A Tabu-search-based Algorithm for Distribution Network Restoration to Improve Reliability and Resiliency

Fault restoration techniques have always been crucial for distribution system operators (DSOs). In the last decade, it started to gain more and more importance due to the introduction of output-based regulations where DSO performances are evaluated according to frequency and duration of energy supply interruptions. The paper presents a tabu-search-based algorithm able to assist distribution network operational engineers in identifying solutions to restore the energy supply after permanent faults. According to the network property, two objective functions are considered to optimize either reliability or resiliency. The mathematical formulation includes the traditional feeders, number of switching operation limit, and radiality constraints. Thanks to the DSO of Milan, Unareti, the proposed algorithm has been tested on a real distribution network to investigate its effectiveness

Modeling Resilience in Electrical Distribution Networks

Electrical distribution networks deliver a fundamental service to citizens. However, they are still highly vulnerable to natural hazards as well as to cyberattacks; therefore, additional commitment and investments are needed to foster their resilience. Toward that, this paper presents and proposes the use of a complex simulation model, called reconfiguration simulator (RecSIM), enabling to evaluate the effectiveness of resilience enhancement strategies for electric distribution networks and the required resources to implement them. The focus is, in particular, on one specific attribute of resilience, namely, the readiness, i.e., the promptness and efficiency to recover the service functionality after a crisis event by managing and deploying the available resources rapidly and effectively. RecSIM allows estimating how and to what extent technological, topological, and management issues might improve electrical distribution networks’ functionality after the occurrence of accidental faults, accounting for interdependency issues and reconfiguration possibilities. The viability of implementing RecSIM on a real and large urban network is showcased in the paper with reference to the study case of the electrical distribution network (EDN) of Rome city

Advancements in Enhancing Resilience of Electrical Distribution Systems: A Review on Frameworks, Metrics, and Technological Innovations

This comprehensive review paper explores power system resilience, emphasizing its evolution, comparison with reliability, and conducting a thorough analysis of the definition and characteristics of resilience. The paper presents the resilience frameworks and the application of quantitative power system resilience metrics to assess and quantify resilience. Additionally, it investigates the relevance of complex network theory in the context of power system resilience. An integral part of this review involves examining the incorporation of data-driven techniques in enhancing power system resilience. This includes the role of data-driven methods in enhancing power system resilience and predictive analytics. Further, the paper explores the recent techniques employed for resilience enhancement, which includes planning and operational techniques. Also, a detailed explanation of microgrid (MG) deployment, renewable energy integration, and peer-to-peer (P2P) energy trading in fortifying power systems against disruptions is provided. An analysis of existing research gaps and challenges is discussed for future directions toward improvements in power system resilience. Thus, a comprehensive understanding of power system resilience is provided, which helps in improving the ability of distribution systems to withstand and recover from extreme events and disruptions

Recovery Model for Survivable System through Resource Reconfiguration

A survivable system is able to fulfil its mission in a timely manner, in the presence of attacks, failures, or accidents. It has been realized that it is not always possible to anticipate every type of attack or failure or accident in a system, and to predict and protect against those threats. Consequently, recovering back from any damage caused by threats becomes an important attention to be taken into account. This research proposed another recovery model to enhance system survivability. The model focuses on how to preserve the system and resume its critical service while incident occurs by reconfiguring the damaged critical service resources based on available resources without affecting the stability and functioning of the system. There are three critical requisite conditions in this recovery model: the number of pre-empted non-critical service resources, the response time of resource allocation, and the cost of reconfiguration, which are used in some scenarios to find and re-allocate the available resource for the reconfiguration. A brief specifications using Z language are also explored as a preliminary proof before the implementation .. To validate the viability of the approach, two instance cases studies of real-time system, delivery units of post office and computer system of a company, are provided in ensuring the durative running of critical service. The adoption of fault-tolerance and survivability using redundancy re-allocation in this recovery model is discussed from a new perspective. Compared to the closest work done by other researchers, it is shown that the model can solve not only single fault and can reconfigure the damage resource with minimum disruption to other services

Reliability and resilience evaluation of distribution automation.

Modern distribution grid utilities are steadily adapting to the concepts of Smart Grids by augmenting distribution grids with Distribution Automation (DA) to enhance visibility and control for the purpose of enhanced system availability. Existing methods to place and evaluate DA overlook the important enhancement it provides to the resilience of a system. Resilience, a much-discussed but poorly defined measure for power systems, represents a system’s ability to withstand and recover from High-Impact Low-Probability (HILP) events such as storms and earthquakes. This thesis argues that exisiting resilience quantification methods do not capture the direct contribution which DA can make to enhance system resilience. It develops a novel model and methodology to analyse distribution grid resilience using the formalisms of Reliability Graphs (RGs), and Stochastic Reward Nets (SRNs). These two models capture the different parts of the complex recovery process which distribution grids perform to recover from faults using DA. There are three novel contributions in this thesis. Firstly, a three-tier hierarchical model which contains an RG is developed to assess the enhancement which DA equipment provides to load point and feeder availability and resilience. Next, and SRN is used to develop a load point (LP) model which incorporates the dependence of feeder assets during the fault isolation phase of the recovery process. Finally, the SRN model is augmented with a phased recovery model to represent the complex recovery process for distribution grids. Utilising these models, the placement of switch automation and fault indicators is evaluated, and the contribution they make to resilience demonstrated. Collectively, these models give a novel means of assessing the the availability, sensitivity and resilience of distribution grids which utilise DA

Fault Location, Isolation and Network Restoration as a Self-Healing function

One of the main emphasis of the smart grid is the interaction of power supply and power customer in order to provide a reliable supply of power as well as to improve the flexibility of the network. Along with this, the increased energy demand, coupled with strict regulations on the quality and reliability of supply intensifies the pressure on distribution network operators to maintain the integrity of the network in its faultless operation mode. Additionally, regardless of the huge investments already made in replacing aging infrastructure and translating “the old-fashioned grid” in a “Smart Grid” to minimize the probability for equipment failure, the chances of failure cannot be completely eliminated. In accordance, in the event of faults in the network, apart from the high penalty costs in which network operators may incur, certain safety factors must be taken into consideration for particular customers (for example, hospitals). In view of that, there is a necessity to minimize the impact on customers without supply and maintain outages times as brief as possible. Within this scenario comes the concept of self-healing grid as one of the key-technologies in the smart grid environment which is partly due to the rapid development of distribution automation. Self-healing refers to the capacity of the smart grid to restore efficiently and automatically power after an outage. Self-healing main goals comprise supply maximum load affected by the fault, take the shortest time period possible for restoration of the load, minimizing the number of switching operations and keeping the network capacity within its operating limits. This research has explored insights into the smart grid in terms of the self-healing functionality within the distribution network with main emphasis on self-healing implementation types and its applicability. Initially a detailed review of the conception of the smart grid in order to integrate the self-healing and thus fault location, isolation and service restoration capabilities was conducted. This was complemented with a detailed discussion about the electricity distribution system automatic fault management in order to create a framework around which the aim of the research is based. Finally the self-healing problem coupled with current practical implementation cases was addressed with the objective of exploring the means of improvement and evolution in the automation level in the distribution network using Fault Location Isolation and Service Restoration (FLISR) applicability as a medium