Path Restoration Research Articles

Microgrids for Service Restoration to Critical Load in a Resilient Distribution System

Microgrids can act as emergency sources to serve critical loads when utility power is unavailable. This paper proposes a resiliency-based methodology that uses microgrids to restore critical loads on distribution feeders after a major disaster. Due to limited capacity of distributed generators (DGs) within microgrids, dynamic performance of the DGs during the restoration process becomes essential. In this paper, the stability of microgrids, limits on frequency deviation, and limits on transient voltage and current of DGs are incorporated as constraints of the critical load restoration problem. The limits on the amount of generation resources within microgrids are also considered. By introducing the concepts of restoration tree and load group, restoration of critical loads is transformed into a maximum coverage problem, which is a linear integer program (LIP). The restoration paths and actions are determined for critical loads by solving the LIP. A 4-feeder, 1069-bus unbalanced test system with four microgrids is utilized to demonstrate the effectiveness of the proposed method. The method is applied to the distribution system in Pullman, WA, resulting in a strategy that uses generators on the Washington State University campus to restore service to the Hospital and City Hall in Pullman.

Effects of restoration measures from the east Japan earthquake in the Iwate coastal area: application of a DSGE model

Restoration investment after an earthquake and tsunami can improve regional production, but effects of investment emerge differently in production, investment and consumption. Conventional economic models cannot reproduce such chronological nonconformity among economic indices. This study aims to analyze whether the dynamic stochastic general equilibrium (DSGE) model can duplicate the chronological restoration path and nonconformity, and quantifies the efficiency of the restoration measures, such as restoration investment with fund transfer and rebuilding subsidy, in the Iwate coastal region, where the east Japan earthquake hit. The analytical results are as follows: (1) consumption after the earthquake follows a hump-shaped path, where peak point of consumption was delayed from production peak, but then recovered; (2) private investment and labor demand decrease by more than self-restoration does when the restoration measures end; and (3) restoration investment with fund transfer and rebuilding subsidy improves the economy by accelerating the reconstruction of damaged capital stocks, and the benefits of these two measures outweigh their respective costs. These findings show that the influence of an unforeseen and disastrous earthquake can be explained well by the forward-looking decisions on consumption and savings (equal to investment) endogenizing in the DSGE model.

Anatomic Customization of Root-Analog Dental Implants With Cone-Beam CT and CAD/CAM Fabrication: A Cadaver-Based Pilot Evaluation.

Existing root-analog dental implant systems have no standardized protocols regarding retentive design, surface manipulation, or prosthetic attachment design relative to the site's unique anatomy. Historically, existing systems made those design choices arbitrarily. For this report, strategies were developed that deliberately reference the adjacent anatomy, implant and restorable path of draw, and bone density for implant and retentive design. For proof of concept, dentate arches from human cadavers were scanned using cone-beam computed tomography and then digitally modeled. Teeth of interest were virtually extracted and manipulated via computer-aided design to generate root-analog implants from zirconium. We created a stepwise protocol for analyzing and developing the implant sites, implant design and retention, and prosthetic emergence and connection all from the pre-op cone-beam data. Root-analog implants were placed at the time of extraction and examined radiographically and mechanically concerning ideal fit and stability. This study provides proof of concept that retentive root-analog implants can be produced from cone-beam data while improving fit, retention, safety, esthetics, and restorability when compared to the existing protocols. These advancements may provide the critical steps necessary for clinical relevance and success of immediately placed root-analog implants. Additional studies are necessary to validate the model prior to clinical trial.

An adaptive–alternative restoration algorithm for optical networks

Optical networks have been considered as the most capable technology for supplying the ever-increasing network bandwidth demand generated by the new Internet services. However, a significant challenge for optical networks is to provide an efficient manner to recover the lost communications due to failures. A failure in a system component or an optical fiber link can shut down all the crossing lightpaths, which may lead to a decrease in the revenue for clients or some sanctions to the providers due to an unattended agreed service level. In this work, we propose an adaptive–alternative path restoration algorithm, named NrPSR-R. The proposal has an adaptation capability according to the network state. NrPSR-R finds the Nr routes with minimum cost and selects one of them using a pre-defined policy. We performed a parametric analysis of the NrPSR-R algorithm. We also compared our proposal to other well-known restoration algorithms on different scenarios and NrPSR-R outperformed the others.

Resilience-Oriented Critical Load Restoration Using Microgrids in Distribution Systems

A resilience-oriented service restoration method using microgrids to restore critical load after natural disasters is proposed in this paper. Considering the scarcity of power generation resources, the concept of continuous operating time (COT) is introduced to determine the availability of microgrids for critical load restoration and to assess the service time. Uncertainties induced by intermittent energy sources and load are also taken into account. The critical load restoration problem is modeled as a chance-constrained stochastic program. A Markov chain-based operation model is designed to describe the stochastic energy variations within microgrids, based on which the COT is assessed. A two-stage heuristic is developed for the critical load restoration problem. First, a strategy table containing the information of all feasible restoration paths is established. Then the critical load restoration strategy is obtained by solving a linear integer program. Numerical simulations are performed on the IEEE 123-node feeder system under several scenarios to demonstrate the effectiveness of the proposed method. The impacts of fault locations, available generation resources, and load priority on the restoration strategy are discussed.

Partitioning-based approach to control the restored path length in p-cycle-based survivable optical networks

In recent years, p-cycles have been widely investigated for survivability of WDM networks. They provide fast recovery speed such as ring and capacity efficiency as mesh survivability schemes. However, restoration paths are very long, which causes excessive latency and intolerable physical impairments. On the other hand, nowadays, a wide set of applications require an optical path with almost no delay. The existing approaches, namely loopbacks removal and inter-cycle switching, provide a significant reduction in the restored path, but even then a number of restored paths remain many times longer than the working path lengths. In this paper, we propose a network partitioning-based approach to control the length of each restored path as per delay sustainability of time critical applications. The basic idea of the work is to partition the network into domains and construct the p-cycles for each domain independently. The domain wise construction of p-cycles restricts their length, which consequently reduces the length of restored paths. Here, we introduce a new concept where the selected border nodes are overlapped among adjacent domains to cover inter-domain spans of the network as a domain span in order to ensure their survivability through domain p-cycles. Simulation results show that the proposed solution is good enough to control the restored path length with small augmentation in redundancy of spare capacity as compared to optimal design of p-cycles. More importantly, it enhances the dual failure restorability significantly.

A Restorative Self-Healing Algorithm for Transmission Systems Based on Complex Network Theory

Restorative self-healing is one of the most important features of smart grids. The major purpose of a restorative self-healing control strategy is to steer a power system to secure operating states. In this paper, a self-healing transmission network reconfiguration algorithm based on the complex network theory is proposed. The capacities of generators and the amounts of important loads (i.e., the high priority loads), as well as the distribution and importance of each transmission line in the outage area are considered in the proposed method using the presented electrical “betweenness.” Next, the optimal restoration paths and the optimal restorative self-healing strategy can be attained automatically. Finally, the New England 10-unit 39-bus system and a part of the actual Guangdong power system in China are employed to illustrate the features of the proposed method.

Comprehensive design methodology for control and data planes in wavelength-routed optical networks

We propose a comprehensive design methodology for control and data planes of wavelength-routed optical networks (WRONs) employing mixed-line-rate (MLR) transmission for cost-effective resource provisioning. The proposed approach attempts to minimize the maximum lightpath capacity demand in Gbps (representing the measure of lightpath congestion) in network for a given traffic matrix by using a mix of a heuristic scheme and linear programming (LP). In the first step of the proposed three-step design, some lightpaths are set up on a set of judiciously selected fiber links (with point-to-point lightpaths between neighboring nodes), on a specific wavelength throughout the network, and an appropriate fraction of the same set of lightpaths is utilized for carrying control information, forming therefore the control plane (CP) of the WRON. The remaining bandwidth of these lightpaths is utilized to carry the data traffic along with all other designed lightpaths of the WRON using appropriate algorithm, forming the overall data plane (DP) of the WRON. In the second step, traffic routing is carried out through LP to minimize lightpath congestion in the network. In the third step, we utilize the results of LP to assign rates to lightpaths, such that the cost (considering only the transceiver cost) of the network is minimized. This design leads to congestion-aware MLR network with due consideration to cost-effectiveness without compromising the network restoration response against link failures. We carry out simulation studies employing possible CPs using both symmetric (CP topology being same as the physical topology) as well as asymmetric (using fewer fiber links than the symmetric case) topology. The results of our simulations indicate that the proposed design of CP with symmetric/asymmetric topology and in-band transmission with sub-lightpath capacity can bring down network congestion and cost with respect to symmetric out-of-band transmission (using fully reserved lightpaths for CP), without any perceptible sacrifice in respect of the network restoration time. Failure can occur either in CP or DP, or in both the planes. We investigate the effect of design of CP with symmetric/asymmetric topology on network restoration time for single- and double-link failures. We further present DP design methodology with hybrid restoration scheme, i.e., combination of dedicated (1:1) path protection and path restoration. We analyze the effect of symmetric CP topology and degree of protection on the congestion of the network. Some lightpaths, that support more traffic, are protected against failures, while the others are left for path restoration in the event of failures. As more lightpaths are protected, the congestion and power consumption of network increase. We provide an analysis of the factors that come into play while altering the degree of protection and observe how the choice for the degree of protection in DP can be arrived at using an appropriate design methodology.

Experimental Evaluation of Recovery From Multiple Failures in Multicore Fiber-Based Optical Network

We experimentally investigate recovery from multiple link failures in a multicore fiber (MCF) link-based optical network (NW). The NW is composed of an input/output interface and a two-ring structure to achieve high-capacity and highly reliable NWs in access areas. Each node has a switch (SW) unit consisting of field-programmable gate array (FPGA)-based optical SW units. The SW unit is able to detect failures and implements a failure recovery scheme that monitors signals and secures a restoration path, even when there are multiple link failures. Signal transmission experiments demonstrated that the path could be recovered within a short time period (approximately 8 ms), even after multiple failures in the NW. Moreover, performing a second (consecutive) switching after no signal was detected in the first switching for complicated multiple failures in the NW also led to recovery within a short time period (approximately 25 ms). These times are sufficiently less than that required by recovery time standard for telecommunication NWs of the Telecommunication Standardization Sector of the International Telecommunication Union (ITU-T). The results indicate that the MCF link would be useful for increasing the reliability of NWs.

Methods for minimax estimation under elementwise covariance uncertainty

We consider the minimax estimation problem in the linear regression model under elementwise constraints imposed on the covariance matrix of the random parameters vector. Minimax estimates are designed using several approaches to the numerical solution of the dual problem, namely, the semidefinite programming method, the conditional gradient method and its modification with the Lagrange multipliers and regularization. The efficiency of the suggested methods is illustrated by the example of path restoration for a maneuvering target with a statistically uncertain acceleration.

Optimisation model for power system restoration with support from electric vehicles employing battery swapping

The energy stored in the batteries of electric vehicles (EVs) could be employed for starting generators when a blackout or a local outage occurs. Considering the feature of the battery swapping mode, an available capacity model of the batteries in a centralised charging station is first developed. Then, the authors analyse the start-up characteristics of a generator powered by batteries and propose a bi-level optimisation-based network reconfiguration model to determine the restoration paths with an objective of maximising the overall generation capability. In the upper-level optimisation model, the generator start-up sequence is optimised, whereas the restoration paths are optimised in the lower-level one. Moreover, they consider the uncertainties associated with the available capacity of the batteries. The bi-level optimisation model for the network reconfiguration is developed in the chance-constrained programming framework and solved by the well-established particle swarm optimisation algorithm. Finally, case studies are employed to demonstrate the effectiveness of the presented model. Simulation results show that a centralised EV charging station could act as a power source to effectively restore a power system without black-start (BS) generators or with insufficient cranking power from BS generators, and the presented model could be used to guide actual system restorations.

Common Protection Path: Novel MPLS-based Recovery using Path Failure Probability and Service Criticality

Background/Objectives: Existing one-to-one, dedicated path-based and link-based MPLS-based recovery schemes are not resource efficient. We propose Common Protection Path, a novel protection scheme which ensures efficient utilization of resources. Methods/Statistical Analysis: Common Protection Path (CPP) selects a common protection path for traffic demands having the same ingress and egress routers. CPP factors in path failure probability and restoration priority levels of the traffic demands, unlike other schemes. We validated CPP algorithm using ns-2, over realistic network topology COST 239 with different link capacities. We compared CPP with one-to-one, dedicated path-based, link-based schemes and our modification of UNIFR (RFNS) i.e. UNIFR-similar. Findings: Our results show that using CPP scheme, more working bandwidth can be protected and more number of demands can be protected as compared to dedicated path-based, oneto- one, link-based and UNIFR-similar schemes. Our experimental results show that depending on the link capacity and the scheme taken for comparison, CPP provides up to 7.72% to 93.63% higher protection for COST 239 topology. Also with respect to restoration overbuild per Gbps protected bandwidth, CPP scheme is better as compared to other schemes. Applications/Improvements: Our results show that the CPP scheme results in efficient utilization of resources.

A fault tolerant channel allocation scheme in distributed cloud networks

With the cloud computing, storage and computing resources are moving to remote resources such as virtual servers and storage systems in large datacenters, which raise many performance and management challenges. The distributed cloud networks must have an ability to maintain an acceptable level of service during network failures to provide high resilience against service failures. This paper presents an eccentric fault tolerant path grouping scheme that can achieve mobility independent Quality of Service guaranteed services in distributed cloud networks To make this possible, we propose a path allocation and restoration strategy called "Reverse Shared Risk Link Group" and demonstrates how this concept can be applied to minimize recovery contention in cloud networks and to assess the network convergence associated with failures. To reflect little more actual situations, we assume that the bandwidth of cloud connection requests can be some fraction of the lightpath capacity. Simulation results show that the proposed recovery scheme outperforms other schemes with fewer signaling traffics and contention probability. Very fast restorability can be accomplished for multiple failures. We also has developed an analytical model and performed analysis for the proposed scheme in terms of two performance factors: mean system time and reservation blocking probability.

Cross-layer restoration with software defined networking based on IP over optical transport networks

The IP over optical transport network is a very promising networking architecture applied to the interconnection of geographically distributed data centers due to the performance guarantee of low delay, huge bandwidth and high reliability at a low cost. It can enable efficient resource utilization and support heterogeneous bandwidth demands in highly-available, cost-effective and energy-effective manner. In case of cross-layer link failure, to ensure a high-level quality of service (QoS) for user request after the failure becomes a research focus. In this paper, we propose a novel cross-layer restoration scheme for data center services with software defined networking based on IP over optical network. The cross-layer restoration scheme can enable joint optimization of IP network and optical network resources, and enhance the data center service restoration responsiveness to the dynamic end-to-end service demands. We quantitatively evaluate the feasibility and performances through the simulation under heavy traffic load scenario in terms of path blocking probability and path restoration latency. Numeric results show that the cross-layer restoration scheme improves the recovery success rate and minimizes the overall recovery time.

Primary Restoration Path Selection Considering Ferranti Effect and Reactive Power Capability of Black-start Generators

Power system restoration following a massive blackout starts with re-energizing Primary Restorative Transmission (PRT) systems at first. As power systems have been gradually enlarged and become more complex, periodical evaluation and reassignment of PRTs are needed. So far it has been decided by try and error approach by corresponding human experts to analyze and evaluate them. This paper presents an intelligent system that finds optimal primary restoration paths using analytic and heuristic knowledge from PSS/E data, and suggests an optimal PRTs depending on the condition of Ferranti effect or a reactive power capability margin of black-start generator. This system was tested in Korea Electric Power system, and showed a promising result.

Group decision support system for backbone-network reconfiguration

Abstract Modern power system is unprecedentedly vulnerable and the society is exposed to higher blackout risks. Therefore restoration is a key issue to power systems. Reasonable backbone-network reconfiguration is necessary for re-establishing the network and restoring loads quickly. In order to speed up network reconfiguration under security constraints, a group decision support system (GDSS) is developed. A unified data platform based on data warehouse is constructed to resolve inconsistencies of data, information and models. A three-stage restoration strategy and a two-layer restoration path searching method are proposed to establish restoration schemes. Multiple attribute decision-making is implemented to evaluate alternatives and consider various attributes about restoration speed and system security comprehensively. Group decision-making provides an aggregated cardinal ranking of candidate restoration schemes. The GDSS uses expert rules for qualitative analysis and numerical computation programs for quantitative analysis, and it can resolve the semi-structured decision problem of network reconfiguration efficiently. Restoration plan of Shandong power grid is developed with the proposed method and it has been adopted by State Grid Shandong Electric Power Company. Performance results of Shandong power grid of China demonstrate the feasibility and flexibility of the method.

Fiber optic submarine cables cuts cost modeling and cable protection aspects

This work presents a model to calculate costs associated with submarine fiber optic cable cuts. It accounts for both fixed and variable factors determining cost of fixing cables and restoring data transmission. It considers duration of a cut, capacity of fibers, number of fiber pairs and expected number of cuts during cable life time. Moreover, it provides templates for initial feasibility assessments by comparing cut costs to cost of different cable protection schemes. It offers a needed tool to assist in guiding decision makers in selecting type of cable, length and depth of cable burial in terms of increase in initial investment due to adapting such protection methods, and compare it to cost of cuts repair and alternative restoration paths for data.

First Experimental Assessment of ABNO-Driven In-Operation Flexgrid Network Re-Optimization

Traffic affected by link failures can be recovered using path restoration schemes. In dynamically operated networks provided with a control plane, restoration algorithms run in a centralized element, such as the path computation element (PCE). To increase traffic restorability in flexgrid networks, multiple paths, subconnections , can be used to restore every single affected connection. However, the multipath restoration scheme might result in a poor resource utilization entailing a lesser grade of service. In-operation network planning algorithms can be used to mitigate this problem once the failed link is repaired; we propose solving the so-called multipath after failure repair optimization problem (MP-AFRO) to reduce subconnections count by aggregating those belonging to the same original connection and rerouting the resulting connection to release spectral resources. The MP-AFRO problem is modeled using a mixed integer linear program formulation. In view of the complexity of the model and the limited time to solve the problem, we propose a heuristic algorithm that provides a good tradeoff between complexity and optimality. The performance on the MP-AFRO heuristic is firstly validated by simulation. Next, the heuristic algorithm is deployed inside an in-operation planning tool in the form of back-end PCE (bPCE) inside the application-based network operations architecture controlling a network; the bPCE is connected to the centralized active stateful PCE. MP-AFRO is experimentally demonstrated using a distributed field trial test-bed connecting the premises of Telefonica (Madrid), CNIT (Pisa), and UPC (Barcelona).

Automatic Impairment-aware Optical Path Switching in Multi-core Fiber Link Based on Multi-ring Structure

We developed a novel multicore fiber (MCF) link based on a multiring structure composed of field programmable gate array (FPGA)-based optical switching units for highly reliable networks. The switching algorithm implemented on the FPGA in the unit has five high-functioning processes capable of coping with multiple link failures in the network. To verify the operations of this MCF link, we experimentally demonstrated automatic impairment-aware optical path switching when a failure occurred in an MCF link based on a two-ring structure. We were able to perform path recovery by switching within a relatively short period of time, 7.6 ms, which is sufficiently less than that required by ITU-T. The restoration path that substitutes for the failed working path was also optimized for low-loss transmissions by selecting the path having the minimum number of units through which a signal passes. These results indicate that the link will be useful for optical network designs that simultaneously need to ensure high capacity and reliable transmissions in businesses such as data centers.

System Restoration Tools: System Restoration Navigator Integrated into EPRI Operator Training Simulator (SRN/OTS)

System operators and planners develop and implement restoration plans based on off-line simulation studies, and accumulated experience and knowledge. One of the challenges in developing a restoration plan is to sift through numerous possible restoration scenarios and paths, in order to identify those that are technically feasible. When implementing a restoration plan in an on-line environment following a blackout, the operators need to adapt to the actual outage scenarios and available resources, and be constantly mindful of anticipated voltage and frequency excursions that must remain within system and equipment tolerances. In recognition of these challenges, EPRI has developed System Restoration Navigator (SRN), to provide decision support to system restoration planning and operations engineers in developing, evaluating and revising system restoration strategies, guidelines, plans and step-by-step procedures. During 2013-2014, EPRI developed SRN version 3.0, which is designed to facilitate its integration into a commercial operator training simulator (OTS) (AKA a dispatch training simulator, DTS). The integration of SRN 3.0 with an OTS allows operators to obtain experience in simulating, developing, experimenting with and revising system restoration plans, and to address related regulatory standards. The integration expands the usability of SRN 3.0 by providing the OTS platform for training purposes and for the purpose of interfacing SRN 3.0 with operational power system models to be able to explore near real time application of SRN 3.0. This 2013-2014 development work also included the integration of SRN 3.0 into EPRI OTS, and its application on the Florida Reliability Coordinating Council (FRCC) power system. A detailed account of development of SRN 3.0, its integration into EPRI OTS and its application to FRCC system is presented in this paper.