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Journal ArticleDOI: 10.1080/23789689.2019.1710074

A resilience assessment of an interdependent multi-energy system with microgrids

04 Mar 2021-Vol. 6, pp 42-55
Abstract: Multi-energy systems (MES) depend on various energy sources to supply reliable and constant energy for our daily activities. The interdependencies between various energy sources could cause the MES...

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Topics: Energy source (64%), Resilience (network) (62%)
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11 results found


Open accessJournal ArticleDOI: 10.3390/SU12114660
07 Jun 2020-Sustainability
Abstract: Traffic congestion is a perpetual problem for the sustainability of transportation development. Traffic congestion causes delays, inconvenience, and economic losses to drivers, as well as air pollution. Identification and quantification of traffic congestion are crucial for decision-makers to initiate mitigation strategies to improve the overall transportation system’s sustainability. In this paper, the currently available measures are detailed and compared by implementing them on a daily and weekly traffic historical dataset. The results showed each measure showed significant variations in congestion states while indicating a similar congestion trend. The advantages and disadvantages of each measure are identified from the data analysis. This study summarizes the current road traffic congestion measures and provides a constructive insight into the development of a sustainable and resilient traffic management system.

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Topics: Traffic congestion (67%)

37 Citations


Journal ArticleDOI: 10.1109/JIOT.2020.3018687
Liudong Xing1Institutions (1)
Abstract: In the Internet of Things (IoT), various devices operate collaboratively in collecting data, relaying information to one another, and processing information intelligently. Due to interactions and dependencies between the IoT devices, the malfunction of one device may trigger a cascade of unexpected and often undesired state changes of other devices, introducing or accelerating catastrophic cascading failures. Understanding the causes of cascading failures and modeling their behavior and effects is crucial for guaranteeing the reliability of IoT systems and delivering the desired quality of service. This article systematically reviews cascading failures modeling and reliability analysis methodologies, as well as mitigation strategies for building the resilience of IoT systems against cascading failures. The review covers diverse IoT applications, from smart grids to smart homes, from sensor networks to IoT cloud computing, and from transportation networks to interdependent infrastructure networks. Opportunities and open research issues are also discussed in relation to restrictions of the current cascading failure models and methods, and potential new technologies and complexity of the constantly evolving IoT systems.

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Topics: Cascading failure (56%), Resilience (network) (52%)

16 Citations


Journal ArticleDOI: 10.1016/J.MEASUREMENT.2021.109051
Tanzina Afrin1, Nita Yodo1Institutions (1)
01 Apr 2021-Measurement
Abstract: For ensuring a robust traffic management system, monitoring traffic conditions promptly by estimating the congestion level is crucial. The current measures can only represent the variations of specific standard parameters and do not consider the probabilistic property. In this paper, a Bayesian Network (BN) based probabilistic congestion estimation approach is proposed. The proposed BN-based approach considers both speed and volume-related measures and provides a probabilistic estimation of the probable congestion state. For recurring and nonrecurring congestion, two different BN models were developed and implemented in realtime datasets. The case study results showed that the proposed BN models could quantify the probable congestion level in terms of a probability for each state in a variable, at the presence of different combinations of prior variables’ state. Further, the proposed BN based approach can be employed in the decision-making process that involves the probabilistic estimation of traffic congestion with a vision of the realtime circumstances.

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7 Citations


Journal ArticleDOI: 10.1080/23789689.2020.1795571
15 Aug 2020-
Abstract: Given the unforeseen events that take continue to place worldwide, cities are experiencing rapid transformations. To maintain their basic functions, cities have to be resilient– possess the ability...

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5 Citations


Journal ArticleDOI: 10.1016/J.IJEPES.2021.106974
Abstract: In this paper, the applicability of Microgrids (MGs) is reviewed for power system resilience against low-probability high-impact (LPHI) events. Financial issues have been always one of the major priorities in the scheduling of MGs. Although these systems can feed their loads in islanding mode, resilient operation of them under critical situations caused by LPHI events is a challenging problem. Improving resilience increases MG costs, therefore it is necessary to establish a trade-off between resilience and economic metrics. Therefore, the main purpose of this paper is to develop a novel multi-objective resilience-economic stochastic MG scheduling model. The proposed bi-level resilience-oriented stochastic scheduling integrates the economic perspective along with resilience function simultaneously using a multi-objective mixed-integer linear programming approach. The considered MG resilience function includes various metrics such as the ability to withstand, quick recovery, and the technical criteria in the face of low-probability high-impact events. The proposed method is tested on the modified IEEE 33-bus power system with a set of distributed energy resources, energy storage systems, and electric vehicle parking lots. The results outlined that, although, the integration of the resilience metrics in the MG scheduling problem has increased the operation cost of the MG approximately 25%, but improved the MG resilience more than 70%. On the other hand, the proper management of the independent distributed energy resources enhanced the resilience of the MG approximately 16% while decreased the operation cost of the MG by at least 28%.

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Topics: Resilience (network) (65%), Scheduling (production processes) (52%), Job shop scheduling (51%) ... show more

3 Citations


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29 results found


Open accessJournal ArticleDOI: 10.1016/J.ENERGY.2013.10.041
Pierluigi Mancarella1Institutions (1)
01 Feb 2014-Energy
Abstract: MES (multi-energy systems) whereby electricity, heat, cooling, fuels, transport, and so on optimally interact with each other at various levels (for instance, within a district, city or region) represent an important opportunity to increase technical, economic and environmental performance relative to “classical” energy systems whose sectors are treated “separately” or “independently”. This performance improvement can take place at both the operational and the planning stage. While such systems and in particular systems with distributed generation of multiple energy vectors (DMG (distributed multi-generation)) can be a key option to decarbonize the energy sector, the approaches needed to model and relevant tools to analyze them are often of great complexity. Likewise, it is not straightforward to identify performance metrics that are capable to properly capture costs and benefits that are relating to various types of MES according to different criteria. The aim of this invited paper is thus to provide the reader with a comprehensive and critical overview of the latest models and assessment techniques that are currently available to analyze MES and in particular DMG systems, including for instance concepts such as energy hubs, microgrids, and VPPs (virtual power plants), as well as various approaches and criteria for energy, environmental, and techno-economic assessment.

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808 Citations


Journal ArticleDOI: 10.1016/J.RESS.2013.07.004
Royce A. Francis1, Behailu B. Bekera1Institutions (1)
Abstract: In this paper, we have reviewed various approaches to defining resilience and the assessment of resilience. We have seen that while resilience is a useful concept, its diversity in usage complicates its interpretation and measurement. In this paper, we have proposed a resilience analysis framework and a metric for measuring resilience. Our analysis framework consists of system identification, resilience objective setting, vulnerability analysis, and stakeholder engagement. The implementation of this framework is focused on the achievement of three resilience capacities: adaptive capacity, absorptive capacity, and recoverability. These three capacities also form the basis of our proposed resilience factor and uncertainty-weighted resilience metric. We have also identified two important unresolved discussions emerging in the literature: the idea of resilience as an epistemological versus inherent property of the system, and design for ecological versus engineered resilience in socio-technical systems. While we have not resolved this tension, we have shown that our framework and metric promote the development of methodologies for investigating “deep” uncertainties in resilience assessment while retaining the use of probability for expressing uncertainties about highly uncertain, unforeseeable, or unknowable hazards in design and management activities.

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612 Citations


Journal ArticleDOI: 10.1109/TSG.2015.2429653
Chen Chen1, Jianhui Wang1, Feng Qiu1, Dongbo Zhao2Institutions (2)
Abstract: Microgrids with distributed generation (DG) provide a resilient solution in the case of major faults in a distribution system due to natural disasters. This paper proposes a novel distribution system operational approach by forming multiple microgrids energized by DG from the radial distribution system in real-time operations to restore critical loads from the power outage. Specifically, a mixed-integer linear program is formulated to maximize the critical loads to be picked up while satisfying the self-adequacy and operation constraints for the microgrids formation problem by controlling the ON/OFF status of the remotely controlled switch devices and DG. A distributed multiagent coordination scheme is designed via local communications for the global information discovery as inputs of the optimization, which is suitable for autonomous communication requirements after the disastrous event. The formed microgrids can be further utilized for power quality control and can be connected to a larger microgrid before the restoration of the main grids is complete. Numerical results based on modified IEEE distribution test systems validate the effectiveness of our proposed scheme.

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Topics: Microgrid (56%), Distributed generation (52%)

455 Citations


Journal ArticleDOI: 10.1109/TSG.2014.2311465
Amin Khodaei1Institutions (1)
Abstract: One of complementary value propositions of microgrids is to improve power system resiliency via local supply of loads and curtailment reduction. This subject is investigated in this paper by proposing a resiliency-oriented microgrid optimal scheduling model. The proposed model aims at minimizing the microgrid load curtailment by efficiently scheduling available resources when supply of power from the main grid is interrupted for an extended period of time. The problem is decomposed to normal operation and resilient operation problems. The normal operation problem solution, i.e., unit commitment states, energy storage schedules, and adjustable loads schedules, is employed in the resilient operation problem to examine microgrid capability in supplying local loads during main grid supply interruption. The schedule is revised via resiliency cuts if a zero mismatch is not obtained. Prevailing operational uncertainties in load, non-dispatchable generation, and the main grid supply interruption time and duration are considered and captured using a robust optimization method. The final solution, which is obtained in an iterative manner, is economically optimal, guarantees robustness against prevailing operational uncertainties, and supports a quick islanding with minimum consumer inconvenience and load curtailment. Numerical simulations demonstrate the effectiveness of the proposed resiliency-oriented microgrid optimal scheduling model applied to a test microgrid.

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Topics: Microgrid (62%), Islanding (53%), Schedule (52%) ... show more

274 Citations


Journal ArticleDOI: 10.1109/JPROC.2017.2685558
09 May 2017-
Abstract: This paper focuses on the role of networked microgrids as distributed systems for enhancing the power system resilience against extreme events. Resilience is an intrinsically complex property which requires deep understanding of microgrid operation in order to respond effectively in emergency conditions. The paper first introduces the definition and offers a generic framework for analyzing the power system resilience. The notion that large power systems can achieve a higher level of resilience through the deployment of networked microgrids is discussed in detail. In particular, the management of networked microgrids for riding through extreme events is analyzed. In addition, the merits of advanced information and communication technologies (ICTs) in microgrid-based distributed systems that can support the power system resilience are presented. The paper also points out the challenges for expanding the role of distributed systems and concludes that networked microgrids in particular provide a universal solution for improving the resilience against extreme events in Smart Cities.

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Topics: Resilience (network) (65%), Microgrid (51%)

246 Citations


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