Repair Crews Research Articles

Dynamic load restoration considering interdependency between power distribution system and urban transportation system

After a major outage, mobile emergency resources (MERs) can be dispatched via the transportation system (TS) for service restoration to critical loads in the power distribution system (PDS). In this case study, the efficiency of service restoration in the PDS is associated with the traffic efficiency of the TS, and vice versa, because the PDS and TS are mutually coupled through traffic lights and MERs. This paper proposes a service restoration method considering interdependency between the PDS and TS, which is formulated as a mixed-integer linear program (MILP). The objective includes maximizing the efficiency of both PDS restoration and TS. By solving the MILP, the dynamic load restoration and MER dispatch strategies can be obtained. For the PDS, the availability of MERs, including mobile sources and repair crews, relates to their dispatch in the TS, and their relationship is formulated as mathematical models. For the TS, the dynamic traffic flow is modeled using the cell transmission model and the effect of traffic lights is considered. Case studies validate the effectiveness of the proposed method.

Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration With Repair Crew and Mobile Power Source Dispatch

Repair crews (RCs) and mobile power sources (MPSs) are critical resources for distribution system (DS) outage management after a natural disaster. However, their logistics is not well investigated. We propose a resilient scheme for disaster recovery logistics to co-optimize DS restoration with dispatch of RCs and MPSs. A novel co-optimization model is formulated to route RCs and MPSs in the transportation network, schedule them in the DS, and reconfigure the DS for microgrid formation coordinately, etc. The model incorporates different timescales of DS restoration and RC/MPS dispatch, the coupling of transportation and power networks, etc. To ensure radiality of the DS with variable physical structure and MPS allocation, we also model topology constraints based on the concept of spanning forest. The model is convexified equivalently and linearized into a mixed-integer linear programming. To reduce its computation time, preprocessing methods are proposed to pre-assign a minimal set of repair tasks to depots and reduce the number of candidate nodes for MPS connection. Resilient recovery strategies thus are generated to enhance service restoration, especially by dynamic formation of microgrids that are powered by MPSs and topologized by repair actions of RCs and network reconfiguration of the DS. Case studies demonstrate the proposed methodology.

Repair and Resource Scheduling in Unbalanced Distribution Systems Using Neighborhood Search

This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming (MILP) model is developed for co-optimizing crews, resources, and network operations. The MILP model coordinates damage isolation, network reconfiguration, distributed generator re-dispatch, and crew/resource logistics. In addition, a framework for integrating different types of photovoltaic (PV) systems in the restoration process is developed. We consider two different types of crews, namely, line crews for damage repair and tree crews for obstacle removal. We also model the repair resource logistic constraints. Furthermore, a new algorithm is developed for solving the distribution system repair and restoration problem (DSRRP). The algorithm starts by solving DSRRP using an assignment based method, then a neighborhood search method is designed to iteratively improve the solution. The proposed method is validated on modified IEEE 123and 8500-bus distribution test systems.

Enhancing Power Distribution Feeders Restoration with a Probabilistic Crew Dispatch Method: Case Studies using Historical Data from a Brazilian Power Distribution Company

Abstract This paper proposes a methodology to repair crews dispatch during distribution feeders restoration immediately after remotely controlled actions have been taken. Our method determines the sectors patrol sequence using the expected number of faults for each sector considering a previously calculated fault probability. Next, a road graph mapping of the buses is obtained by associating each bus with its real-world position. The crews’ route inside each sector is determined by the application of the nearest neighbor algorithm on that mapping. The case studies analyzed 24 real faults available in the database of a Brazilian power distribution company, and, a comparison was made between the time spent to locate the failures by simulating both the proposed methodology and the usual greedy strategy. The average time spent in localizing all the failures was from 9.49 % to 41.81 % shorter than in the usual method. Moreover, the speed and distance of repair crews showed weak influence in the crew dispatch methodology efficiency. Such results indicate an enhancement of the power distribution QoS indicators by using the proposed methodology to deal with faults.

A Combined Repair Crew Dispatch Problem for Resilient Electric and Natural Gas System Considering Reconfiguration and DG Islanding

Resilience is an overarching concept that requires combined efforts from interdependent critical infrastructures to achieve. As the interdependence between the power system and the natural gas system grows, the roles of coordination in post-disaster repair will be unneglectable to improve the resilience of the two systems. In this paper, a combined repair crew dispatch problem for the interdependent power and natural gas systems is proposed. The repair schedule of the two systems is coordinated and co-optimized. Both power system topology reconfiguration and intentional DG islanding are modeled as operational measures to further improve the resilience of the interdependent systems. Case studies validate the effectiveness of the proposed method in reducing load shedding and repair duration, and prove that the interdependence has a significant impact on the repair sequence and crew coordination.

Development of Optimum Repair Schedule of Electrical Network Equipment to Improve the Reliability of its Functioning

To ensure uninterrupted power supply to consumers, maintenance of the electrical networks in a working condition is today carried out through the use of a system of preventive maintenance. In the general case such a system allows building equipment repair schedules based on repair cycles for a long time predetermining the list of necessary material and labor resources in advance. However, in practice, the use of this system is rather difficult and not always effective. This is due to the need to change the repair schedule for emergency or urgent repairs taking into account the seasonality of work performed and the organizational structure of the production department of electrical networks and related departments as well as taking into account the specific features of the operation of specific equipment. Taking into account the current pace of development of electrical networks with a steady increase in the number of consumers (which also leads to a complication of the configuration of electrical networks) this is impossible without the use of appropriate mathematics and software that automates the planning processes for the maintenance and repair of electrical networks with a large number of factors. The minimum equipment downtime was taken as the main criterion for optimality, as a factor that largely determines the reliability of power supply. A planning algorithm has been developed that takes into account the ranking of works in order of importance, the possibility of their shift in time and the likely adjustment of the schedule based on the results of assessing the technical condition of the equipment. A method for minimizing the downtime of repair crews by using them in adjacent areas as well as a technique for identifying a set of equipment that may be under repair in the same period of time are proposed.

An Improved SSCB Combining Fault Interruption and Fault Location Functions for DC Line Short-Circuit Fault Protection

At the occurrence of a permanent fault in a DC microgrid, apart from isolating the faulty section using a solid-state circuit breaker, the protection system should also have the fault position located so that repair crew can be sent to clear the fault and restore the isolated section. Available fault location methods are either influenced by network topology or need to add costly equipment. Located immediately next to the faulty line, the solid-state circuit breaker has the advantage of position required for injecting and detecting fault location signals, and it is isolated from the rest of the system by disconnector after fault interruption. Therefore, using the solid-state circuit breaker for fault location has a potential research value. However, it is rarely discussed in previous literatures. In this paper, an improved topology of the solid-state circuit breaker is proposed, which is able to inject signals into the isolated faulty line to determine fault position. By reusing components, the improved topology can achieve function expansion without much increasing the size and cost for fault protection, obtaining an accurate result uninfluenced by the network topology. Simulations and experiments are conducted in a 200 V/DC system to verify the effectiveness of the design.

Stochastic indexes for power distribution systems resilience analysis

The resilience in critical infrastructures context indicates the capability to anticipate, absorb, resist and recover from an event or adversity. In a power distribution system, as the frequency of severe weather event increases, this characteristic becomes mandatory, considering the impact in the society when a blackout occurs. This study proposes the analysis of power distribution systems resilience through two stochastic resilience indexes. Given several simulated weather scenarios and several numbers of available repair crews, the resilience indexes estimate the probability of a waiting crew time greater than a threshold as well as for the impact in the total time to restore the entire distribution system. These indexes, together with a costs and losses estimation methodology help the utilities in the decision support process as it demonstrates how the number of available repair crews will impact in the restoration process and costs for each possible weather scenario. The result for a real Brazilian power distribution system indicates its feasibility and benefits for the utilities.

Integrated optimal scheduling of repair crew and relief vehicle after disaster

When catastrophes occur, certain areas could be isolated and have more hardship in being provided with the relief goods because of the destruction of roads. Additional damages will occur if isolated areas cannot be supplied relief goods quickly. Therefore, to provide adequate relief goods to the demand area in time, it is essential to recover the destroyed roads and make the isolated areas accessible. In addition, relief goods should be distributed on the basis of optimal scheduling. If the order for repairing destroyed roads and supplying relief goods to an isolated area is established from the respective viewpoints, a delay will occur compared to optimal schedule considering both of them simultaneously. Thus, this study proposes a mathematical model based on Mixed Integer Linear Programming (MILP) and an Ant Colony Optimization (ACO) algorithm providing optimal scheduling by taking into account both reconstruction and delivery. By conducting various numerical experiments, the solution from the MILP and ACO could lead to more effective results than decisions based on two points of view that are not synchronized. Some meaningful findings are also found by numerous computational experiments. This research can help to make the optimal decision for scheduling of recovery and supply that thus reduces any additional damage after a major disaster.

Resilience-Oriented Distribution System Restoration Considering Mobile Emergency Resource Dispatch in Transportation System

After major outages, local power sources, including mobile power sources (MPSs), can be coordinated to serve critical loads in distribution systems (DSs). Repair crews (RCs) are sent to repair faulted components. Both mobile emergency resources, i.e., MPSs and RCs, need to travel through the transportation system (TS) before they reach the destination for service. However, traffic congestion may happen after natural disasters and impact the dispatch of the MPSs and RCs. Therefore, the dynamic traffic state in the TS should be considered for efficient dispatch of mobile emergency resources. This paper proposes a framework to determine critical load restoration strategy for the DS, considering the dispatch strategy of the MPSs and RCs in the TS. The cell transmission model (CTM) is used to formulate the weighted dynamic traffic assignment problem (WDTA) in the TS as a linear program (LP), aiming at minimizing the total prioritized travel time of the MPSs and RCs. For the DS, the multi-period critical load restoration problem (CLR-DS) is formulated as a mixed-integer linear program (MILP) to maximize the cumulated service time to critical loads. Unbalanced three-phase power flow and time-varying topological constraints are considered. Case studies validate the effectiveness of the proposed method.

Anatomy of Failures: Stability Requirements in All Stages of Operations

The paper provides examples of how temporary conditions experienced during construction, retrofit, or repair can bring an otherwise robust structure to failure. The KTVO Tower near Kirksville, Missouri, USA, guyed by seven tiers of guy cables, stood 610 m tall, until it suddenly collapsed on June 2, 1988. The collapse occurred during the replacement of potentially defective braces. The Tower had been subject to severe weather conditions, as well as having previously lost some braces; and yet, the experienced repair company brought it down through altered brace replacement employed by the repair crew. How did it happen? This paper goes through all the stages of this tragic event; from the failure scene back through failure analysis to the design, manufacturing, material supplies, and fatally altered repair procedure. This paper also provides an example of reinforced concrete structures which are erected with the steel reinforcement delivered to their final position as a multi-story cage lifted in-place by crane and acting as temporary independent structures. Their stability relies on proper bracing and restraint. What if some of the bracing becomes an obstacle to some activities? The paper concludes with best practices for involving a licensed professional at all stages of construction or repair in order to help prevent future collapses.

Matheuristic for emergency response in the electric distribution system with unforeseen islanding

Since power supply may suffer interruptions, caused by climate events or even due to equipment and human failures, these interruptions are associated with procedures commonly referred as emergency orders. These emergency orders must be attended by repair crews in an attempt to reestablish the power supply all over the system. Assuming a set of these emergency orders, the network operation center (NOC) must find a scheduling so that they are all attended by the repair crews and the power supply reestablished as soon as possible, while considering the minimization of the total service cost. Distributed generation (DG) may be one alternative for furnishing temporally power supply, such as photovoltaic and wind power generation sources. In such approach, the islanding operation confers such a complexity when considering how much time should be needed to supply the affected loads and which ones may be even selected. This study proposes a novel matheuristic for emergency response to the contingency planning problem related to electric distribution operations, considering unforeseen islanding of DG. From using a mixed integer linear programming (MILP) model, based on the emergency order scheduling problem (EOSP) with islanding operation formulations, the optimization criteria involves the minimization of the cost of non-supplied energy and the penalties related to high important customers, while respecting electrical constraints. Computational results on the IEEE 33-bus system, modified with the insertion of DGs, show the effectiveness of the proposed solution on reducing the total attendance cost when compared to a traditional scheduling solution without considering the islanding operation.

Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand

This paper proposes a novel method to co-optimize distribution system operation and repair crew routing for outage restoration after extreme weather events. A two-stage stochastic mixed integer linear program is developed. The first stage is to dispatch the repair crews to the damaged components. The second stage is distribution system restoration using distributed generators, and reconfiguration. We consider demand uncertainty in terms of a truncated normal forecast error distribution, and model the uncertainty of the repair time using a lognormal distribution. A new decomposition approach, combined with the Progressive Hedging algorithm, is developed for solving large-scale outage management problems in an effective and timely manner. The proposed method is validated on modified IEEE 34- and 8500-bus distribution test systems.

Joint Calculation of the Non-Stationary Thermal Mode of a Building and its Water Heating System

The solution of the problem of joint cooling of the building and its water heating system, in case of the thermal energy supply termination, is relevant, since only it can determine the real time available to repair crews to restore the operation of the heating system of each object. The article gives a brief description of the algorithms for calculating the non-stationary hydraulic and thermal regime of the heating system and the algorithm for calculating the non-stationary thermal regime of the building. The joint implementation of both algorithms is based on taking into account the influence of the thermal regime of the system and the building on each other at each time step. Linking of thermal processes in a heating system and in a building is carried out taking into account in their thermal balances of the same quantity of heat flowing for a step on time from a heating system element to the room or vice versa. Calculations on the proposed PC program investigated the influence of different factors on the cooling time of the heating system and the whole building.

Power Distribution System Outage Management With Co-Optimization of Repairs, Reconfiguration, and DG Dispatch

This paper proposes a two-stage method for the outage management of power distribution systems. The first stage is to cluster repair tasks of damaged power generation and delivery components based on their distances from the depots (central crew stations) and the availability of resources, to improve the computational efficiency in solving outage management problems for large distribution systems. The second stage is to co-optimize the repair, reconfiguration, and distributed generation dispatch to maximize the picked-up loads and minimize the repair time. The distribution system repair and restoration problem is formulated as a mixed integer linear program, considering constraints of system operation and routing repair crews. Crews are dispatched considering equipment resources, traveling time, and repair time. The proposed method is tested on modified IEEE 34 and 123-bus distribution test systems with multiple damages. The results demonstrate the advantages of co-optimizing repair and restoration.

A note on network repair crew scheduling and routing for emergency relief distribution problem

This paper proposes a dynamic programming algorithm for the NRCSRP with multiple crews. This algorithm also improves the existing algorithm for the problem with a single crew.

Network repair crew scheduling for short-term disasters

• A repair crew model considering dynamic aspects of short-term disasters in the post-disaster period was developed. • Dynamic characteristics of disasters in the short-term were considered. • A mathematical model based on mixed integer programming was proposed. • An ant colony algorithm was developed, and it can solve a multiple repair crew problem quickly. Casualties and damages caused by disasters occur every year. To reduce further damages in the post disaster period , many types of research have been conducted. The repair crew problem is one of these efforts, and it is used for deciding ways to manage repairs to destroyed roads that connect members of supply chain networks. Especially in rural areas where road networks are sparse and supply chains are limited, road-network repair is particularly important because road destruction can contribute to high rates of rural isolation. In addition, the unpredictable nature of disasters creates concerns for those effecting post-disaster management. Especially in the short-term after a disaster, damage characteristics can dramatically change. Therefore, we considered a repair crew problem in which aspects of damage vary at certain times. A mathematical formulation on the basis of mixed integer programming is introduced to minimize the weighted sum of total damages caused in isolated areas and completion time of a repair crew. To overcome the complexity issue, an ant colony system algorithm was developed. It can be used to solve a multiple repair crew problem. Our study gives new insights into ways to manage problems in the post-disaster period.

CLOUD computing risk management for server‐farm repair rates, consumer load cycle, server‐farm repair crew count, and additional servers

A discrete event simulator, CLOURAM: CLOUD Risk Assessor and Manager, algorithmically estimates the risk indices in modern‐day CLOUD computing scenarios with tangible risk management targets that are favorable to the intractably tedious, theoretical Markov solutions or hand calculations overly limited in scope. The goal is to improve the operational quality of CLOUD by optimizing the number of servers for capacity addition and optimizing the final repair crew count. We too optimize the server unit repair rates, and the consumer load cycle by curbing the demand using Linear Programming (LP)‐based optimization with the proper objective functions and constraints. Small and large CLOUD systems are simulated with cost and benefit comparisons. The 2‐state (UP and DN) or 3‐State (UP, DN, and DER) units statistically fail and recover with Negative Exponential or Weibull densities. WIREs Comput Stat 2018, 10:e1424. doi: 10.1002/wics.1424This article is categorized under: Statistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality Control Algorithms and Computational Methods > Networks and Security Statistical Models > Simulation Models Algorithms and Computational Methods > Linear Programming

An integrated network design and scheduling problem for network recovery and emergency response

Effective recovery and restoration of infrastructure systems play a crucial role in recovery after disasters. This issue is particularly critical when delivering time-sensitive services and commodities. Damage to infrastructure can lead to disruptions and diminished capacity to respond to emergencies. We model the interdependencies between infrastructure systems and service providers as a network model, where emergency responders deliver critical services while network recovery crews repair damage to critical infrastructure. We present a novel extension to the P-median problem, where the objective is to minimize the cumulative weighted distance between the emergency responders and the calls for service over the time horizon by coordinating the activities of two types of service providers. We locate emergency responders (facilities) on a network over a finite time horizon while network recovery crews install arcs. The installation part of the models is modeled as a scheduling problem with identical parallel servers (the repair crews), where an arc can be used by the emergency responders when installation is completed. We propose Lagrangian relaxation formulations of the models, which we solve using subgradient optimization. A feasible solution is obtained using the Lagrangian relaxation, which provides an upper bound to the original models. We test our models with both real-world data and data sets from Beasley’s OR Library to demonstrate the effectiveness of the algorithm in solving large-scale models. The results give insight into the optimal schedule for restoring critical arcs in a network when delivering critical services and commodities after a disruptive event.

Energization-Status Identification of Three-Phase Three-Core Shielded Distribution Power Cables Based on Non-Destructive Magnetic Field Sensing

Three-phase three-core distribution power cables are widely deployed in power distribution networks and are continually being extended to address the ever-increasing power demand in modern metropolises. Unfortunately, there are high risks for the repair crew to operate on energized distribution power cables, which can cause deadly consequences such as electrocution and explosion. The predominant energization-status identification techniques used today are either destructive or only applicable to un-shielded power cables. Moreover, the background interferences affect the sensing technique reliability. In this paper, we have developed a non-destructive energization-status identification technique to identify energized three-phase three-core distribution power cables by measuring magnetic fields around the cable surface. The analysis shows that the magnetic-field-distribution pattern as a function of azimuth around the cable surface of the energized (current- or voltage-energized) three-phase three-core distribution power cable is distinguishable from the de-energized one. The non-idealities of phase currents and cable geometry were also discussed, and the proposed method still works under these circumstances. The sensing platform for implementing this technique was developed accordingly, consisting of magnetoresistive sensors, a triple-layered magnetic shielding, and a data acquisition system. The technique was demonstrated on a 22-kV three-phase three-core distribution power cable, and the energized status of the cable can be successfully identified. The proposed technique does not damage cable integrity by piercing the cable, or exposing the repair crew to hazardous high-voltage conductors. The platform is easy to operate and it can significantly improve the situational awareness for the repair crew, and enhance the stability of power distribution networks.