Article
To read the full-text of this research, you can request a copy directly from the authors.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... In recent years, the resilience of power system [22][23][24][25][26][27][28] and gas system [29,30] has been studied independently. Ref. [22,23] presented the concepts of power system resilience and distinguished the concepts between reliability and resilience. ...
... In recent years, the resilience of power system [22][23][24][25][26][27][28] and gas system [29,30] has been studied independently. Ref. [22,23] presented the concepts of power system resilience and distinguished the concepts between reliability and resilience. Ref. [24] proposed a novel resilience assessment methodology by defining two indices about the system resilience and component resilience, respectively. ...
... The details of this IEGDS can be found in Ref. [52]. In this IEGDS, buses 1, 15, 29 are connected with coal-fired generators, while buses 6,9,17,21,23 are connected with gas-fired units and also connected with gas nodes 9, 7, 20, 24, 37, respectively. Gas-fired units have smaller capacities than those of coal-fired units but support faster startup and shutdown responses to provide power support in a typhoon. ...
Article
Recent energy systems have witnessed a large number of extreme weather events due to the global climate change, resulting in severe damages and economic losses. To address this problem, this paper proposes a multi-stage stochastic programming model for resilient integrated electricity and natural gas distribution systems under typhoon natural disasters. A three-stage modeling is employed to quantify the system resilience against the dynamic process of a typhoon, where the network reinforcement, network reconfiguration, and network repairing are coordinated. Moreover, the interaction between the power system and natural gas system during a typhoon attack is reflected in this model. To address the uncertainties introduced by the typhoon moving paths, non-anticipativtity constraints are adopted in the proposed multi-stage stochastic programming model. Case studies on a 33-bus-48-node and a 144-bus-85-node integrated electricity and natural gas distribution systems verify the effectiveness of the proposed method. The results of the case studies show that the current IEGDS is still fragile when facing natural disasters, and building a resilient IEGDS to recover from natural disasters rapidly is meaningful in recent vigorous trends of developing integrated energy systems. By applying the proposed model, the proposed model and strategies can enable the IEGDS to reduce the load curtailment by about 52%, and the total economic loss will be reduced by 54%.
... Cette notion de edge computing est cohérente avec des approches de gestion décentralisées et des approches 17 [12]. La co-simulation du réseau électrique et du réseau de communication est utilisée pour étudier l'influence de ce dernier sur le bon fonctionnement du réseau électrique au travers de prismes tels que, entre autres, la cyber-sécurité [13,14] et la résilience face aux attaques informatiques [15], le placement optimal d'éléments de mesure communicants [9], l'influence de la qualité de service sur le contrôle en tension d'un noeud [16], la gestion des défaillances en cascade [17]. Les incertitudes du système de communication sont évaluées dans le cadre des Smart Grids dans [18] : la défaillance d'éléments de l'infrastructure de communication, le taux d'erreurs de transmission, les délais de transmission, les erreurs de routage et la perte d'un message y sont considérés. ...
... On désigne par Smart grid un réseau d'énergie qui intègre des technologies de l'information et de la communication, ce qui concourt à une amélioration de15. La plupart des centrales renouvelables ne possèdent pas de parties mobiles connectées au réseau électrique étant donné qu'elles sont interfacées au travers de modules d'électronique de puissance.16. ...
Thesis
La thématique des smart grids est fondée sur l'interaction d’un réseau électrique et d’un réseau de communication reliant des agents distribués, « intelligents » et communicants. Dans le cas d’un réseau électrique classique, les événements imprévus (perte d'un équipement, ligne saturée, etc) sont principalement amortis et compensés par l'inertie du réseau et ses centrales de réserves. Un smart grid se propose de réduire cette dépendance à l'aide de stratégies de gestion distribuées intelligentes faisant appel à des échanges d'information et donc à un réseau de communication. La question de l'impact de la fiabilité du réseau de communication est donc ici cruciale. Le présent projet se propose donc d'analyser finement l'impact des aléas de communication sur la résilience d'un smart grid et de développer des stratégies de gestion prenant en compte ces aléas pour garantir l'opérabilité et l'efficience du smart grid.On se penche en particulier sur trois types d'algorithmes : un algorithme de marché pair à pair, un algorithme d'Optimal Power Flow qui prend en compte les contraintes physiques du réseau électrique, et enfin un algorithme de marché pair à pair endogène. Nous avons étudié de manière approfondie le principe d'algorithme asynchrone, qui permet de limiter les délais d’attente à chaque itération, ainsi que les effets des aléas du réseau de communication sur la résolution des versions asynchrones de ces algorithmes.
... While these definitions describe the traits of the term, other argue that they do not cover the whole aspect of resilience. Das et al. (2020) suggest in their article that resilience should be divided into what they call resilience measures. The three measures avoidance by prevention, absorption and recover, are relevant for different phases of the crisis, and may contribute the resilience framework. ...
... Developing metrics helps to quantify the actual resilience level of the energy grid (Woltjer et al., 2018). Another method for ensuring resilience in CI proposed by Das et al. (2020) is to conduct a resilience analysis of the behaviour of the infrastructure upon the failure of its constituent elements. The infrastructure's response to the disruptions is analysed by using forward inductive reasoning and characterised by their response time to recover from the events. ...
... The concept of resilience is based on the "bounce back" principle [72]. A resilient grid is considered as an interconnected network of different components [62], [73] that has four fundamental properties of resilience, namely anticipation (outright avoidance / resistance / repulsion of adverse impacts of hazards / being able to prevent possible damage), absorption (capacity to minimize / mitigate / lessen / limit the adverse impacts of hazards / threats and related disasters), recovery (restoration and improvement where appropriate, of disaster affected systems, and communities, including efforts to reduce disaster risk factors), and adaptability (initiatives and measures to reduce the vulnerability of natural and human systems against actual or expected impacts of hazards by studying the previous events and improving or advancing the systems' capacities) after the damaging events [20]. Consequently, [72] perceived resilience as the adaptive ability of enhancing performance, owing to knowledge and alteration, learnt by unceasing change. ...
... [6] recommended that quantitative indicators ought to first be clear and designed to define features' components [69], in addition to being quantifiable, repeatable, and comparable [10] [11]. Further, quantitative resilience metrics should be time dependent [35], [73], to secure the performance [16] of the network during the different phases associated with an event [39] and should also be able to reflect the consequence of a certain disruptive event or the effectiveness of the resilience measures [16]. [3] further expressed the need to describe a quantity that was typical of the practical abilities of the grid in terms of the quantity and / or quality of the services provided by the grid. ...
... Some of the bold examples include blackouts in the United States (2003) and India (2012), which affected millions and led to financial losses of more than a billion US dollars [2]. These and other such events highlight the need for research on the resilience and robustness of power systems against failure [3]. Robustness analysis typically deals with identifying key attributes of The associate editor coordinating the review of this manuscript and approving it for publication was Padmanabh Thakur . ...
... The term ''robustness'' in this paper is primarily concerned with the drop in performance of a power grid when a disruption occurs [18]. Several metrics have been proposed in the literature to study and improve the system robustness against node/link failures [3], [6], [10], [18], [19]. These approaches can be divided into three classes, namely network (topology) based, performance (power flow, system dynamics) based and hybrid which combines topology with electrical properties of the network. ...
Article
Full-text available
Improving the resilience of the power distribution networks is becoming a top priority for the utility companies. Robustness is a key part of resilience, and is often studied through failure-based analysis. Furthermore, with the increasingly dynamic nature of the grid, voltage fluctuation is an important factor to consider while assessing system robustness. Very few metrics exist for capturing robustness to voltage fluctuations, primarily due to their complex computation process. While several failure-based robustness metrics have been proposed in the literature, there is no strict consensus regarding the applicability of these metrics. Therefore, this paper addresses two key gaps in robustness analysis of power distribution networks. First, this paper presents a systematic study of different failure-based robustness metrics by comparing their similarity and dissimilarity in ranking critical nodes of the power distribution network. Secondly, the efficacy of these metrics in characterizing voltage fluctuations is evaluated by comparing their ranking to that of voltage influencing scores. From experimental results, it is shown that hybrid failure-based metrics can quantify voltage fluctuations to a reasonable extent. We highlight the major shortcomings of current metric formulations and discuss possible future research directions related to robustness characteristics and analysis.
... Some important aspects of power system resilience have been extensively investigated. To name a few, first, while the concept of resilience is useful to indicate power system sustainability, etc., it has proved very challenging to quantify and thus requires sophisticated designs of resilience metrics [13,15]. Authors of [16] introduce a multi-stage resilience trapezoid to model power system behaviors before, during and after extreme weather events, and propose a framework to assess both infrastructure and operational resilience. ...
... Given a pre-attack NCED profile determined by the outmost level of Eq. (11), the attacker (i.e., the extreme weather event) in the middle level then finds its optimal attack strategy (i.e., the worst case for the grid) that maximizes the post-attack weighted number of overloaded lines. Specifically, the attacker optimally selects a set of lines to be interdicted (i.e., disconnected from the grid as in physical attacks) [15]. Let be the attack budget. ...
Article
With climate change, we have been witnessing more frequent extreme weather events causing increasingly common large-scale power outages. It is essential and urgent to improve power system resilience, which also substantially impacts the resilience of dependent infrastructures, such as water and health systems. This work investigates the enhancement of power grid resilience using proactive network-constrained economic dispatch (NCED) strategies. An extreme weather event is modeled as an attacker interdicting a selected set of transmission lines to cause overloading of remaining lines, which potentially leads to cascading failures. We define a set of resilience metrics, with the first one being a weighted number of overloaded lines immediately after the attack to capture the potential cascading chain effect, the second one predicting the worst-case value of the first metric to provide a forward-looking evaluation, and the last one assessing whether each line can be overloaded in the worst case to supply more granular awareness. We also propose a defender–attacker–defender NCED model solved by a column-and-constraint generation algorithm to optimize the defined metrics. The model can generate strategies that (1) enhances resilience without additional NCED cost; (2) further enhances resilience with a budgeted extra NCED cost; and (3) achieves a moving target defense scheme shifting the grid’s vulnerable part(s). The associated price of resilience is specifically evaluated. Results on standard test systems demonstrate the proposed methods’ effectiveness. Overall, our methods and results provide insights on the establishment of social, economic and environmental resilience by contributing to the resolution of resilience-related power and energy issues.
... According to the classification of power system accidents (known events, 'grey swan' and 'black swan') in Ref. [44], resilience is mainly aimed at 'grey swan' and 'black swan' events with high impact and low probability, that is, unpredictable, high impact, and rare phenomena, and the consequences caused by such events are often unpredictable, Based on the studies of resilience conception in Ref. [30,38,43,[49][50][51][63][64][65][66][67][68][69], this paper defines the resilience of MECPSs and summarises the illustration of the multi-phase performance response curve of MECPSs, which is shown in Figure 3. The curve denotes the performance level change of MECPSs in extreme events. ...
... The main purpose is to reduce the direct impact of extreme natural disasters and to recover the system to the normal state as soon as possible after the occurrence of extreme natural disasters. Based on the above two purposes, the improvement measures of distribution network resilience are mainly divided into two aspects: planning and operation measures [4,10,22,30,44,47,136,137]. ...
Article
Full-text available
Natural disasters and cyber intrusions threaten the normal operation of the critical Multi‐Energy Systems (MESs) infrastructures. There is still no universally‐accepted definition of MESs resilience under the integration of cyber and physical, and lack of a widely accepted methodology to quantify and assess the resilience in MESs. Hence, this paper introduces an extensive review of the state‐of‐the‐art research of power systems’ resilience. Then, this work proposes the definition of the Multi‐Energy Cyber‐Physical Systems (MECPSs) resilience and its related characteristics. To improve the resilience of MECPSs, this paper investigates extreme natural disaster models and analyses the vulnerability of the system to find the key constraint factors. Furthermore, this work presents the qualitative assessment curve, quantitative indexes, and assessment framework of the MECPSs resilience. Finally, the key improvement measures for the planning and operation of MECPSs resilience and the focus of future research are presented.
... A wide range of real-world systems such as power grids [1], financial transaction networks [2], communication networks (e.g., the Internet) [3], and command and control systems [4] have been modeled as complex networks. Among other characteristics, the resiliency of networked systems has received growing research attention from diverse application areas including economic systems [5], organizational management [6], and multiple engineering systems [7,8]. Generally speaking, resiliency can be viewed as the ability of a system to bounce back from high-impact disruptions to achieve partial or full recovery [9]. ...
Article
Full-text available
Local attacks in networked systems can often propagate and trigger cascading failures. Designing effective healing mechanisms to counter cascading failures is critical to enhance system resiliency. This work proposes a self-healing algorithm for networks undergoing load-based cascading failure. To advance understanding of the dynamics of networks with concurrent cascading failure and self-healing, a general discrete-time simulation framework is developed, and the resiliency is evaluated using two metrics, i.e., the system impact and the recovery time. This work further explores the effects of the multiple model parameters on the resiliency metrics. It is found that two parameters (reactivated node load parameter and node healing certainty level) span a phase plane for network dynamics where three regimes exist. To ensure full network recovery, the two parameters need to be moderate. This work lays the foundation for subsequent studies on optimization of model parameters to maximize resiliency, which will have implications to many real-world scenarios.
... According to the U.S. Department of Energy, grid resiliency is defined as the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions [3]. The methods, challenges, and opportunities for measuring smart grid resilience have been reviewed in [4]. The grid asset hardening strategies for improved grid resiliency have been studied in [5]. ...
Article
Full-text available
Grid resiliency is defined as the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. Following large-scale disruptions of the power grid such as a complete blackout, parallel power system restoration accelerates the recovery process by allowing for simultaneous restoration in each island through network partitioning, thus enhancing grid resiliency. However, existing network partitioning strategies have not sufficiently considered variable renewable resources yet, and may not be flexible or computationally efficient to accommodate additional requirements from the evolving bulk power grid. To bridge these gaps, this study proposes a propagation-based optimization approach for power grid network partitioning. The requirements of blackstart resources, power balancing, synchrocheck relays for ties lines, and increased ramp rate requirements due to variable renewable resources are modeled in the constraints. Through propagation on the physical connectivity of grid assets, the network partitioning issue is formulated as a mixed integer linear programming (MILP) problem. The linearity ensures highly computational performance and optimality of the solutions from the proposed approach to identify the cutset edge possibilities for bulk power grid applications. Graph reduction strategies are proposed to further improve the computational performance for online or nearly online applications. Case studies based on two IEEE benchmark systems show that the proposed MILP model is able to determine the optimal cutset for network partitioning in approximately 0.28 seconds, and the proposed network reduction strategy is able to further improve the computational performance by approximately 9%.
... However, this needs a little attention when main changes are happening due to the integration of RESs, battery storage systems, and EVs. Therefore, requires entirely different control methods in distribution networks [9]. This paper surveys the existing works (2015-2021) on the SG concerning modeling techniques, integration of RES, frameworks, energy trading, and security aspects. ...
Article
Full-text available
High consumption and ever-increasing demand for electricity at commercial, residential, and industrial levels have attracted the research community to look for new technologies for the future grid. A smart grid is an advanced technology-enabled electrical grid system with the incorporation of information and communication technology. The smart grid also enables two-way power flow, and enhanced metering infrastructure capable of self-healing, resilient to attacks, and can forecast future uncertainties. This paper surveys various smart grid frameworks, social, economic, and environmental impacts, energy trading, and integration of renewable energy sources over the years 2015 to 2021. Energy storage systems, plugin electric vehicles, and a grid to vehicle energy trading are explored which can potentially minimize the need for extra generators. This study shows that the integration of renewable energy sources, plug-in electric vehicles, and energy storage systems provide long-term economic and environmental benefits and have identified challenges, opportunities, and future directions. This study is expected to serve as a potential source of guidance for the researchers to explore various aspects of the smart grid over the last 06 years which shows them the future directions. This survey will also serve as a guiding source for transmission and distribution systems operators while showing them the right path to transform their traditional grids into smart grids.
... To mitigate the impacts of extreme weather events on electric infrastructures and power grids, extensive efforts have been devoted toward proposing the concept of resilience. In [8], resilience was defined as a property of systems representing their response to and recovery from low probability and high impact events. The measurements of system resilience are disciplined into ecological resilience [9], psychological resilience [10], risk management [11], and energy security [12]. ...
Article
Full-text available
Extreme weather events are the common causes for power supply interruptions and power outages in electrical distribution systems. Improving the distribution system and enhancing its resilience is becoming crucial due to the increased frequency of extreme weather events. Preparation and allocation of multiple flexible resources, such as mobile resources, fuel resources, and labor resources before extreme weather events can mitigate the effects of extreme weather events and enhance the resilience of power distribution systems. In this paper, a two-stage stochastic mixed-integer linear programming (SMILP) is proposed to optimize the preparation and resource allocation process for upcoming extreme weather events, which leads to faster and more efficient post-event restoration. The objective of the proposed two-stage SMILP is to maximize the served load and minimize the operating cost of flexible resources. The first stage in the optimization problem selects the amounts and locations of different resources. The second stage considers the operational constraints of the distribution system and repair crew scheduling constraints. The proposed stochastic pre-event preparation model is solved by a scenario decomposition method, Progressive Hedging (PH), to ease the computational complexity introduced by a large number of scenarios. Furthermore, to show the impact of solar photovoltaic (PV) generation on system resilience, three types of PV systems are considered during a power outage and the resilience improvements with different PV penetration levels are compared. Numerical results from simulations on a large-scale (more than 10,000 nodes) distribution feeder have been used to validate the effectiveness and scalability of the proposed method.
... Note that some of these traditional concepts, like reliability, risk and, stability are well-established in the scientific literature. In contrast, widely accepted definitions of resilience and quantitative metrics for resilience assessment are not yet well established [43]. Reliability defines the ability of a system to meet operational/safety criteria over the long run with high probability (or to perform a given function over a given time interval). ...
Article
Full-text available
Controlled islanding can enhance power grid resilience and help mitigate the effect of emerging failure by splitting the grid into islands that can be rapidly and independently recovered and managed. In practice, controlled islanding is challenging and requires vulnerability assessment and uncertainty quantification. In this work, we investigate robustness drops due to − line failures and a controlled partitioning strategy for mitigating their consequences. A spectral clustering algorithm is employed to decompose the adjacency matrix of the damaged network and identify optimal network partitions. The adjacency matrix summarizes the power system topology, and different dynamic and static electrical factors such as line impedance and flows are employed to weigh the importance of the grid's cables. Differently from other works, we propose a statistical correlation analysis between vulnerability metrics and goodness of cluster scores. We investigate expected trends in the scores for randomized contingencies of increasing orders and examine their variability for random outages of a given size. We observed that the spectral radius and natural connectivity vary less on randomized failure events of a given size and are more sensitive to the selection of the adjacency matrix weights. Vulnerability scores based on the algebraic connectivity have a higher coefficient of variation for a given damage size and are less dependent on the specific dynamic and static electrical weighting factors. We show a few consistent patterns in the correlations between the scores for the vulnerability of the grid and the optimal clusters. The strength and sign of the correlation coefficients depend on the different electrical factors weighting the transmission lines and the grid-specific topology.
... At the moment, there is a large number of materials on the subject of intelligent networks (Smart Grid). Among them are reviews [1][2][3][4][5][6], scientific publications [7][8][9][10][11][12][13][14], concepts and standards [15][16][17][18][19][20]. A digital network [21][22][23] is a set of electrical network objects, which are controlled on the basis of digital technologies. ...
Article
Full-text available
The digital training ground of Sevastopol State University (SevSU) is a physical model of a section of an intelligent distribution network of a new generation. In this article, a semi-Markov model of the distribution network section of the SevGU digital training ground is built. The reliability stationary characteristics of the considered section of the network are determined, two cases of consumer nutrition are considered. A numerical example of finding the reliability stationary characteristics using the obtained in the article formulas is given. The obtained results make it possible to analyze the reliability and efficiency of the distribution network sections.
... A similarly designed research issue is investigated by [8,10,11]. Approaches to optimizing energy flows within energy communities are also being developed, studied, and tested in scientific literature [12][13][14][15]. Legal frameworks as well as challenges are explored by [9,16]. ...
Article
Full-text available
The use of photovoltaic energy (PV) and the involvement of residents within energy communities are becoming increasingly important elements of decentralized energy systems. However, ownership structures are still too complex to empower electricity consumers to become prosumers. We developed a token-based system of the gradual transfer of PV ownership rights, from the initial investor to residential and small-scale commercial consumers. To demonstrate the system, we set up a simulation of a 27-party mixed usage building with different load profiles, ranging from single student apartments to office units with battery electric vehicles, in a German energy community. As a result, we show that the proposed system design is economically viable for all involved stakeholders over the simulation horizon from 2022 to 2036, with a payback time of <5 years, 4 years to distribute 50% of the PV tokens, and an overall self-consumption share of 69%.
... There are many ways to measure and define electrical grid resilience such as: the total degradation of service after an event; the time spent taking recovery actions; or the rate at which service is recovered [46]. A variety of tools and methods have been developed in the literature to study microgrid or energy resilience [2][3][4]10,[47][48][49][50]. ...
Article
Full-text available
We propose a methodology to determine the impact of different potential mission scenarios upon energy resilience for mission-critical loads attached to a military base’s microgrid infrastructure. The proposed methodology applies to any installation with changing operational states that has energy-resilience requirements. The proposed methodology may be used by energy managers to account for potential mission scenarios that a base may be part of, followed by assessing the microgrid energy resilience to supply the critical loads for said mission scenarios, especially where the external grid power may be unavailable and/or damage to microgrid components may be present. In the event a microgrid design is unable to provide sufficient electrical energy, distributed energy resources and energy storage systems including renewable energy resources may be added to improve energy resilience. A case study is conducted on a fictitious representative military base, microgrid design, and changing mission demands to demonstrate the application of the proposed methodology. This article contributes a methodology for energy managers to evaluate energy resilience using microgrids by accounting for potential mission scenarios, their energy requirements, resulting energy preparedness, and recommendations for improvement, as necessary.
... For the smooth transition to a modern grid, measurement of resilience plays a critical role. In [18], the researchers have adopted qualitative and quantitative approaches to study the resilience of the smart grid. A systematic analysis of resilience metrics is performed to identify the factors and properties that influence stability considering different scenarios. ...
Article
Full-text available
With the transformation from a traditional, rural, and agrarian society to a secular, urban, and industrial society and competitive environment, the rise in the power demand and supply makes it difficult to meet the customer’s expectations and needs. It has become necessary that the electric utility industry make sure they have accurate information about system performance and reliability. The paper presents four different cases through which the reliability of the electric distribution system is studied by calculating customer-oriented indices and load-oriented indices. The assessment is carried out using Modified Reliability Assessment Method (MRAM) on IEEE 24 bus system using MATLAB simulation, and the indicators of reliability analysis such as System Average Interruption Frequency Index (SIAFI), System Average Interruption Duration Index (SAIDI), Customer Average Interruption Duration Index (CAIDI), Average Service Availability Index (ASAI), Average Service Unavailability Index (ASUI), Energy Not Supplied index (ENS), Average Energy Not Supplied (AENS), Annual Customer Interruptions (ACI), and Customer Interruption Duration (CID) are evaluated. Moreover, the impact of the inclusion of cyber networks in the traditional system is also taken into consideration to determine the system’s reliability. Also, the result shows that the parallel combination is more superior to the other one. © 2022 Lalit Tak, Atul Kumar Yadav, Neeraj Kumar Singh, Mahshooq Abdul Majeed and Vasundhara Mahajan.
... Resilience is a property of systems that describes their ability to operate during and recover from adverse situations to resume normal operations. Resilience depends on the system's elements, configuration, interactions with the surrounding environment, and threats [5]. Resilience metrics based on a multi-phase resilience trapezoid for power system operational and infrastructure resilience [6] and sequential Monte-Carlobased time-series simulation models to assess power system resilience [7] have been used to help quantify this characteristic. ...
Article
Full-text available
Traditional optimal power flow (OPF) ensures power systems are operated safely at minimum cost. However, recent incidents, such as the 2021 Texas Winter Storm, have caused immense economic loss and had adverse societal impact. It is worth considering other objectives to guide power system oper- ation more resiliently. The metric RECO quantifies the robustness of ecosystems, which depends on systems network structure and energy flow. It shows the systems inherent ability of absorbing disturbances. An optimal value of RECO has been identified as a key element of the longer-term survivability of ecosystems against various catastrophes. In this paper, we formulate an ecological robustness oriented OPF (RECO OPF) problem to optimize the power system to improve its reliability and survivability under unexpected contingencies. The problem is applied to six power system cases, ranging from 24-bus to 500-bus systems. We study the optimized systems properties and compare the reliability and cost of the RECO OPF with the economics-driven OPF and security-constrained OPF (SCOPF). From the results and analyses, our method improves the systems reliability, with less violations and unsolved scenarios under unexpected disturbances. These show the potential to use RECO to control power flow distribution for improved survivability and resilience.
... It also provides seamless communication environments with sophisticated connectivity. The advanced functionalities of SG include assuring reasonable usage decision-making, saving energy and expenses, power system resilience, etc. [5], [6]. ...
Article
In the era of Industry 4.0 and digital transformation, smart grid (SG) plays an important role in the construction of various smart places. Logs produced by electrical appliances recording power consumption within the grid contain private information and may be collected as evidence for the services of dispute resolution or digital forensics. Therefore, security of the logs is of paramount importance. Our work designs a blockchain-enabled log management scheme with nonrepudiation for SGs. In this article, we employ ciphertext-policy attribute-based encryption to establish a fine-grained access control of the logs, which addresses data confidentiality concern. In addition, we introduce a hybrid blockchain system generating novel signature chains, for achieving an efficient private log protection system with a lot of properties including data loss prevention, tamper resistance, immutability and nonrepudiation. Employing various cost-saving solutions, our scheme achieves an efficient communication with more functionalities and security features, compared with the predecessor works.
... With regard to savvy grids, the optimum charge-discharge of EVs, which has been a significant problem, will stay away from high capital expenses [3,4]. Adjusting power demands can be handled by charging EVs when demand is low and therefore the cost of energy is low, and discharging EVs when demand is high and thus the cost of electricity is high. ...
... This will promote optimal power flow calculation [2], [3], optimal integration of distributed renewable energy [4], [5] and support decarbonization of other sectors such as the transportation [6], [7]. Eventually, CPPSs can intelligently integrate the behaviors of all stakeholders in the energy supply chain, thereby providing economic and safe power supply, and promoting the sustainable development of the environment and economy [8], [9]. ...
Article
Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges. The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems (CPPSs). This paper presents a comprehensive review of some of the latest attack detection and defense strategies. Firstly, the vulnerabilities brought by some new information and communication technologies (ICTs) are analyzed, and their impacts on the security of CPPSs are discussed. Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework, and their features and negative impacts are discussed. Secondly, two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed, and their benefits and drawbacks are discussed. Moreover, two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed. Finally, the trends and challenges in attack detection and defense strategies in CPPSs are provided.
... Resilience is a property of systems that describes their ability to operate during and recover from adverse situations to resume normal operations. Resilience depends on the system's elements, their configuration and interactions, and the surrounding environment [6]. From a regional transmission operator perspective, Chen et al. emphasize the necessity of constructing a robust grid to allow operators to address various contingencies on any given day [7]. ...
Preprint
Full-text available
Electric power grids are critical infrastructure that support modern society by supplying electric energy to critical infrastructure systems. Incidents are increasing that range from natural disasters to cyber attacks. These incidents threaten the reliability of power systems and create disturbances that affect the whole society. While existing standards and technologies are being applied to proactively improve power system reliability and resilience, there are still widespread electricity outages that cause billions of dollars in economic loss annually and threaten societal function and safety. Improving resilience in preparation for such events warrants strategic network design to harden the system. This paper presents an approach to strengthen power system security and reliability against disturbances by expanding the network structure from an ecosystems perspective. Ecosystems have survived a wide range of disturbances over a long time period, and an ecosystem's robust structure has been identified as the key element for its survivability. In this paper, we first present a study of the correlation of ecological robustness and power system structures. Then, we present a mixed-integer nonlinear programming problem (MINLP) that expands the transmission network structure to maximize ecological robustness with power system constraints for an improved ability to absorb disturbances. We solve the MINLP problem for the IEEE 24 Bus Reliability Test System and three synthetic power grids with 200-, 500- and 2000-buses, respectively. Our evaluation results show the optimized power systems have increased the network's robustness, more equally distributed power flows, and less violations under different levels of contingencies.
... A smart grid (SG) known as an intelligent grid, future grid, electrical /power grid, intelligent and intergrid, is considered a remarkable advancement and solution to address the current issues of the electrical power grid in the 20th century [1]. The improvements of the present power systems are moving towards incorporating advanced computing technologies, communication infrastructure, smart meters, and sensors [2]. The SG technology improves the incorporation of different sources of energy generation into one system and accordingly enhances the power generation efficiency [3]. ...
Article
The energy internet (EI) integrated with smart grid (SG) has been a growing and emerging technology that manages and controls towards reliability, security, data integrity, demand response management, cyber-attacks, efficient utility energy service, and protocols. Nevertheless, EI-based SG implementation has several shortcomings, such as scalability, congestion, and pricing, making the entire system vulnerable and complex. Hence, this paper comprehensively reviews the EI concept for utility energy service and demand-side management (DSM) in SG, related issues, and future directions. In line with the matter, this review showcases an inclusive description of EI technology, highlighting architecture, theory, and applications. Besides, the various EI integrated utility services are discussed with regard to cloud-based utility service, one-stop online utility service, short message service-based utility service, future utility service, and affordable utility service. Moreover, the DSM in SG connected with EI environment is explored, covering the resilience of EI architecture, 5G based EI, and EI-based DSM for sustainable consumption. The numerous key issues, problems, and challenges are outlined to identify the existing research gaps. Finally, the review proposes some improvements for future opportunities and developments for EI in utility energy service and DSM in SG. All the critical discussion, analysis, and suggestions would be valuable for the power engineer and researchers to enhance EI-based SG for future sustainable operation and management.
... Several surveys have been proposed for the energy domain. Li, Shahidehpour, and Aminifar (2017) present the application of cybersecurity to the control of distributed power systems; Arghandeh (2016), Haggi (2019), Inderwildi (2020) and Mohebbi (2020) focus on the application of smart grid technologies and CPS to enhance the resilience of the power systems; (Das, 2020) propose a review and analysis of qualitative frameworks and quantitative metrics for studying the resilience of the smart grid; Arghandeh (2016) review the state of the art of reliability modelling methods and the evaluation indexes of urban multi-energy systems. The relevance of CPS and their resilience emerges also from numerous research studies focused on production systems in the emerging scenario of industry 4.0. ...
Article
Cyber-Physical Systems (CPSs) are increasingly more complex and integrated into our everyday lives forming the basis of smart infrastructures, products, and services. Consequently, there is a greater need for their ability to perform their required functions under expected and unexpected adverse events. Moreover, the multitude of threats and their rapid evolution pushes the development of approaches that go beyond pure technical reliability, rather encompassing multi-dimensional performance of a socio-technical system. These dimensions call for the notion of resilience, to be used as a staging area for modelling system performance. While a large number of documents deal with this kind of problem for systems including CPSs, a comprehensive review on the topic is still lacking. The scope of this paper is to survey available literature for understanding to which extent CPSs contribute to system resilience, and to synthetize the approaches developed in this domain. More than 500 documents were reviewed through a protocol based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) review technique. This survey identifies main models and methods categorizing them on the basis of the hazards of interest and their effects on security, privacy, safety and business continuity. It also summarizes main conceptual frameworks and metrics used to assess and compare the resilience capabilities of a system including also CPSs. This cross-domain survey highlights the dominant techno-centric unit of analysis for available literature, still highlighting emerging trends towards more systemic representations of system threats, even socio-technically oriented, and respective modern investigation approaches.
... Specifically, in order to effectively quantify resilience, quantitative metrics are utilized to evaluate these capabilities and dimensions by measuring the impact of different operational resilience and infrastructural enhancement strategies (e.g., grid hardening) on power systems when resident in the different performance phases described. Although a number of studies have presented overviews of resilience [37][38][39][40][41][42][43][44][45][46][47][48], the gaps remain that there are no existing attempts that focus on the comprehensive analysis of quantitative power system resilience metrics (PSRMs). In addition, no attempts exist that provide a framework towards categorization and a review methodology towards quantitative standardization as a baseline to compare the functional effectiveness of PSRMs. ...
Article
Full-text available
Power systems incur considerable operational and infrastructural damages from high impact low probability events such as natural disasters. It therefore becomes imperative to quantify the impact of these disruptive events on power system performance so that adaptive actions can be effectively applied. This impact can be evaluated using resilience metrics which should be able to assess the transitions between the different phases in which a power system resides when subjected to an extreme event. Also, the metrics can aid in the evaluation of the effectiveness of the power system adaptive strategies. However, challenges exist since developed metrics do not proceed with a standardized framework, and due to the vast variety of existing metrics, it becomes ambiguous for researchers and power utilities to find converging information pertinent to their work. In an effort to address these challenges, this paper provides a comprehensive review of quantitative power system resilience metrics which are standardized and evaluated with diverse categorizations. The review methodology employs the Axiomatic Design Process that utilizes the axiomatic design theory and design structure matrix to decompose resilient power system functional requirements into metric design parameters. By integrating the Axiomatic Design Process, we provide a standard for comparison and analysis of the adequacy of reviewed quantitative metrics in power systems resilience quantification, while the categorizations aim to identify the specifications of these metrics. This aids in directing further studies towards resilience requirements that have received less literary attention. In addition, the paper furnishes statistical analysis of reviewed metrics in venues and years of publication by percentage, recurring resilience indicators, and power system levels/stages in which the metrics are applicable. Finally, this paper presents common requirements for resilience quantification, discusses gaps and challenges related to power system resilience metrics as well as implications posed by these challenges, while making recommendations towards filling these gaps, and posing pertinent questions to the power system resilience community.
... The associated deployment of information and communications technologies to enable MGs improves the overall electric power systems' operational performance and reduces its vulnerability to cyber-attacks (Jimada-Ojuolape & Teh, 2020). That is, although MGsdefined as a single controllable entity integrating a potentially large number of supply-side resources in a consistently decentralized wayare generally used as resilient and reliable electricity provision solutions (Das, Munikoti, Natarajan & Srinivasan, 2020), they are vulnerable to cybersecurity-related incidents (Bajwa, Mokhlis, Mekhilef & Mubin, 2019;Cagnano, De Tuglie & Microgrids, 2020;Wang et al., 2018). Thus, it is vital to identify the associated risk factors and cyber vulnerabilities, and subsequently reinforce MGs against physical, communication, and cybersecurity-related threats. ...
Article
Microgrids are inherently subject to a variety of cyber-physical threats due to potential vulnerabilities in their cyber systems. In this context, this paper introduces a cyber-attack-resilient design of a multi-carrier microgrid to avoid the loss of critical loads. The objective of the proposed model is to minimize the total planning cost of multi-carrier microgrids, which incorporates the investment and replacement costs of distributed energy resources, operation and maintenance costs, peak demand charges, emission costs, unserved energy costs, and potential reinforcement costs to handle cyber-physical attacks. Not only is the proposed multi-carrier microgrid planning approach able to determine the optimal size of multi-carrier microgrids, but it also identifies and reinforces the system to handle cyber-physical attacks by serving critical loads. The proposed multi-carrier microgrid planning model is formulated as a mixed-integer programming problem and solved using the GAMS 24.1 software. To evaluate the effectiveness of the proposed integrated resource planning model, it is applied to a real-world industrial park test-case system. Numerical simulations demonstrate the effectiveness of the resilience-oriented multi-carrier microgrid planning model. Importantly, the simulation results indicate the economic viability of multi-carrier microgrids optimized by the proposed model. Also, the model sensitivity of various decision variables has been analyzed.
Article
The digital transformation of power systems into cyber-physical systems (CPSs) is the inevitable trend of modern power systems with the integration of large-scale renewable energy. The in-depth interdependence of cyber and physical spaces leads to more complicated external environments for such cyber-physical power systems (CPPSs) and brings great challenges to the resilience of CPPSs. A resilient CPS imposes strict requirements for its ability to cope with high-impact, low-probability cyber-physical disturbances. To better study the vulnerability and resilience of CPPSs, several representative blackouts from the past two decades are reviewed from the cyber-physical perspective. Inspired by general system theory, this study offers a framework with three key features of a CPPS and presents the three-layer interdependences from facilities to functions. The differences between CPPS resilience and conventional power system resilience are also emphasized. Thereafter, the study discusses the influence of cyber-physical disturbances from natural hazards, cyberattacks, and human-in-the-loop on the resilience of CPPSs. Accordingly, a survey of the state-of-the-art resilience-oriented techniques for CPPS in the face of natural hazards is organized based on quantitative metrics as well as planning and operation attributes. Regarding the resilience against cyberattacks, relevant cutting-edge research is reviewed in terms of prevention, detection, and mitigation strategies. Furthermore, from the cyber-physical-social perspective, the exploitation of social behaviors to inform the design of the physical system and the cyber system to ultimately enhance the resilience of CPPSs is also studied. Based on the findings from this research, the remaining challenges and the broad prospects of cyber-physical resilience enhancement techniques are also discussed.
Article
This paper provides a compressive literature review on the application of complex network theories in the resilience evaluation and enhancement of modern power systems. First, the resilience property is decomposed into structural and operational aspects. On one hand, the structural resilience is explained and reviewed by modeling modern power systems as graphs and analyzing the pertinent static and dynamic characteristics. On the other hand, after converting operational data to certain networks, the operational resilience is investigated throughout the progression of an extreme event, namely, from preventive, corrective, to restorative strategies. Moreover, the discussion on resilience evaluation and enhancement is extended to multilayer networks as modern power systems are increasingly coupled with communication networks and other energy carriers. It is concluded that complex network theories serve as an effective means to comprehending and refining the structural and operational resilience of modern power systems.
Thesis
Full-text available
Microgrids, often synonymous with multi-energy systems, are considered as a viable strategy to provide reliable and cost-effective energy solutions because of their economic, technical, and environmental benefits. Thus, the economic assessment of microgrids expansion, particularly clustered microgrids, under vatious uncertainties is a complex challenge. This dissertation scrutinizes the economic deployment of multi-carrier microgrids by sizing optimally distributed energy resources and identifying the demand response intensity of responsive customers. Herein, two planning-decision framework is proposed. First framework is developed for model with non-linear equation which studies the impact of various uncertainties on multi-carrier microgrid expansion planning as well as designing an emission-neutral multi-carrier microgrid system regarding regulations. The second framework is developed for linear model which is a generic model capable of solving complex models under different circumstances including multi-carrier microgrid expansion regarding demand response programs, multi-carrier microgrid expansion under cyberattacks, deployment of bankable multi-carrier microgrid, and clustered multi-carrier microgrids expansion. The objective is to minimize the system-aggregated planning cost of the multi-carrier microgrid-based system, including the distributed energy resources investment and replacement costs, demand response enabling technology cost, operation cost/benefit, maintenance cost, energy demand shifting cost/benefit, peak demand charge, emission cost, and the expected cost of unserved energy while ensuring the desired levels of reliability and online reserve. The first framework utilizes a decomposition method that unites the genetic algorithm of MATLAB and mixed-integer nonlinear programming model of GAMS software. In contrast, The scecond framework is formulated using mixed-integer linear programming and solved via GAMS platform. Numerical simulation analyses demonstrate the effectiveness of the proposed multi-carrier microgrid expansion planning problem from economic, reliability, environmental, and technical outlooks.
Article
Differentiation of resilience from reliability has been a heated topic ever since the emergence of the former upon the limitation, and as a complement, of the latter, while finding the common ground for both has been scarce. This study first picks out the steady-state performance of both to be the common ground, while differentiating their typical causes, namely, the extreme weather for the resilience threats and the component ageing for the reliability challenges. An original evaluation framework developed earlier for the sole reliability is then extended here towards this common ground to accommodate resilience, becoming the joint reliability and resilience evaluation framework. The joint evaluation framework is built upon the Monte Carlo simulation, which embeds the rolling unit commitment as the system operation module to balance the optimality of operation strategy and the punctuality of condition update, and the forecast module with the machine learning technique for generate varied operation conditions. The proposed evaluation framework that joins resilience with reliability not only has its efficacy validated on the 39-bus system, but also deepens the evaluation by analyzing scenarios created with variating the values of key factors that impact resilience, including the typhoon speed, load factor, restoration time, and typhoon direction. Such a joint reliability and resilience evaluation pioneers as an integrated approach to conduct both evaluations in three aspects, namely, differentiating the causes of reliability and resilience harms and paralleling the challenges of both on system performance, upgrading the existing evaluation methods by applying the rolling mechanism to the operation strategy, and offering an open framework to embed complex functions, such as forecast tools enabled by machine learning and proactive responses for resilience enhancement.
Article
The increased high-impact and low-probability extreme weather events have posed unprecedented impacts on power system operation, and it is necessary to have appropriate methods to analyze the impacts. In this paper, a sequential steady-state security region (SSSR) is proposed to better describe the operational region impacted by sequential weather events, and SSSR is a polytope describing a region, where the operational constraints are satisfied. Based on SSSR with uncertain topology changes because of extreme weather events, a bi-level programming model is proposed. By means of Karush–Kuhn–Tucker conditions, the lower-level optimization model is equivalently transformed into a set of linear constraints, which are included in the upper-level optimization model. System topology scenarios are generated with the Monte Carlo method to avoid the curse of dimensionality caused by numerous uncertain topology scenarios. The generated system topology scenarios are mapped into the binary variables, representing line states, by means of the recursive McCormick (RMC) envelopes. Two test systems validate the proposed model. The results show that the proposed SSSR can well describe the feasible sequential region with regard to extreme weather events.
Preprint
Smart Grid (SG) faces several challenges to efficiently transfer the power generated to power consumers. So, a robust monitoring tool is required to monitor the transmission lines in order to ensure the security of the resource. This power transmission monitoring is a good example of an ultra-reliable low latency application of 5G with the aim to provide quality of service and quality of experience. The primary objective of this study is to design a wireless network for real-time monitoring of transmission lines to take preventive measures. In this paper, we present an Internet of Things enabled real-time transmission line monitoring system comprising wireless, wired, and cellular technologies. The objective is to minimize the time delay at the minimum installation cost of the network. In our proposed model, all the sensors are powered by Renewable Energy Resources (RES) like wind and solar energy, etc. The placement problem is formulated to determine the location of cellular-enabled transmission towers. Moreover, feasible regions are also calculated to show the relationship between time delay and energy consumption. Results show that the proposed model provides efficient solutions and takes less time for data transmission and is more energy-efficient.
Article
Multiple physical failures and severe power disruptions occur in power grid under extreme operation conditions. In this paper, we study power grid resilience and derive quick recovery methods through adjusting the operating modes of available components and reconfiguring the remaining network. The largest amount of power that is available to the loads after reorganizing the remaining undamaged components in the post-disaster stage is identified as an important resilience indicator. An interior point method is firstly used to find the largest amount of power supply (LPS) of fixed topology. The post-disaster network should contain as many available components as possible in order to give the best topological connection. However, disconnecting some undamaged components proactively can further increase the LPS. This phenomenon can be interpreted as the Breass paradox and is effectively a combinatorial network reconfiguration. A double-loop optimization strategy is proposed to achieve the LPS available to the post-disaster network, where the interior point method serves the inner optimization loop and the outer optimization loop generates an optimal topology using a genetic algorithm. Simulation results verify the efficacy of the proposed method in achieving a quick power recovery in extreme events. Our work provides useful advice to power grid operators on how to effectively coordinate available resources after extreme events occur.
Article
The subject of resilience in electrical grids has become more popular among researchers in recent decades due to the rise of worldwide natural disasters such as floods, severe storms, snow, and hailstorms as well as the imposition of high costs resulted from widespread outages. Various methods have been proposed to improve the resilience of electrical grids under different conditions. In each work, the authors have validated their proposed method based on a function or metric they have defined to clarify its effect on improving the resilience of electrical grid. However, to date, there is no standardized metric for assessing the resilience of an electrical grid and providing the possibility to compare the many strategies discussed in different papers. This paper tries to explain the metrics that have been presented in various researches in this regard so far, and it compares these metrics from different aspects in order to determine the most comprehensive metric.
Chapter
In power system, only electric grid means to a vast and variable setup of electrical components that distribute electrical energy from the generating locations to the user end. The components are transmission buses, substations, feeder buses etc. The electric grid is deliberated to be a technological prodigy in handling so many generating units, high megawatts of generating capacity and several miles of transmission lines. However, in recent scenario the electricity disruption like a blackout is very common not in India but in advanced countries like United State of America. A grid would be more efficient when more resiliency is added into the existing electric network and made ready for diffident unavoidable tragedies and natural calamities. Therefore, if some extra powerful features are supplemented to the existing grid, then it becomes a smart grid. The extra powerful features can be advanced control techniques application in grid operation. This will make the existing grid network more efficient, faster in power transmission and self-repair after power disturbances, inexpensive, improved security etc. This chapter presents a discussion on the various challenges in execution of smart grid. After that, some of recent proposed control techniques designed and applied to handle those issues. Various control applications in smart grid are supplemented with appropriate test bench problem and experimental or simulation results.KeywordsSmart gridDefinitionEvolutionChallengesControl technologiesCommunication technologiesCommercial applications
Article
Hydrogen vehicles are expected to play a significant role in realizing zero-carbon transportation. Hydrogen vehicles will be serviced at hydrogen refueling stations, where electrolysis (i.e., the process of using electricity to split water) will be the primary means of local hydrogen production. In that regard, the transportation and power systems will be increasingly interdependent through hydrogen refueling stations, forming a coupled hydrogen-power system (H-P system). In this paper, we propose a graph-based approach for evaluating and enhancing the structural resilience of the H-P system. On the one hand, a graph-based modeling method for the H-P system is proposed based on multilayer network theory, and a resilience metric for the H-P system is developed based on the Laplacian matrix. On the other hand, an optimization model is constructed for designing the interdependency patterns of H-P systems with the resilience goal. Last, numerical experiments are conducted for validating the effectiveness of the proppsed method. We look forward that this paper will provide guidance for harmonizing the planning of hydrogen refueling and power systems, thereby contributing to the large-scale deployment of hydrogen refueling stations.
Article
The integration of advanced Information and Communication Technologies (ICTs) in the conventional electric power grid is evolving into a Cyber-Physical Power System (CPPS). The seamless integration of control, communication, and computing operations allow CPPS to be fully monitored and controlled. Threats, vulnerabilities, and catastrophic attacks will intrude as CPPS monitoring, protection, and control functions advance. For the CPPS to operate safely, securely, and efficiently, sustainable cybersecurity solutions must be developed, and the power grid’s reliability and resilience must be maintained even when exposed to unfavorable network conditions. While more distributed and renewable energy sources are connected to the grid, cybersecurity helps to ensure the supply of electricity is sustainable and of high quality. The validation of such sustainable cybersecurity analysis goes beyond the traditional power grid network analysis, which means that the test should integrate the physical and cyber system behavior and respond to the network attacks. To analyze the cybersecurity and cyberattacks in the practical CPPS, comprehensive and realistic CPPS testbeds are needed. The heterogeneous nature of the CPPS concept urges multidisciplinary testbeds with various functions and capabilities to evaluate the new cyber-attacks, vulnerabilities, and threats in CPPS. Using this CPPS testbed framework, the different types of cyber-attack can be detected, and detection algorithm can be evaluated, and helps to enhance the development of sustainable cybersecurity defenses for realistic CPPS environment with the increasingly dense integration of distributed energy resources (DERs). This Part-I paper review the CPPS testbeds in the view of the physical power system layer, sensing layer, communication layer, control layer, application layer, test platforms, and research goals with the fusion of cyber and physical systems. In addition, this review presented an overview, structure, and application-based evaluation of existing testbeds from the industry and institutions. The various research areas in CPPS are reviewed first to show the research trends on different aspects of CPPS which have gained significant attention in the past decade. The necessity of testbeds for cyberattacks and sustainable cybersecurity analysis in CPPS are then described. Finally, the NIST framework for CPS, CPPS domains, and research areas are presented. Further the Part-II paper will review the classification, overview, and assessment of CPPS testbeds.
Article
Full-text available
The traditional power network has now evolved into the smart grid, where cyber technology enables automated control, greater efficiency, and improved stability. However, this integration of information technology exposes critical infrastructure to potential cyber-attacks. Furthermore, the interdependent nature of the grid’s composite information and operational technology networks means that vulnerability extends across interconnected devices and systems. Therefore, a DDoS (Distributed Denial-of-Service) attack, which is relatively easy to deploy but potentially highly disruptive, can be used strategically against the smart grid with particularly egregious results. In this paper, we take inspiration from epidemiological modelling to propose a compromise propagation model, alongside a behavioural DDoS model, to explore how dependencies between the grid’s networks might influence the scale and impact of DDoS attacks. We found that the internal connectedness of a network amplifies the received impact of failures in an external network on which it is dependent. Furthermore, testing showed that alongside attack force, attack duration influences recovery times, due to both the quantity of resources consumed and the time needed to accumulate recoveries. The models were validated against simulations conducted with cyber-security providers L7 Defense, showing our approach to be a viable companion or alternative to traditional graph-based dependency models.
Article
Resiliency has been studied in the power and water systems separately. Often the resiliency study is not so comprehensive as to understand interdependent, integrated water and power systems. This research outlines the relevant factors necessary to understand and advance quantification of such integrated systems. It also presents a review of integrated water-power systems resiliency. Based on literature survey and identification of challenges, the authors present quantification and computational steps needed to understand integrated water-power systems resiliency. A conceptual framework is proposed to quantify integrated water-power system resiliency. Finally, the authors presented an opportunity for improved water and power system resilience.
Article
Affected by climate change, extreme weather events are occurring with increasing frequency and severity, resulting in more and more blackouts. Thus, resilience enhancement is drawing wider attention from academia and industry. Nevertheless, most of the existing studies ignore the resilience enhancement operational strategies against the extreme-weather-triggered cascading failures. To solve these problems, this paper proposes a sequentially proactive operational strategy to enhance resilience against extreme-weather-triggered cascading failures. Firstly, due to the difference between the time scales of extreme weather events and cascading failures, the outage process under extreme weather conditions is regarded as a double-time-dimension process, including the weather disaster and cascading failures. Besides, given that extreme weather and cascading failures are random, the random scenarios sampling method is utilized to simulate the double-time-dimension outage process. Further, customized double-time-dimension process constraints are introduced to the proposed model to represent the correlation between extreme weather events and cascading outages. Meanwhile, by regarding the probability of outages scenarios as the weight of each objective, the proposed model can be transformed into mixed-integer linear programming. Numerical studies validate the feasibility and effectiveness of the proposed method. The results demonstrate that the proposed strategies can prevent extreme weather from triggering cascading failures and reduce the size of blackouts, to enhance the resilience performance of the power system. The findings can provide some meaningful insights for system operators to adopt resilience enhancement measures against the extreme-weather-triggered cascading failures.
Chapter
In recent years, rapid advances in different energy technologies and emerging new intelligent systems have driven energy networks to undergo an unprecedented deformation. In the path of this transformation, some critical challenges have appeared regarding the handling of a large number of new smart devices, ensuring their fit with society's requirements, raising dependences among multifarious energy grids, ever‐increasing in multi‐vector energy consumption, etc. One of the key phases of this evolution is related to the huge need for growing the penetration of renewable energy resources (RERs) in response to an unacceptable range of pollution created by conventional energy suppliers. However, how the current potential of an upgraded system can allow for the exploitation of numerous RERs and effectively handle their presence is a key challenge requiring innovative solutions and practical strategies. The modernization of energy networks addresses the need for building a reliable, secure, resilient, and intelligent network that enables the system with a full/high share of RERs for sustainability while allowing end‐users to benefit from more and greater diverse market services and opportunities by actively participating in the energy grid's interactions. This chapter clarifies what are the characteristics of future modern energy networks and why grid modernization is essential for the interdependent structure of networks that are going to be engaged with a large number of stochastic clean energy production devices. The related challenges and opportunities are also targeted to be covered to give a clear overview for the future modern multi‐carrier energy grid.
Article
Cyber–physical systems (CPSs) are confronted with major problems, such as high proportions of renewable energy penetration and frequent extreme events, which severely restrict the stability of power systems. The key to solve these problems is the construction of a resilient power system. This study expounds on the development background and current situation of resilient CPSs from the perspectives of emerging technology and appropriate energy policy. Based on the foregoing, the importance of modeling in resilience research is highlighted, and the selection principles of different modeling methods are discussed. In addition, the optimal control strategies and methods applied to respond to extreme events in a three–stage power system are summarized, highlighting the application of optimal control strategies or emerging technologies for investigating simulations and actual systems. The study also focuses on the current development status of renewable energy and how variable renewable energy can reinforce power system resilience. Finally, in view of the gaps in the current CPS research, the key problems that must be resolved by future CPSs are identified.
Article
Full-text available
Electric mobility has become increasingly prominent, not only because of the potential to reduce greenhouse gas emissions but also because of the proven implementations in the electric and transport sector. This paper, considering the smart grid perspective, focuses on the financial and economic benefits related to Electric Vehicle (EV) management in Vehicle-to-Building (V2B), Vehicle-to-Home (V2H), and Vehicle-to-Grid (V2G) technologies. Vehicle-to-Everything is also approached. The owners of EVs, through these technologies, can obtain revenue from their participation in the various ancillary and other services. Similarly, providing these services makes it possible to increase the electric grid’s service quality, reliability, and sustainability. This paper also highlights the different technologies mentioned above, giving an explanation and some examples of their application. Likewise, it is presented the most common ancillary services verified today, such as frequency and voltage regulation, valley filling, peak shaving, and renewable energy supporting and balancing. Furthermore, it is highlighted the different opportunities that EVs can bring to energy management in smart grids. Finally, the SWOT analysis is highlighted for V2G technology.
Article
In recent years, the increased frequency of natural hazards has led to more disruptions in power grids, potentially causing severe infrastructural damages and cascading failures. Therefore, it is important that the power system resilience be improved by implementing new technology and utilizing optimization methods. This paper proposes a data‐driven spatial distributionally robust optimization (DS‐DRO) model to provide an optimal plan to install and dispatch distributed energy resources (DERs) against the uncertain impact of natural hazards such as typhoons. We adopt an accurate spatial model to evaluate the failure probability with regard to system components based on wind speed. We construct a moment‐based ambiguity set of the failure distribution based on historical typhoon data. A two‐stage DS‐DRO model is then formulated to obtain an optimal resilience enhancement strategy. We employ the combination of dual reformulation and a column‐and‐constraints generation algorithm, and showcase the effectiveness of the proposed approach with a modified IEEE 13‐node reliability test system projected in the Hong Kong region.
Chapter
There have been numerous efforts to define, measure, and analyze resilience of smart grids. This chapter presents a comprehensive review of resilient smart-grid systems. It describes the issues and challenges of smart-grid to improve the resiliency. Moreover, it analyzes the Smart Grid Resilience Matrices and different methods for resiliency improvement.
Article
Power systems are the backbone of modern society, but high-impact and low-probability natural disasters pose unprecedented challenges to power systems in recent years. Power systems consist of generation, networks, and loads, which have their own characteristics. Different sectors need to various responses and strategies in the face of natural disasters. This paper presents a systematic review on power system resilience from four dimensions: (1) Impact analysis. In this dimension, typical disaster-related power outages are quantitatively analyzed, and the impacts of the events on the power systems from the perspective of generation/networks/loads are qualitatively analyzed. (2) Impact quantification. The quantification metrics of the impacts of different events on generation, networks, and loads are systematically reviewed. These systematical quantification metrics are essential prerequisites for resilience improvements. (3) Resilience improvement. Adaptation options from the component-level perspectives are first introduced, and then the optimal strategies from the system-level perspectives are presented. Various power sources have different power production characteristics against different kinds of natural disasters, and coordinated scheduling of different power sources is an effective means to improve generation resilience. System networks are important to bridge generation and loads, and they need to have strong resilience in the face of varying and uncertain impacts caused by natural disasters with system hardening, reconfiguration implementation, microgrid formulation, etc. Loads are becoming more smart and responsive, and these smart/responsive loads have outstanding potential regulating abilities for improving power system resilience. (4) Future research directions with regard to power system resilience improvements are discussed.
Article
With the development of the Internet of Things, the interdependency between the physical system and the cyber system becomes intense and improves operational efficiency. But the interdependency also increases the risk of failure propagation. The resilience of the cyber–physical system is important for security facing extreme events. Based on complex network theory, a weighted multiplex network model is proposed to realize the unified modeling of the power system and communication system. In addition, the cascading failure mechanism in the cyber–physical power system is built based on power dispatch and information transmission mechanisms in the actual scenario. Then, spectral metrics are introduced to evaluate structural resilience from a global perspective. Finally, simulations of cascading failure are performed to verify the effectiveness of spectral metrics on resilience evaluation. The proposed model and metrics provide a convenient approach to quantifying the resilience of an interdependent system. The results of resilience evaluation can be used as a reference for system structure planning.
Article
Recently, the resilient operation of distribution networks has attracted attention owing to the considerable growth in natural disasters. After isolating the faulted or damaged areas, restoring the intact parts is challenging. This can be exacerbated by high penetration of renewable resources. During the restoration, the access to available resources is limited by time, production capacity, or stored energy. Therefore, a balance must be made while considering load criticality. Accordingly, a new distribution restoration process is proposed in this paper to overcome these challenges while considering switching sequence. To be accounted for real-world cases, a new binary-based segmentation model is developed for multiple-transformer bus loads. Besides, a novel bus load supply prioritization is proposed to overcome the drawbacks of previous methods which have used weighting factors in the objective function. Also, a new energy-based objective function is developed, taking the degree of energy available from distributed generation and storage resources into account. Besides benefiting from network reconfiguration and stationary energy storage systems, integration of modern storage-integrated soft open points is also modeled and considered. The model is validated through a case study, demonstrating its functionality to deal with real-world cases with load priority steps, multiple-transformer bus loads, and limited energy access.
Article
Given the complexity of power grids, the failure of any component may cause large-scale economic losses. Consequently, the quick recovery of power grids after disasters has become a new research direction. Considering the severity of power grid disasters, an improved power grid resilience measure and its corresponding importance measures are proposed. The recovery priority of failed components after a disaster is determined according to the influence of the failed components on the power grid resilience. Finally, based on the data from the 2019 Power Yearbook of each city in Shandong Province, China, the power grid resilience after a disaster is analyzed for two situations, namely, partial components failure and failure of all components. Result shows that the recovery priorities of components with different importance measures vary. The resilience evaluations under different repair conditions prove the feasibility of the proposed method.
Technical Report
Full-text available
This report has been written for the Department of Energy's Office of Electricity Delivery and Energy Reliability to support the Office of Energy Policy and Systems Analysis in their writing of the Quadrennial Energy Review in the area of energy resilience. The topics of measuring and increasing energy resilience are addressed, including definitions, means of measuring, and analytic methodologies that can be used to make decisions for policy, infrastructure planning, and operations. A risk-based framework is presented which provides a standard definition of a resilience metric. Additionally, a process is identified which explains how the metrics can be applied. Research and development is articulated that will further accelerate the resilience of energy infrastructures.
Conference Paper
Full-text available
The emerging proliferation of information and communication technology throughout the electricity grid enables technologies, such as Demand Response (DR) schemes, eventually creating a Smart Grid. This development is expected to produce effective DR systems where consumers get reduced electricity costs while their utility companies reduce their costs of services due to peak demand reductions with increasing efficiency. False data injection/data integrity attacks on these systems can potentially result in sub-optimal solutions for a majority of users while a potentially malicious subset of users receives benefits. Furthermore, such attacks might also affect the resilience of the Smart Grid. In this paper, we depicted a novel high impact FDIA and evaluate how an adversary can use a targeted strategic data integrity attack in order to get financial benefits through a real-time based pricing scheme. Our experimental results show how a small percentage of overall demand increase can lead to a significant cost reduction for the adversary. Based on our results we elaborate on the significance of this type of false data injection attacks on general distributed DR schemes.
Article
Full-text available
This paper studies the performance and resilience of a linear cyber-physical control system (CPCS) with attack detection and reactive attack mitigation in the context of power grids. It addresses the problem of deriving an optimal sequence of false data injection attacks that maximizes the state estimation error of the power system. The results provide basic understanding about the limit of the attack impact. The design of the optimal attack is based on a Markov decision process (MDP) formulation, which is solved efficiently using the value iteration method. We apply the proposed framework to the voltage control system of power grids and run extensive simulations using PowerWorld. The results show that our framework can accurately characterize the maximum state estimation errors caused by an attacker who carefully designs the attack sequence to strike a balance between the attack magnitude and stealthiness, due to the simultaneous presence of attack detection and mitigation. Moreover, based on the proposed framework, we analyze the impact of false positives and negatives in detecting attacks on the system performance. The results are important for the system defenders in the joint design of attack detection and mitigation to reduce the impact of these attack detection errors.Finally, as MDP solutions are not scalable for high-dimensional systems, we apply Q-learning with linear and non-linear (neural networks based) function approximators to solve the attacker’s problem in these systems and compare their performances.
Conference Paper
Full-text available
In smart distribution systems, it is expected that there will be an inherent coupling of real time pricing and overall demand. For example, active consumers may respond to changes in electricity pricing by adjusting their consumption while the aggregator/distribution system operator (DSO) may change pricing in real time to influence consumer behavior to obtain a more favorable load profile. This interaction between the consumer and aggregator/DSO is typically enabled by a cyber-infrastructure that is prone to attack. In this paper, the impact of real time pricing attacks on the demand dynamics is quantified. Specifically, a pricing policy is considered wherein a discrete set of prices that is based on the overall demand range is used by the aggregator. The demand in turn is based on pricing and its dynamics is quantified. When an attacker manipulates the real-time prices, this leads to unwarranted changes in demand which could possibly lead to undesirable operating conditions. The impact of such an attack on the error associated with demand is derived and the stability of the error dynamics is investigated. Finally, using simulations, the proposed pricing and demand model along with the error stability results are validated.
Conference Paper
Full-text available
In smart distribution systems, it is expected that there will be an inherent coupling of real time pricing and overall demand. For example, active consumers may respond to changes in electricity pricing by adjusting their consumption while the aggregator/distribution system operator (DSO) may change pricing in real time to influence consumer behavior to obtain a more favorable load profile. This interaction between the consumer and aggregator/DSO is typically enabled by a cyber-infrastructure that is prone to attack. In this paper, the impact of real time pricing attacks on the demand dynamics is quantified. Specifically, a pricing policy is considered wherein a discrete set of prices that is based on the overall demand range is used by the aggregator. The demand in turn is based on pricing and its dynamics is quantified. When an attacker manipulates the real-time prices, this leads to unwarranted changes in demand which could possibly lead to undesirable operating conditions. The impact of such an attack on the error associated with demand is derived and the stability of the error dynamics is investigated. Finally, using simulations, the proposed pricing and demand model along with the error stability results are validated.
Article
Full-text available
This paper deals with modelling the dynamic resilience of rail passenger transport networks affected by large-scale disruptive events whose impacts deteriorate the networks’ planned infrastructural, operational, economic, and social-economic performances represented by the selected indicators. The indicators of infrastructural performances refer to the physical and operational conditions of the networks’ lines and stations, and supportive facilities and equipment. Those of the operational performances include transport services scheduled along particular routes, their seating capacity, and corresponding transport work/capacity. The indicators of economic performances include the costs of cancelled and long-delayed transport services imposed on the main actors/stakeholder involved—the rail operator(s) and users/passengers. The indicators of social-economic performances reflect the compromised accessibility and consequent prevention of the user/passenger trips and their contribution to the local/regional/national Gross Domestic Product. Modeling resulted in developing a methodology including two sets of analytical models for: (1) assessing the dynamic resilience of a given rail network, i.e., before, during, and after the impacts of disruptive event(s); and (2) estimation of the indicators of particular performances as the figures-of-merit for assessing the network’s resilience under the given conditions. As such, the methodology could be used for estimating the resilience of different topologies of rail passenger networks affected by past, current, and future disruptive events, the latest according to the “what-if” scenario approach and after introducing the appropriate assumptions. The methodology has been applied to a past case—the Japanese Shinkansen HSR network affected by a large-scale disruptive event—the Great East Japan Earthquake on 11 March 2011.
Article
Full-text available
Energy resiliency has been thrust to the forefront by recent severe weather events and natural disasters. Billions of dollars are lost each year due to power outages. This article highlights the unique value renewable energy hybrid systems (REHS), comprised of solar, energy storage, and generators, provide in increasing resiliency. We present amethodology to quantify the amount and value of resiliency provided by REHS, and ways to monetize this resiliency value through insurance premium discounts. Acase study of buildings inNewYork City demonstrates howimplementing REHS in place of traditional backup diesel generators can double the amount of outage survivability, with an added value of $781,200. For a Superstorm Sandy type event, results indicate that insurance premium reductions could support up to 4% of the capital cost of REHS, and the potential exists to prevent up to $2.5 billion in business interruption losses with increased REHS deployment.
Article
Full-text available
Natural disasters such as hurricanes damage power distribution systems by low probability- high impact events. Other infrastructures such as water networks will be disrupted due to their dependency on the power network. In this situation, a city or region experiences critical conditions. In this paper, a new resilience index based on social welfare concept is presented to decrease unserved loads, restore the distribution system rapidly and decrease the dependency of water network operation to power network failures. The new resilience index is optimized with effective strategies including: upgrading distribution poles, DG placement with different capacities and distribution system automation. The problem is formulated as a stochastic two-stage optimization. The first-stage decisions are the number of each resilience improvement strategy limited to a predetermined budget. Genetic algorithm is applied to solve the first stage. The objective of the second stage is maximizing the social welfare which is solved by an innovative approach. Numerical simulations are performed on the IEEE 33-bus radial distribution system and designed water network related to it. The results demonstrate the effectiveness of the proposed method.
Article
Full-text available
Purpose of Review In this paper, we study the literature on cyber-physical security of electrical power systems. The paper is intended to address the security strengths and weaknesses of the electrical power systems against malicious attacks. Recent Findings The concept of holistic resilience cycle (HRC) is introduced to improve cyber-physical security of electrical power systems. HRC is a systematic view to the security of the power systems, characterized by its four stages as closely interconnected and explicable only by reference to the whole. HRC includes four stages of prevention and planning, detection, mitigation and response, and system recovery. Summary Power systems are evolving from traditional settings towards more autonomous and smart grids. Cyber-physical security is critical for the safe and secure operations of the power systems. To achieve a higher security level for power systems, the research community should follow a systematic approach and consider all stages of the holistic resilience cycle in addressing security problems of the power systems.
Article
Full-text available
Resilience of engineered systems is measured by the ability to anticipate, prepare for, recover, learn, and improve from an external disturbance regime that comprises of a series of chronic low-intensity and infrequent acute shocks, which disrupt functionality. Here, we present a new systems-level model for coupled technological systems, which provide functionality, and social systems in charge of management. Each system is characterized by a single, aggregated, dynamic state variable, namely (1) critical service deficit, representing services/functionality not provided by the technological system to match demands, and (2) adaptive capacity, representing total resources available to the managing/social institutions to maintain and repair critical services. These coupled systems are subjected to an external stochastic disturbance regime (Poisson shocks), and temporal perturbations in the two state variables are simulated. We use this “toy” model to simulate four hypothetical scenarios to illustrate likely coupled system temporal trajectories and shifts between a desirable (full service) and an undesirable (limited service) regime or complete system collapse (no service, no adaptive capacity). We also present several quantitative approaches to assess time series data and examine coupled systems dynamics. Resilience of the coupled systems for coping with and recovering from service losses is a dynamic property, contingent on system parameters that define the initial conditions before the shocks and recovery, and the frequency and magnitude of shocks.
Article
Full-text available
In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retail rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. The model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.
Article
Full-text available
The electricity infrastructure is a critical lifeline system and of utmost importance to our daily lives. Power system resilience characterizes the ability to resist, adapt to, and timely recover from disruptions. The resilient power system is intended to cope with low probability, high risk extreme events including extreme natural disasters and man-made attacks. With an increasing awareness of such threats, the resilience of power systems has become a top priority for many countries. Facing the pressing urgency for resilience studies, the objective of this paper is to investigate the resilience of power systems. It summarizes practices taken by governments, utilities, and researchers to increase power system resilience. Based on a thorough review on the existing metrics system and evaluation methodologies, we present the concept, metrics, and a quantitative framework for power system resilience evaluation. Then, system hardening strategies and smart grid technologies as means to increase system resilience are discussed, with an emphasis on the new technologies such as topology reconfiguration, microgrids, and distribution automation; to illustrate how to increase system resilience against extreme events, we propose a load restoration framework based on smart distribution technology. The proposed method is applied on two test systems to validify its effectiveness. In the end, challenges to the power system resilience are discussed, including extreme event modeling, practical barriers, interdependence with other critical infrastructures, etc.
Article
Full-text available
Boosting the resilience of power systems is one of the core requirements of smart grid. In this paper, an integrated resilience response framework is proposed, which not only links the situational awareness with resilience enhancement, but also provides effective and efficient responses in both preventive and emergency states. The core of the proposed framework is a two-stage robust mixed-integer optimization model, whose mathematical formulation is presented in this paper as well. To solve the above model, an algorithm based on the nested column-and-constraint generation decomposition is provided, and computational efficiency improvement techniques are proposed. Preventive response in this paper considers generator re-dispatch and topology switching, while emergency response includes generator re-dispatch, topology switching and load shedding. Several numerical simulations validate the effectiveness of the proposed framework and the efficiency of the solution methodology. Key findings include: 1) in terms of enhancing power grid resilience, the integrated resilience response is preferable to both independent preventive response and independent emergency response; 2) the power grid resilience could be further enhanced by utilizing topology switching in the integrated resilience response.
Article
Full-text available
Large scale power failures induced by severe weather have become frequent and damaging in recent years, causing millions of people to be without electricity service for days. Although the power industry has been battling weather-induced failures for years, it is largely unknown how resilient the energy infrastructure and services really are to severe weather disruptions. What fundamental issues govern the resilience? Can advanced approaches such as modeling and data analytics help industry to go beyond empirical methods? This paper discusses the research to date and open issues related to these questions. The focus is on identifying fundamental challenges and advanced approaches for quantifying resilience. In particular, a first aspect of this problem is how to model large-scale failures, recoveries and impacts, involving the infrastructure, service providers, customers, and weather. A second aspect is how to identify generic vulnerability (i.e., non-resilience) in the infrastructure and services through large-scale data analytics. And, a third is to understand what resilience metrics are needed and how to develop them.
Article
In this paper, a novel distributed finite-time control scheme is proposed to enhance the resilience and frequency stability of smart grid by utilizing a distributed energy storage system (DESS). The proposed entire framework integrates the traditional governor-based control and excitation control with DESS-based control. The design objectives also address some practical challenges including communication delay, limited DESS capacity or absent DESS, and voltage dynamic and denial-of-service (DoS) attacks. The proposed excitation control can enhance the performance of other existing approaches for utilizing DESS. The IEEE 68-bus power system and East China Power Grid are used to validate the effectiveness of the proposed control framework in enhancing the frequency stability and resilience of smart grid.
Article
Technological advancements in today’s electrical grids give rise to new vulnerabilities and increase the potential attack surface for cyber-attacks that can severely affect the resilience of the grid. Cyber-attacks are increasing both in number as well as sophistication and these attacks can be strategically organized in chronological order (dynamic attacks), where they can be instantiated at different time instants. The chronological order of attacks enables us to uncover those attack combinations that can cause severe system damage but this concept remained unexplored due to the lack of dynamic attack models. Motivated by the idea, we consider a game-theoretic approach to design a new attacker-defender model for power systems. Here, the attacker can strategically identify the chronological order in which the critical substations and their protection assemblies can be attacked in order to maximize the overall system damage. However, the defender can intelligently identify the critical substations to protect such that the system damage can be minimized. We apply the developed algorithms to the IEEE-39 and 57 bus systems with finite attacker/defender budgets. Our results show the effectiveness of these models in improving the system resilience under dynamic attacks.
Article
A novel delay-adaptive control strategy is proposed to enhance the smart grid resilience and transient stability which combines the traditional governor-based control with the distributed energy storage system (DESS) control. In this paper, the communication delay is fully considered in the development of the controller, where the distributed control mode would convert to the decentralized control mode automatically in the case of large communication delay. Meanwhile, the effect from input delay of the DESS-based control is solved by Artstein transformation, which is firstly used in the transient stability control of the time delayed power system to reduce the time delayed state equation of power system into the delay-free state equation of power system. The stability of power system under the proposed control scheme is ensured based on the reduced power system model to improve the input delay characteristics of power system. The delay-adaptive governor-based control also accommodates to the case of a generator bus without any associated DESS. Meanwhile, the designed objectives also address some practical challenges, including limited DESS capacity and sample noise.
Article
Recent extreme weather events have emphasized the need for new methods and metrics to assess the power system resilience in response to high-impact low-probability (HILP) events. Microgrids (MGs) have been instrumental in such occasions for maintaining the power supply continuity to local customers. This paper provides a quantitative framework for assessing the MG resilience in response to HILP windstorms. The proposed framework jointly employs fragility curves of overhead distribution branches and windstorm profile to quantify the degradation in the MG performance (particularly supplied load in this work). The proposed analytical method is simple and computationally efficient which offers a quick means for getting knowledge about adverse impacts of an approaching windstorm and taking preventive measures accordingly. A set of normalized metrics is defined which provides a comparable tool for assessing the resilience in various operating conditions and power systems. The impacts of restorative actions, the system reinforcement, and the event severity on resilience curves and metrics are also investigated. The effectiveness of the proposed approach in response to an extreme windstorm is examined on a real-scale MG test bed.
Article
The increasingly frequent natural disasters highlight the necessity of improving power system resilience. This paper proposes a hierarchical energy management framework based on multi-microgrids for resilience enhancement. According to the framework, when power supply from the main grid is interrupted, the microgrids go into isolation mode and optimally sustain the power supply through a two-stage scheme. In the first stage, each microgrid reschedules its available resources to minimize the load curtailment and operation cost using the rolling horizon optimization. A demand-side management method based on load classification is designed for isolated microgrids. In the second stage, the microgrids with surplus power capacities export power to support those microgrids with load curtailment. In doing so, a consensus algorithm is applied for microgrids distributed communication to determine the power exchange plan. The optimization model is formulated as a mix-integer linear programming (MILP) problem and can be readily solved by commercial software. Numerical results demonstrate the effectiveness of the proposed model in improving the resilience.
Article
Coupled infrastructure systems and complicated multihazards result in high level of complexity and difficulty to assess and improve the infrastructure system resilience. With a case study of Greater Toronto Area energy system (including electric, gas, and oil transmission networks), an approach to analysis of multihazard resilience of interdependent infrastructure system is presented in the article. Integrating network theory, spatial and numerical analysis methods, the new approach deals with the complicated multihazard relations and complex infrastructure interdependencies as spatiotemporal impacts on infrastructure systems in order to assess the dynamic system resilience. The results confirm that the effects of sequential hazards on resilience of infrastructure (network) are more complicated than the sum of single hazards. The resilience depends on the magnitude of the hazards, their spatiotemporal relationship and dynamic combined impacts, and infrastructure interdependencies. The article presents a comparison between physical and functional resilience of electric transmission network, and find functional resilience is always higher than physical resilience. The multiple hazards resilience evaluation approach is applicable to any type of infrastructure and hazard and it can contribute to the improvement of the infrastructure planning, design, and maintenance decision making.
Article
One of the key elements of any community or facility is the integrated energy system (IES) which consists of utility power plants, distributed generation systems, and building heating and cooling systems. Assessing the sustainability of an IES would be of great value to decision-making relevant to design, future growth planning, and operation of such systems. This paper addresses one of the basic issues in this regard, i.e. resilience assessment and quantification of IES. A new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems is proposed in this study. Through modeling of system response to potential internal and external failures (called failure modes) during different operational temporal periods (such as different diurnal and seasonal periods of the year), the proposed methodology quantifies resilience of the system based upon loss in the services which the system is designed to deliver. A three-dimensional matrix, called Loss Matrix, is introduced whose elements represent the undelivered system services under different scenarios, i.e. combinations of failure modes and different operational temporal periods. Assigning monetary penalty costs to such losses and including them in the objective function of an optimization model of the entire system allows the three-dimension loss matrix to be reframed into a two-dimensional Consequence Matrix where individual elements represent the imposed penalty costs to the system stakeholders due to undelivered services and/or non-optimal system performance. Normalizing the individual elements results in the Resilience Matrix of the system for different scenarios. The developed methodology is illustrated for IES of a large office building serves to satisfy critical and noncritical electrical, heating, and cooling loads. The resilience assessment framework proposed in this paper would serve as a mean to identify critical components of a particular IES, thereby facilitating resilient design and operation, and also to evaluate cost-effective resilience enhancement strategies.
Article
We are increasingly witness to the enormous security problems that cyber-physical control systems have and their susceptibility to certain types of attacks. An attractive way to coordinate the situation and ensure resilience in lineal times could be through redundancy-based restoration mechanisms. For this reason, in this article, we present a network infrastructure based on three layers, where the redundant support is primarily concentrated on a fog-based structure to protect a specific subset of cyber-physical control devices. The specification of the context and the abstract construction of the approach include a set of conceptual theories related to structural controllability, power dominance, supernode, and opinion dynamics, where the validation of the approach is subject to a practical analysis based on two threat case studies.
Article
Enhancing the resilience of infrastructure systems is critical to the sustainability of the society against multiple disruptive events. This paper develops an approach for allocating restoration resources to enhance resilience of interdependent infrastructure systems. According to Inoperability Input-Output Model, a resilience metric for infrastructure systems is developed, in which the performance loss of infrastructure systems resulting from a disruptive event is measured in economic loss and inoperability. Model for determining the optimal infrastructure restoration resources allocation is proposed with the objective of maximizing resilience. Infrastructure interdependence is modeled by the Dynamic Inoperability Input-Output Model (DIIM), which is an accepted economic model for describing the interconnected relationship of industry sectors. To investigate the utility of the restoration resource allocation model, numerical analysis is conducted with an example derived from the data provided by the US Bureau of Economic Analysis. The results show that: (1) the optimal restoration resource allocation varies with the resource budget; (2) for a specific disruptive event, there exists an optimal resource budget which can minimize the sum of restoration cost and the performance loss of infrastructure system; and (3) the significance of factors such as initial inoperability of infrastructure systems on the optimal allocation. The proposed model can assist the decision makers in (i) better understand the effects of resource allocation, and (ii) deciding which allocation strategies should be used following a disruptive event.
Article
In this study, a significant literature review on peak load shaving strategies has been presented. The impact of three major strategies for peak load shaving, namely demand side management (DSM), integration of energy storage system (ESS), and integration of electric vehicle (EV) to the grid has been discussed in detail. Discussion on possible challenges and future research directions for each type of the strategy has also been included in this review. For the energy storage system, different technologies used for peak load shaving purpose, which include their methods of operation and control have been elaborated further. Finally, the sizing of the ESS storage system is discussed. For the demand side management system, various management methods and challenges associated with DSM implementation have been thoroughly explained. A detailed discussion on the electric vehicle strategy has also been included in the review, which considers the integration, control and operation techniques for implementing the peak load shaving.
Article
This paper investigates the problem of secure state estimation for cyber-physical systems (CPSs) modeled by continuous or discrete-time linear systems when some sensors are corrupted by an attacker. A novel state observer is proposed with adaptive switching mechanism. Attack tolerance principle is established based on adaptively truncating the injection channels of attacks. To implement it, a switching function matrix is introduced into the observer design. Driven by a well-defined performance index, the switching function matrix automatically reaches and remains in the desired entry mode and turns off the input channels of attacks. Based on the equivalence between s-strong detectability of the observation error system and 2s-sparse detectability of the original system, the observation error system is proven to be asymptotically stable even under the cyber attacks. Compared with the existing complex static batch optimization algorithms, the proposed adaptive observer can be derived only by off-line solving a set of simple linear matrix inequalities (LMIs). Simulation examples are given to illustrate the estimation performance and the computational efficiency of the proposed method
Article
The resilience of infrastructure networks is an increasingly important consideration in infrastructure planning and risk management. One aspect of resilience-based planning is determining which components in the network are most important to the resilience of the network. This work makes use of a resilience-based component importance measure, the resilience worth, and proposes to model this measure under uncertainty using a Bayesian kernel technique. Such a technique can be useful in modeling component importance as it enables the probability distribution for the importance measure to be updated using data and prior information with a Bayesian kernel model. The proposed approach is applied to study the importance of locks and dams along the Mississippi River Navigation System. The highest predictive overall accuracy is achieved with a uniform prior distribution, and using the posterior distribution and a multicriteria decision analysis technique, we identify the five locks and dams with the largest impact on the system's resilience.
Article
There is huge expectation from smart power grid to provide sustainable energy services using bi-directional flow of data and power enabled by advanced information, communication and control infrastructure. An important element of such a smart grid is prosumers i.e. the consumers who also produce and share surplus energy with grid and other users. Prosumers are not only an important stakeholder of the future smart grids but also have a vital role in peak demand management. Therefore, it is needed to investigate and review the Prosumers based Energy Management and Sharing (PEMS) along with associated challenges. It will help in understanding and analyzing the impact of prosumers in future smart grids. In order to achieve these objectives, this paper presents a comprehensive review of PEMS in smart grid environment and associated impact on power system reliability and energy sustainability. The process of energy sharing among prosumers involves two key elements: information and communication technologies and optimization techniques. These two elements have been discussed in detail to cover the PEMS implementation requirements. The relevant communications technologies presented in the paper include wired, wireless, short and long range options while linear and nonlinear optimization techniques, in context of PEMS, are described. Various technologies, methodologies and mechanisms adopted for PEMS are comprehensively discussed in order to enhance readers' intuition. Challenges and issues faced by prosumer communities and energy sharing have also been elaborated in detail.
Article
Security of power supply is a crucial element of energy system planning and policy. However, the value that society places on it is not clearly known. Several previous studies estimate the cost of electricity interruptions for individual European Union (EU) Member States – as the Value of Lost Load (VoLL). In this paper, we use a production-function approach to estimate the average annual VoLL for households in all twenty-eight EU Member States. This is the first time that a unified approach has been applied for a single year across the EU. VoLL is further presented on an hourly basis to better understand the impact of the time at which the interruption occurs. Finally, we analyse the impact of ‘substitutability factor’ – the proportion of household activities that are electricity-dependent – on the VoLL. Results from this study show that the differences in VoLL between EU Member States is signif