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The mismatch between load demand and supply power may increase when distributed generation based on renewable energy sources is connected to the distribution system (DS). This paper shows the optimal battery energy storage system (BESS) placement problem on the DS to minimize the electricity cost. Diverse electricity prices are considered for normal, off-peak and peak hours in a day. Wild geese algorithm (WGA) is applied to optimize the location and power of the BESS. The problem and the efficiency of WGA is validated on the 18-bus DS four scenarios consisting of the DS without BESS placement, the DS with BESS placement, the DS existing photovoltaic system (PVS) without BESS placement and the DS existing PVS with BESS placement. The numerical results show that optimal BESS placement is an effective solution for minimizing electricity cost on the DS with and without PVS. In addition, the results have also shown that WGA is a potential method for the BESS placement problem.

One of the most serious issues that requires special attention is the protection of distribution networks. Using the proper protective equipment improves the safety of the power distribution network during fault conditions. Fault current limiter (FCL) is a type of modern preservation system used to protect power networks and equipment. The voltage restoration of buses during faulty conditions is one of the main concerns of power networks. A group of coordinated DC reactor type fault current limiters are designed and tested in this study to protect the network and restore its bus voltage during the fault period. The proposed FCLs coordination strategy is modelled and simulated in the MATLAB platform, and the results are validated.

Günümüzde hızla artan nüfusun paralelinde yaşamsal ihtiyaçlara bağlı tüketimler için ortaya çıkan teknolojik gelişmeler ve sanayileşme ile enerji ihtiyacı her geçen gün artmaktadır. İlgili enerji ihtiyacı daha çok konvansiyonel kaynaklardan karşılanmakta ancak bu durum çevre kirliliğine sebebiyet vermektedir. Fosil yakıtların en çok tüketildiği ve doğal olarak karbon emisyonuna neden olan alanlardan biri olan ulaşım sektöründe ise ciddi değişimler meydana gelmektedir. Özellikle fosil kaynaklı araçlar yerini Elektrikli Araçlara (EA) bırakmakta ve birçok marka EA modelleri geliştirmeye yönelik önemli adımlar atmaktadır. Ancak EA’ların üretim ve kullanımının artması enerjiye olan ihtiyacı da katlamaktadır. Aynı zamanda bu araçların şarj ihtiyaçları için kurulması gereken şarj istasyonu sayısı ve yatırım gerektiren altyapı hizmetlerinin planlanmasını zorunlu kılmaktadır. Bu çalışmada, Türkiye’de hizmet veren bir dağıtım sistemi operatörlüğünde işletilen ve EA şarj istasyonu kurulması planlanan otopark alanları için DIgSILENT PowerFactory V15.1 programında detaylı analizler gerçekleştirilmiştir. Türkiye’de hizmet veren bir otopark işletmecisi ile ortak çalışılacak alanlarda altyapı hizmetlerinin aksamaması ve olası güç sistemi arızalarının önüne geçebilmek amacıyla güç akışı analiz sonuçları paylaşılmıştır. Hatlardan akan aktif, reaktif güçler ve transformatör yüklenmelerine göre öneriler sunulmuştur., Today, the need for energy is increasing day by day with the technological developments and industrialization that have emerged in order to keep up with the consumption related to the vital needs that increase in parallel with the rapidly increasing population. This emerging energy need is mostly provided by non-renewable resources and also causes environmental pollution. Serious changes are occurring in the transportation sector, which is one of the areas where fossil fuels are consumed the most and naturally causes carbon emissions. In particular, fossil-based vehicles are replaced by Electric Vehicles (EVs), and many brands are taking important steps to develop EV models. However, the increase in the production and use of EVs also increases the need for energy. At the same time, it makes it necessary to plan the number of charging stations and infrastructure services that require investment for the charging needs of these vehicles. In this study, detailed analyzes were carried out in the DIgSILENT PowerFactory V15.1 program for the parking areas operated by a distribution system operator in Turkey and where an EV charging station is planned to be installed. Power flow analysis results were shared in order to prevent disruption of infrastructure services and possible power system failures in areas to be worked in partnership with a parking lot operator serving in Turkey. Suggestions are presented according to the active and reactive powers flowing from the lines and transformer loads.

Lisäää oa-julkaisu, kun saatavilla. Recently, due to the restructuring of power systems and the high penetration level of local renewables, distribution systems have encountered with the complexity of power management. Therefore, the modern systems would be operated in a multi-agent structure which facilitates the power management as well as privacy protections of independent entities. In this structure, the distribution system is assumed to compose of several agents who independently schedule their local resources in order to maximize their own profits. Consequently, this paper provides an efficient peer-to-peer (P2P) active power management framework in a multi-agent distribution system while considering network constraints (i.e., line loadings and losses). In this context, in the proposed P2P scheme, the distribution system operator (DSO) model the network constraints in the form of line-usage costs within the transactive signals. Respectively, the developed transactive control signals enable the DSO to model the power loss as well as alleviate the congestion in the grid. Therefore, the agents automatically consider the network constraints in their power transactions management procedure without any direct interferences of the DSO in their resource scheduling. Finally, the proposed model is implemented on the modified-IEEE-37-bus-test system in order to investigate its effectiveness in the energy management of multi-agent systems.

This paper deals with the short-circuit analysis of distribution systems dominated by Voltage Source Converters (VSCs). A novel methodology has been proposed in this paper for short-circuit calculation of power systems populated with VSCs where the control modes and potential current-saturated operation of power converters are considered. The studied distribution system has been modeled using an element-based steady-state formulation that includes the converter equations in both normal operation and fault scenarios. Then, equilibrium points of the studied distribution system are identified by solving the established systems of equations for different potential current-saturation states of the VSCs. The methodology identifies possible solutions involving different saturation states of different converters. The proposed methodology is applied to a specific case study of a distribution system penetrated with VSCs in both grid-forming and grid-following control. The short-circuit analysis results indicate that VSCs operation shows a significant impact on the short-circuit equilibrium points of the studied system. In addition, multiple equilibrium points may exist depending on whether the grid-forming converter is saturated or not. The existence of multiple equilibrium points is validated through dynamic simulations.

The power distribution systems fault root cause classification is an important but challenging problem. Traditional classifiers fail to achieve high accuracy and good generalization performance due to data insufficiency. A large volume of unlabeled data is available, which can be utilized to improve classification performance. This paper proposes a novel classifier called Robust Semi-Supervised Prototypical Network (RSSPN) based on Prototypical Network architecture and semi-supervised learning to address this issue. The proposed method can mine information from unlabeled data to improve the generalization ability and classification accuracy. Furthermore, RSSPN adopts the idea of meta-learning to obtain the few-shot learning" ability for identifying new fault classes using very few samples encountered during the operation and update online. Experiments have been conducted on a dataset consisting of 1152 labeled samples belonging to 12 different classes and 10000 unlabeled samples. The accuracy of the proposed method is significantly better than the traditional classifiers.

This paper introduces a new model for optimal wind distributed generation (WDG) allocation based on mixed integer linear programming (MILP) in todays' smart grids considering on-load tap changing (OLTC) and power factor control (PFC) strategies. The objectives of the proposed optimization model are improving voltage stability and energy loss minimization subject to power flow constraints, line thermal limits, maximum number and size of WDG units, penetration limit, discrete OLTC tap position constraints, and PFC constraints. An efficient voltage phasor-information-based probabilistic voltage stability index (VSI) is extracted to measure the improvement of voltage stability with WDGs. Besides energy losses, reduction index is used to measure the energy loss reduction with the integration of renewable WDGs in the distribution system. An efficient linearized power flow (LPF) model as well as piecewise linearized model of the quadratic terms associated to the PFC constraints are represented to convert the original nonconvex problem into the form of a well-known MILP problem, which guarantees optimal solution and computationally is efficient to be solved using powerful commercial solvers. The effectiveness and validity of proposed model is investigated in compared to the state-of-the-art population-based methods and classical models.

Insulated aerial bundled cables (ABCs) are preferred over conventional bare conductor cables in electrical distribution system as ABCs are more safe, less prone to electricity pilferage and offers higher reliability. However, the degradation phenomenon of ABCs is sudden as compared to conventional cables especially in coastal areas. Sudden failures of ABCs in coastal areas make the maintenance planning challenging. Hence, accurate reliability estimation is required which can enable timely maintenance planning and in turn reducing the chances of failures. A novel reliability model is reported in this work which is derived from historical failure data of particular type of ABCs coupled with the degradation models. The models are based upon the actual environmental conditions experienced by the cables under study. The actual loading data as well as environmental data of two sites of varying distance from Seashore are used to develop the respective reliability models. The reliability prediction from proposed reliability model is then validated using time to failure computation through comparison of historical infrared thermography based Non-destructive testing (NDT) data, acquired at the sites under study, with reference to NDT measurements acquired from the ruptured/failed cable. The validation indicates the efficacy of the proposed reliability model.

Repair scheduling and routing and logistics support are interdependent and critical for post-disaster distribution system restoration (PDSR), which is also influenced by the geographical characteristics of outage area. Hence, we develop a co-optimization model for the PDSR with logistics support and geographical characteristics. A hybrid improved bacterial colony chemotaxis algorithm is proposed to solve the model, in which A* algorithm is employed to route repair crews and material delivery in the transportation network considering geographical characteristics, and an improved bacterial colony chemotaxis algorithm is proposed to determine the repair scheduling and material allocation in the distribution system. Different scale of distribution system instances with different damage levels and different geographical characteristics are used to demonstrate the effectiveness of the proposed methodology.

New metrics and a new methodology for determining system infrastructural–operational resilience are presented for the optimal real-time operation of two critical interdependent infrastructure systems—the water distribution systems (WDS) and the electric power system (EPS) under critical conditions of limited water and/or limited electrical energy resulting from extreme drought or electric grid failure, respectively. Operational resilience (OR) and infrastructural resilience are defined. The integrated resilience computation method is presented and utilizes results from a combined optimization–simulation framework, which involves capturing the interactions and associated dynamics between the EPS and WDS. A realistic example of the WDS and EPS is used to demonstrate the application of the resilience concepts to assess the interdependent systems’ performance.

The speed and robustness of fault section location directly affect the resilience of the distribution network when the latter is exposed to extreme events. This article is proposing a fast and robust fault section location method for distribution system considering the outage reports from smart meters in low-voltage network and notifications from remote fault indicators (RFIs) in medium-voltage network. To make section location faster, a proposed location model moves underreporting variables and misreporting variables to offline recognition. To make section location more robust, the location model proposes new constraints of expected RFI states to remove the limitation of multiple faults on different paths to all sources. Simulation results on a utility feeder with distributed generations demonstrate that the proposed method has faster location and better robustness, which is helpful to the resilience enhancement of the distribution network.

The future distribution systems expose to an unprecedented level of uncertainties due to renewable resources, nontraditional loads, aging infrastructure, etc., posing potential risks to secure operation of the system.This article proposes a new technique to estimate the voltage stability margin of the distribution systems with high penetration of renewables.Its convergence and robustness under complex and stressed working conditions are guaranteed in theory. This technique is handy for the operation as it features self-adaptive step size and is applicable to general system topology. It leverages a newly derived analytical solvability certificate based on the Kantorovich fixed-point theorem. A fast version of the proposed technique is duly proposed to speed up the computation up to 8 times while maintaining high accuracy, which lends itself to online and time-sensitive emergency tasks. Numerical simulations with various IEEE test feeders verify the performance of the techniques. Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) This work was supported in part by NTU SUG, MOE AcRF TIER 1- 2019-T1-001-119 (RG 79/19), and in part by EMA & NRFEMA-EP004-EKJGC-0003.

When a single line-to-ground fault occurs in the ungrounded distribution system, the steady-state fault current is relatively small for fault analysis and the transient fault current is observable, which can be used for faulted feeder identification and location. The principal frequency component retains most of the characteristics of the transient current. The principal frequency is related to the distance from the fault point to the substation and can be used for fault location. This paper analyzes the sequence network model of a single line-to-ground fault in the distribution network, and gives a method for principal frequency calculation. Depending on the characteristics of the maximum amplitude of the principal frequency component of the faulted feeder, the method of faulted feeder identification is given. Based on the complementary characteristics of the phase angle of the principal frequency component of the fault current and the phase angle at the substation bus, the faulted section location is carried out. MATLAB simulation is used to verify the effectiveness of the faulted feeder identification and location method.

This paper demonstrates a novel digital radio distribution system able to transmit not only over optical fibres and coaxial cables but also over twisted pair cables. The digitised RF signal is compressed for maximum transmission efficiency in a way that allows for integral self-learning algorithms to be introduced for multi-service applications. © 2013 IEEE.

Publisher Copyright: © 2023 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd. As the load on distribution networks grows, system operators and planners are constantly challenged with the issue of voltage regulation or enhancing the quality of supply to customers at the load end of lengthy distribution lines. This paper presents the optimum determination of series capacitor units in a distribution system to maximize energy-saving and enhance voltage levels. Interestingly, series capacitors can enhance the capability of transmission lines, reduce line losses, enhance the performance of buses with large induction motor loads and reduce voltage flicker. At the same time, the limitations of series compensation are taken into consideration while calculating its optimum values. To achieve the planning objective and optimal load flow objective, two strategies: The Improved Grey Wolf Optimization method (I-GWO) and Tabu Search (TS), are hybridized to get the benefit of their advantages. The I-GWO has a movement strategy called dimension learning-based hunting for enhancing the balance between global and local search and maintaining diversity. The proposed (I-GWO-TS) algorithm can solve mixed-integer programming to achieve the planning and the optimal load flow objectives. The proposed method can be applied to a real Egyptian distribution system that is heavily loaded, with poor voltage regulation, and also has high-power losses. The obtained results demonstrate the capability of the proposed approach to determine optimal series capacitors’ location and sizing for maximization of energy saving. Further, the proposed method improves the network performance regarding the voltage profile and power losses, although the limitations of including series compensation were considered in the distribution system.

This research discusses the goods distribution system in an urban area by considering an odd-even vehicle license plate rule. This rule enables the vehicles with the even-number plate to pass particular roads on even-number dates and vice versa during specific time intervals determined by the authority. This rule is potentially rising the company’s logistic cost up to 20%. Therefore, a Mixed-Integer Linear Programming model is developed to solve the problem. The performance of the model is tested on some numerical examples. Computational results show that the model generates optimal solutions with numerous computational times. The instances of customers located randomly and clustered manner (i.e., mix) are arduous to solve. The average computational time of these instances is 1 hour and 35 minutes.

Pressure control is recognized as an efficient measure for reducing leaks from water distribution systems. We have evaluated the effectiveness of various pressure control modes by means of pilot-operated diaphragm type pressure-reducing valves (PRVs), taking into account the sensitivity of the valves to various settings. First, the response of a PRV to consecutive pressure settings variations was experimentally evaluated in the hydraulic simulation laboratory of National Institute for Scientific Research. These experiments revealed that the studied valve only reacts when variation in the pressure setting corresponds to at least a 1/6 turn of the pilot valve. Second, an actual case study from Quebec City, Canada, was simulated to evaluate the impact of the PRV response on three pressure control modes: fixed control, time-based control, and real-time control (RTC). The results show that RTC of pressure leads to reductions in leakage rate for the studied network but that the PRV operational constraints limit the expected performance of RTC.

Self-healing capability is one of the most critical factors for a resilient distribution system, which requires intelligent agents to automatically perform restorative actions online, including network reconfiguration and reactive power dispatch. These agents should be equipped with a predesigned decision policy to meet real-time requirements and handle highly complex $N-k$ scenarios. The disturbance randomness hampers the application of exploration-dominant algorithms like traditional reinforcement learning (RL), and the agent training problem under $N-k$ scenarios has not been thoroughly solved. In this paper, we propose the imitation learning (IL) framework to train such policies, where the agent will interact with an expert to learn its optimal policy, and therefore significantly improve the training efficiency compared with the RL methods. To handle tie-line operations and reactive power dispatch simultaneously, we design a hybrid policy network for such a discrete-continuous hybrid action space. We employ the 33-node system under $N-k$ disturbances to verify the proposed framework.

Despite many studies have been published on non-technical loss management, there is a lack of solutions focused in the financial return of utilities actions. This paper aims to contribute to fill up this gap, presenting a new approach that maximizes the financial return of utilities when selecting consumers for field inspections. The predicted return of an inspection is calculated considering its operational cost versus the potential of energy recovery and the tariff value. The potential of energy recovery, in turn, is calculated considering the probability of non-technical loss existence and the forecast of unmeasured energy. The Rotation Forest algorithm is utilized to indicate the non-technical loss existence, while the eXtreme Gradient Boosting algorithm is utilized for energy recovery forecast. The proposed approach was applied in a real database of 261,489 consumers from a Brazilian utility. Then, 338 new field inspections were performed on unlabeled consumers in order to corroborate results in a real application. Achieved results showed an increase of up to 11.5 times in the financial return of field inspections when applying the proposed approach. Results could also be used to determine the optimal number of inspections in the utility, for which the financial return is maximum.

The status of switches in distribution systems might be changed for protection purposes or to achieve the operation objectives. However, the system topology should be known for the efficacious management and control of these systems. In most practical systems, due to the lack of enough measurements, the topology cannot be identified accurately and speedily. The forecast output can be transformed into the joint probability density function (PDF) of uncertain parameters, e.g., power demands. The measured data and this PDF are first conflated to update the PDF to best comply with the measurements. The topology identification problem, i.e., finding the probability of each topology given a set of measured values, is converted to a simpler form, i.e., finding the probability of observing these measured values in this topology. These probabilities are then calculated by tracing how the measurements affect the shape of the new consolidated PDF in each topology compared to the original PDF. The proposed technique employs as much data as available, is able to find the accurate probabilities, and particularly is yet quite fast. The mathematical treatment of extracting such probabilities is presented and the proposed technique is validated in numerical studies in terms of accuracy, speed and, versatility

Online and omnichannel retailers are proposing increasingly tight delivery deadlines, moving toward instant on-demand delivery. To operate last-mile distribution systems with such tight delivery deadlines efficiently, defining the right strategic distribution network design is of paramount importance. However, this problem exceeds the complexity of the strategic design of traditional last-mile distribution networks for two main reasons: (1) the reduced time available for order handling and delivery and (2) the absence of a delivery cut-off time that clearly separates order collection and delivery periods. This renders state-of-the-art last-mile distribution network design models inappropriate, as they assume periodic order fulfillment based on a delivery cutoff. In this study, we propose a metamodel simulation-based optimization (SO) approach to strategically design last-mile distribution networks with tight delivery deadlines. Our methodology integrates an in-depth simulator with traditional optimization techniques by extending a traditional black-box SO algorithm with an analytical model that captures the underlying structure of the decision problem. Based on a numerical study inspired by the efforts of a global fashion company to introduce on-demand distribution with tight delivery deadlines in Manhattan, we show that our approach outperforms contemporary SO approaches as well as deterministic and stochastic programming methods. In particular, our method systematically yields network designs with superior expected cost performance. Furthermore, it converges to good solutions with a lower computational budget and is more consistent in finding high-quality solutions. We show how congestion effects in the processing of orders at facilities negatively impact the network performance through late delivery of orders and reduced potential for consolidation. In addition, we show that the sensitivity of the optimal network design to congestion effects in order processing at the facilities increases as delivery deadlines become increasingly tight.

Distributed Generation (DG) integration, especially based on renewable energy resources, has gained great attention by power utilities and frequently utilized in the electrical distribution systems. However, DG integration imposes some risks towards system stability which may lead to system blackouts. This mainly occurs when the grid is decoupled from a portion of the distribution system consisting DGs while the total load demand is greater than total DGs output power. In order to overcome this problem, load shedding technique can be adopted to stabilize the system frequency. However, existing load shedding techniques were unable to accurately estimate the power imbalance due the variation in system loading. This results in excessive/inadequate load shedding to stabilize the system frequency. Moreover, random selection of the loads without load prioritization might cause vital loads to be shed. Therefore, in this paper, a new load shedding strategy for islanded distribution system is proposed. Polynomial regression analysis estimates the power mismatch while MILP optimization estimates optimal load combination for shedding. Furthermore, load priority (i.e., vital, non-vital, and semi-vital) is also considered to avoid disconnecting vital loads. Efficiency of the proposed scheme is evaluated on three different test systems. Validation is performed by modelling the proposed load shedding on PSCAD/EMTDC software for dynamic analysis. From the results, it can be analyzed that the proposed technique is superior compared to other techniques proposed in the literature.

The increased penetration of distributed energy resources (DERs) has enhanced the importance of coordinated operation of transmission system operator (TSO) and distribution system operators (DSOs) in order to better exploit DERs. When TSO and DSOs coordinately operate to optimize overall performance of the system, it does not ensure that the benefit is attained by all participants. To ensure entering TSO and DSOs as subjective and self-interested agents’ coordinated operation, this article introduces a non-cooperative framework for coordinated operation of TSO and DSOs. In the proposed non-cooperative operation approach, TSO and DSOs are considered as subjective agents whose interest is to optimize their own objective functions selfishly while they are interactive and modify their solutions through exchanged boundary signals until the equilibrium is obtained. The effectiveness of the proposed non-cooperative operation approach has been demonstrated through many studies on two integrated test systems. Comparison of simulation results of applying the proposed non-cooperative approach with those of the cooperative ones demonstrates that although the optimal solution is achieved for the whole system in the cooperative operation, some agents cannot obtain a satisfactory solution. Thus, these agents prefer to enter a non-cooperative game with other agents. The proposed non-cooperative game leads to relative benefits for all agents.

The Alpine ski-resorts are conventionally powered by the electrical distribution network to perform the snow-making operations throughout the ski slopes. On one hand, these grids can present a low capacity, and on the other, the line lengths are not negligible due to natural obstacles and altitude changes. As a consequence, the voltage drops are remarkable when several power loads are fed by the low voltage section. Based on this aspect, a novel evolution of ski-resorts power grids toward microgrids is pursued to improve the power system quality of service and to foster the implementation of distributed energy resources (DERs). The article examines the ac electrical distribution system installed in the ski-resort of San Vito di Cadore, Italy. A preliminary power flow analysis identifies bottlenecks on voltage profiles and weights effective solutions to evolve the power grid. Four system configurations are contrasted in terms of voltage drop in order to establish the most convenient redesign. A proper voltage profile along the entire ski-resort is ensured by the last solution, which redistributes the loads powering among the five resort's substations. Finally, a techno-economical-environmental analysis explores the possibility of installing DER and storage to feed the resort loads. The study demonstrates the capability of hydropower plant in enhancing microgrid sustainability and environmental friendliness.

Load growth in electrical distribution networks became naturally occurring due to industrial development and human population demand growth. Consequently, system losses are continually raised while the voltage profile is reduced. This paper presents a novel hybrid method to determine the best locations and sizes of single and multiple of different renewable distributed energy resources (DER). The presented hybrid method is based on Salp Swarm Algorithm (SSA) and combined power loss sensitivity (CPLS). Integration of photovoltaics (PV) and wind turbines (WT) in distribution network is used to enhance the system voltage, minimize system losses and increase the system capacity. The effect of annual load growth in system load and system operating constraints are taken in consideration. IEEE 33-bus and 69-bus radial distribution systems (RDS) are used to validate the presented algorithm for integrating the DERS in distribution system. In addition, the presented algorithm is compared with different recent optimization algorithms in order to prove its effectiveness and superiority.

The distribution system of goods is one of the most important parts for every company. The company certainly has many route options to visit, and this is expected to be conducted efficiently in terms of time. In the distribution of goods by Alfamidi company in Palu City which has 51 outlets include into the category of Traveling Salesman Problem (TSP) because of many route options that can be visited. The problem can be solved by employing the Ant Colony Optimization (ACO) method which is one of the algorithms Ant Colony System (ACS). The ACS acquires principles based on the behavior of ant colonies and applies three characteristics to determine the shortest route namely status transition rules, local pheromone renewal and global pheromones. The result showed that the shortest route of the distribution of goods based on the calculation of selected iterations was ant 1 with the shortest total distance obtained 86.98 km.

In the review of the Indian film The Lunchbox, Peina Zhuang shows that although food is central in human relations and social development in modern India, the transformation of food production and distribution systems at the micro level reveals, resists, and reinforces the conflicts between tradition and modernity. The food in the traditional Bombay lunch remain because of the lunchbox delivery system, but this comes at a cost. While in the very moment that it threatens traditions by, for instance, effacing the caste sources of the food, the lunchbox delivery system reifies the patriarchal relegation of women to the kitchen. Complicated in its implications, The Lunchbox is an entertaining take on India’s rapidly transforming food scene.

This paper presents the application of hydraulic modelling for the prediction of pipe bursts in a water distribution system (WDS). As a case study, more than 1430 km of pipelines within 29 water pressure zones (PZs) in Bendigo and Castlemaine WDSs, located in Victoria, Australia, were modelled and calibrated using an InfoWorks WS hydraulic model. A pressure index (PI) was defined to quantify the intensity of high pressures in the WDS pipes. The PIs for all the PZs were calculated using hydraulic model simulations. Ten years of actual pipe burst data (2007–2017) in the studied WDSs were used in the research. A burst index (BI) was used to measure the burst rate for the length of pipe network within the study area. A mathematical relationship between PI and BI was proposed based on the first eight years (2007–2015) of burst data and the results of the hydraulic modelling in the same period. The number of pipe bursts for the last two years (2016–2017) in each PZ was then predicted according to the proposed mathematical relationship. The predicted number of bursts fitted well with the actual recorded pipe burst data, with a coefficient of determination of 0.98.

Z/T/Γ-source circuit breakers used in flexible DC distribution systems have been rapidly developed due to their advantages of high speed and low cost. However, the precise model of the circuit breaker is generally a high-order circuit, which is difficult to solve. The lack of simplified topology and parameter design considering system parameters (line inductance, line resistance and load capacitance) restricts their applications in practical engineering. Therefore, based on the equivalent mathematical model, a simplified topology that can represent Z/T/Γ-source circuit breakers is proposed and their working principles are revealed in this paper. Considering system parameters, the parameters of Z/T/Γ-source circuit breakers are designed to take care of short circuit fault and step changes in load. Finally, simulation and experiment show that parameters designed by the proposed method can ensure the reliable operation for Z/T/Γ-source circuit breakers.

Both frequency and intensity of natural disasters have intensified in recent years. It is, therefore, essential to design effective strategies to minimize their catastrophic consequences. Optimizing recovery tasks, including distribution system reconfiguration (DSR) and repair sequence optimization (RSO), are the key to enhance the agility of disaster recovery. This article aims to develop a resilience-oriented DSR and RSO optimization model and a mechanism to quantify the recovery agility. In doing so, a new metric is developed to quantify the recovery agility and to identify the optimal resilience enhancement strategies. The metric is defined as “the number of recovered customers divided by the average outage time of the interrupted customers.” A Monte-Carlo-based methodology to quantify the recovery agility of different DSR plans is developed. It will be shown that if the total number of interrupted customers over the recovery horizon is minimized, the metric will be maximized. Accordingly, the DSR and RSO optimization models are modified to maximize the introduced metric. The proposed optimization model is formulated as a mixed-integer linear programming model that can be solved via commercial off-the-shelf solvers. Finally, the proposed methodology is applied to several case studies to examine its effectiveness. It will be also shown how the proposed methodology can be utilized for distributed generator (DG) and tie-line placement problems in planning for enhanced structural resilience.

The main technical challenges in the emerging concept of the micro-grid (MG) and integration of sustainable energy resources in the Distribution System (DS) is the low fault current phenomena in the islanded mode of the MG operation and change in the network topologies with frequent DG connection and disconnection. The existing protection schemes require modification as they may fail to operate because of their inability to adapt to the changes due to the integration of Distributed Generator (DG). Various new protection schemes have been introduced by many researchers for this new concept of Microgrid (MG) that is not only adaptive to the changes in the levels of fault current and network topologies in both grid-connected and islanded modes but also intuitive enough to determine and clear the fault with minimum disturbances in the supply. This paper gives a brief review of the challenges associated with Microgrid protection and presents a critical review of the existing Microgrid protection schemes. The limitations of the existing adaptive protection schemes that need to be overcome to make adaptive protection scheme a viable solution are also presented.

High-impedance faults in power distribution systems is a lasting problem with decades of steady investigation. Due to the complexity of the problem, the field can also be challenging to navigate. Although there exist surveys of the field in the literature, it is not easy to find a comprehensive contextualization of how and when the field developments unfolded. This paper presents the historical narrative of the progress and developments based on the most cited papers since the inception of the field. The accounts are not limited to archaic and obsolete works. They are all contextualized from the seminal papers to contemporary methods and related technology. Quantitative figures on the survey of the methods and relevant knowledge gaps are also discussed at the closing of the paper.

This article proposes a framework as a remedial action scheme (RAS) for close to real-time system operation when system operator becomes aware of possibility of decentralized outages due to simultaneous attacks on several market retailers. The upper level of the framework is an offline RAS where system operator immediately implements a customized reconfiguration preventing the decentralized outages. Due to immediate implementation of upper-level reaction, it is possible to face decentralized congestions in the new topology having minimum reliance on the attacked market retailers. Since severity of congestions is less than that of outages, the lower level of the framework is implemented as an online RAS. In this level, eligible nonattacked market retailers are invited into a secondary market to compete for generation/consumption redispatch and contribute into alleviation of congestions with the purpose of increasing their income. The effectiveness of the proposed framework is validated on a well-known 136-bus distribution system.

Local energy trading (LET) in electrical distribution grid is a concept that implies energy trading between active participants on a local level. Along with it, some market operators and distribution system operators (DSOs) consider adoption of a transactive energy paradigm in distribution system management by providing dynamic price signals to prosumers located in low- voltage grid, based on the conditions in the medium and high-voltage grid. The aim is to increase distribution network reliability on market principles. This work presents a framework for participation of DSOs in LET. LET is simulated as an auction-based platform over a modified IEEE European Low Voltage Test Feeder where methods for active DSO's participation are tested and impacts on power flows and voltages researched. In the case study analysis, the implementation of LEM doubled the local solar PV production in a point where all households had solar PV s and no upstream exports were allowed. The contributions to prevention of voltage deviations were also achieved, but regular voltage management under this paradigm would require new tasks for the DSOs.

El presente artículo analiza el desarrollo de la industria vidriera valenciana entre los siglos XIII y XV. Para ello se recurre a un centenar de documentos de carácter notarial, normativo, judicial y fiscal, procedentes de distintos archivos valencianos. Estos permiten estudiar la localización de los hornos de vidrio en el reino de Valencia y las formas de trabajo de los vidrieros, así como los procesos de distribución y los sistemas de venta del vidrio doméstico. Finalmente, se aborda la demanda y el consumo de estos bienes y sus usos en las viviendas de diferentes sectores sociales de la época. Todo ello invita a reconsiderar la relevancia de esta industria en el reino de Valencia, mucho menos estudiada que sus homólogas catalanas y mallorquinas, en el contexto de la Corona de Aragón y del Mediterráneo noroccidental durante la Baja Edad Media. This essay analyses the development of the Valencian glass industry between the 13th and the 15th centuries. For this purpose, it turns to around a hundred documents from notarial, normative, legal and tax records, placed in various Valencian archives. These reveal the location of glass furnaces in the kingdom of Valencia and the glass-makers’ activities, as well as the sale and distribution systems of domestic glass. Finally, it addresses the demand and consumption of these goods and their usage within the dwellings of various social strata of the period. This all leads to reconsider the relevance of this industry in the kingdom of Valencia, far less studied than its counterparts from Catalonia and Majorca, in the context of the Crown of Aragon and the north-western Mediterranean during the later middle ages.

The optimized designed irrigation scheme and water distribution system to reduce the anthropogenic impact and remove the pollutants by 20–25 % have been presented. The optimal launch sequencing of the irrigation equipment has been introduced by using the study irrigation area under conditions of water resources scarcity to determine the launch sequences regardless the crop rotation used. The presented model allows to bring down the irrigation water consumption by 30 % while decreasing the working cycle of the irrigation material, specifically by reducing the number of land irrigations without any impact on the yield.

The article analyzes reasons of technogenic accidents in the RF. It mentions the key ‘internal’ and ‘external’ reasons of accidents at hazardous production facilities. The article deals with the requirements for ensuring reliable, economical and safe operating modes of the equipment. It sets forth a modern structure for personnel training. Certain scientific and technical requirements and recommendations are offered for simulation of ergatic distribution systems for trainers designed for operation personnel of power generation facilities. The article dwells upon the initial regulations of the power industry in the USSR that set forth the requirements for training and simulator systems.

Актуальность обусловлена, с одной стороны, необходимостью активной газификации крупных территориальных образований (строящихся новых жилых агломераций, коттеджных и дачных поселков, а также крупных промышленных комплексов). С другой стороны, продолжается увеличение общей протяженности газораспределительных систем и усложнение конфигурации схем газопроводов. Перечисленные факторы влияют на надежность работы газораспределительных систем и предъявляют высокие требования со стороны потребителей энергии к безаварийной их работе. Цель. Основная исходная надежностная информация, используемая для анализа надежности газопроводов, - это интенсивности отказов его элементов: отдельных участков линейной части, газоперекачивающих агрегатов и т.д., и интенсивности восстановления этих элементов. Эти показатели характеризуют такие свойства надежности как, безотказность и ремонтопригодность. Цель исследований заключается в оценке влияния показателей безотказности и ремонтопригодности оборудования на интегральные показатели надежности газораспределительной системы (ГС). К ним относятся математическое ожидание, дисперсия и среднеквадратическое отклонение (с.к.о.) пропускной способности ГС, а также коэффициент надежности газопровода. Методы: эквивалентирования, аналитический метод на уровне случайных Марковских процессов - схема «гибели и размножения», теоремы сложения и умножения вероятностей, композиция рядов распределения; математическая модель анализа надежности проектируемого магистрального газопровода (МГ). Результаты. На основе математической модели оценки надежности проектируемого магистрального газопровода и разработанной вычислительной программы были выполнены расчеты по определению интегральных показателей надежности условной газораспределительной системы. Исследования показали, что при изменении исходных показателей надежности (интенсивностей отказов и восстановлений) элементов ГС на одинаковую величину их влияние на изменение интегральных показателей надежности ГС имеет разную силу. Выводы. На основе предложенной математической модели анализа надежности ГС показано влияние показателей интенсивности отказов и интенсивности восстановлений элементов, характеризующих безотказность и ремонтопригодность газотранспортных систем, на ее интегральные показатели надежности, в частности, на коэффициент надежности. The Relevance of the research is due to the need for active gasification of large territorial entities (new residential agglomerations under construction, cottage and dacha settlements, as well as large industrial complexes). On the other hand, the increase in the total length of gas distribution systems and the complexity of the configuration of gas pipeline schemes continues. These factors affect the reliability of the gas distribution systems and place high demands on the part of energy consumers for trouble-free operation. Purpose. The main initial reliability information used for analyzing the reliability of gas pipelines is the failure rates of its elements: individual sections of the linear part, gas pumping units, etc., and the recovery rates of these elements. These indicators characterize such properties of reliability as reliability and maintainability. The purpose of the research is to assess the impact of reliability and maintainability of equipment on the integral reliability indicators of the gas distribution system (GDS). These include the expectation, variance and standard deviation of the throughput of the GDS, as well as the reliability coefficient of the pipeline. Methods: equivalent methods, analytical method at the level of random Markov processes - the scheme of "death and reproduction", the theorem of addition and multiplication of probabilities, the composition of distribution series; mathematical model of reliability analysis of the designed main gas pipeline. Results. On the basis of a mathematical model for assessing the reliability of the designed main gas pipeline and the developed computational program, calculations were performed to determine the integral indicators of the reliability of the conventional gas distribution system. So, studies have shown that when the initial reliability indicators (failure rates and recoveries) of the GDS elements are changed by the same amount, their effect on the change in the integral reliability indicators of the GDS has a different effect. Conclusion. On the basis of the proposed mathematical model for analyzing the reliability of the GDS, the influence of the failure rate indicators and the recovery rate of elements characterizing the reliability and maintainability of gas transmission systems on its integral reliability indicators, in particular, on the reliability coefficient, is shown.

Integrated sensors are installed in water distribution systems for the real-time detection of pipe leakage and contamination. We design a novel strategy for sensor placement to monitor leakages and...

Inventory Management in Stochastic Distribution Systems