further evaluate situations of single and double outages. As a complement to the indicators of single point of failure and double point of failure, respectively, N−1 and N−2 security criteria, the novel metrics of a single point of reduced availability and double point of reduced availability are proposed. These criteria identify those single subsystems or subsystem pairs causing system availability to drop below requested levels in periods when they are out of service. The metrics so offer information on the overall system's availability during times of maintenance and failures. Thanks to this understanding, it is shown that a guided reduction of the number of subsystems considering their relative importance can lead to designs offering desirable trade-offs in terms of complexity, reliability, availability, and resilience.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

-ilities Tradespace and Affordability Project – Phase 3

One of the key elements of the SERC’s research strategy is transforming the practice of systems engineering and associated management practices – “SE and Management Transformation (SEMT).” The Grand Challenge goal for SEMT is to transform the DoD community’s current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first, document-driven, point- solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise- oriented, hardware-software-human engineered, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046)

RiskNet: neural risk assessment in networks of unreliable resources

We propose a graph neural network (GNN)-based method to predict the distribution of penalties induced by outages in communication networks, where connections are protected by resources shared between working and backup paths. The GNN-based algorithm is trained only with random graphs generated on the basis of the Barabási–Albert model. However, the results obtained show that we can accurately model the penalties in a wide range of existing topologies. We show that GNNs eliminate the need to simulate complex outage scenarios for the network topologies under study—in practice, the entire time of path placement evaluation based on the prediction is no longer than 4 ms on modern hardware. In this way, we gain up to 12 000 times in speed improvement compared to calculations based on simulations.This work was supported by the Polish Ministry of Science and Higher Education with the subvention funds of the Faculty of Computer Science, Electronics and Telecommunications of AGH University of Science and Technology (P.B., P.C.) and by the PL-Grid Infrastructure (K.R.).Peer ReviewedPostprint (published version

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

Resilient power grid for smart city

Modern power grid has a fundamental role in the operation of smart cities. However, high impact low probability extreme events bring severe challenges to the security of urban power grid. With an increasing focus on these threats, the resilience of urban power grid has become a prior topic for a modern smart city. A resilient power grid can resist, adapt to, and timely recover from disruptions. It has four characteristics, namely anticipation, absorption, adaptation, and recovery. This paper aims to systematically investigate the development of resilient power grid for smart city. Firstly, this paper makes a review on the high impact low probability extreme events categories that influence power grid, which can be divided into extreme weather and natural disaster, human-made malicious attacks, and social crisis. Then, resilience evaluation frameworks and quantification metrics are discussed. In addition, various existing resilience enhancement strategies, which are based on microgrids, active distribution networks, integrated and multi energy systems, distributed energy resources and flexible resources, cyber-physical systems, and some resilience enhancement methods, including probabilistic forecasting and analysis, artificial intelligence driven methods, and other cutting-edge technologies are summarized. Finally, this paper presents some further possible directions and developments for urban power grid resilience research, which focus on power-electronized urban distribution network, flexible distributed resource aggregation, cyber-physical-social systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology

System Qualities Ontology, Tradespace and Affordability (SQOTA) Project – Phase 4

This task was proposed and established as a result of a pair of 2012 workshops sponsored by the DoD Engineered Resilient Systems technology priority area and by the SERC. The workshops focused on how best to strengthen DoD’s capabilities in dealing with its systems’ non-functional requirements, often also called system qualities, properties, levels of service, and –ilities. The term –ilities was often used during the workshops, and became the title of the resulting SERC research task: “ilities Tradespace and Affordability Project (iTAP).” As the project progressed, the term “ilities” often became a source of confusion, as in “Do your results include considerations of safety, security, resilience, etc., which don’t have “ility” in their names?” Also, as our ontology, methods, processes, and tools became of interest across the DoD and across international and standards communities, we found that the term “System Qualities” was most often used. As a result, we are changing the name of the project to “System Qualities Ontology, Tradespace, and Affordability (SQOTA).” Some of this year’s university reports still refer to the project as “iTAP.”This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-0004.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-0004

Cyber-Physical Threat Intelligence for Critical Infrastructures Security

Modern critical infrastructures comprise of many interconnected cyber and physical assets, and as such are large scale cyber-physical systems. Hence, the conventional approach of securing these infrastructures by addressing cyber security and physical security separately is no longer effective. Rather more integrated approaches that address the security of cyber and physical assets at the same time are required. This book presents integrated (i.e. cyber and physical) security approaches and technologies for the critical infrastructures that underpin our societies. Specifically, it introduces advanced techniques for threat detection, risk assessment and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM), pen-testing, vulnerability assessment and security data analytics can be used in the context of integrated Critical Infrastructure Protection. The novel methods and techniques of the book are exemplified in case studies involving critical infrastructures in four industrial sectors, namely finance, healthcare, energy and communications. The peculiarities of critical infrastructure protection in each one of these sectors is discussed and addressed based on sector-specific solutions. The advent of the fourth industrial revolution (Industry 4.0) is expected to increase the cyber-physical nature of critical infrastructures as well as their interconnection in the scope of sectorial and cross-sector value chains. Therefore, the demand for solutions that foster the interplay between cyber and physical security, and enable Cyber-Physical Threat Intelligence is likely to explode. In this book, we have shed light on the structure of such integrated security systems, as well as on the technologies that will underpin their operation. We hope that Security and Critical Infrastructure Protection stakeholders will find the book useful when planning their future security strategies

MEASUREMENT AND ENHANCEMENT OF THE RESILIENCE OF POWER SYSTEMS WITH A COMBINED DIESEL AND SOLAR POWER BACKUP

Power outages shut down facilities such as hospitals, shelters, and communication services. Each power system needs to be resilient to power outages. In a power system, resilience can be achieved by infrastructure hardening; smart meter (AMI), energy storage, micro grid, renewable energy and accessibility of critical components. Most critical systems, such as hospitals, have a backup power that is deiseal power generator. The resilience of such a power system refers to how a backup power can still supply the critical load or base load for such critical systems when facing to the prime power outage. This thesis studies how the resilience of such a power system can be quantitatively measured and whether a combined diesel and solar backup power can enhance the resilience of the entire power system with an affordable cost. Specifically, the hospitals in Saskatoon were taken as a study vehicle. A literature review was conducted first, which revealed that there was no satisfactory quantitative measurement available in literature for the resilience of power systems on the occasion of prime power outages. The overall objective of this thesis was thus to develop a quantitative measure for the resilience of power systems with a backup power when facing the prime power outage. The problem is in essence about the reliability of the backup power in the event of the prime grid power is disrupted. A general measure for the resilience of the backup power system (R for short), which can be multiple types of power generators, was developed, which was dimensionless (i.e., independent of the scale of the system). The measure was proved to be reasonable to the extreme cases (i.e., R=0, R=1). The use of the proposed measurement was illustrated for two situations of the backup power: (i) the backup power being a diesel power generator only, and (ii) the backup power being a combined diesel power generator and solar panel. The situation (i) corresponds to the current situation of the backup power in the hospitals in Saskatoon. The result shows that the resilience of the RUH (royal university hospital) is the highest one (R=70.5%) among the three hospitals in Saskatoon with the other two being SCH (Saskatoon City Hospital) and SPH (Saint Paul Hospital), and the resilience of SPH is the lowest one (R=54%). This result was in agreement with the experience of the managers of the hospitals. The economics of the combined backup power (diesel plus solar power generators) was studied with the help of a software system called SAM (system advisor model). Specifically, the power generated by and economic attributes of the solar panel of different sizes without battery storage were analyzed for the three hospitals, respectively. Note that the economic attributes are NPV (net present value) and payback time. The resilience of the combined backup power was calculated for different sizes of solar panels with the help of SAM and the proposed measure. The optimal design, namely the size of solar panel, was obtained in terms of the resilience and payback time; specifically, for the RUH, the size of solar panel is 700 KW (R of the solar panel alone is 35%; R of the combined backup power is 98%; the payback is 13.1 years, the capital cost is 1488490$), for the SPH, the size of solar panel is 500 KW (R of the solar panel alone is 25$), and for the SCH, the size of solar panel is 500 KW (R of the solar panel alone is 20%; R of the combined backup power is 94%; the payback is 10.4 years, the capital cost is $1060940). Besides, in the normal situation, the reduction of the grid power by solar power is about 7%. This research can thus conclude that the resilience of the backup power system of the hospitals in Saskatoon can be improved by adding solar panels with an acceptable cost payback time and at the same time the environmental sustainability, related to the fossil fuel power generation, can is also improved. The primary contribution of this thesis research is the provision of a quantitative measure for the resilience of a power system including a backup power, especially with respect to the recovery stage in the event of the prime power outage. The secondary contribution is the increase of the resilience of the power system of the hospitals in Saskatoon by 25% for SPH, 35% for RUH, and 20% for SCH and the reduction of the use of the grid power by 7% for the benefit to the environmental sustainability