Underground Distribution Systems Research Articles

Deep learning-based detection of qanat underground water distribution systems using HEXAGON spy satellite imagery

Qanats are a remarkable type of ancient hydraulic structure for sustainable water distribution in arid environments that use subterranean channels to transport water from highland or mountainous areas. The presence of the qanat system is marked by a line of regularly spaced shafts visible from the surface, which can be used to detect qanats using satellite imagery. Typically, qanats have been documented by field mapping or manual digitisation within a Geographic Information System (GIS) environment. This process is time-consuming due to the numerous shafts within each qanat line. However, several automated methods for detecting qanat structures have been explored, using techniques such as morphological filters, custom convolutional neural networks (CNN) and, more recently, YOLOv5 and Mask R-CNN. These approaches used high-resolution RGB images and CORONA images. However, the use of black and white CORONA in CNNs has been limited in its applicability due to a high rate of false positives.This paper explores the potential of YOLOv9 in processing the black and white HEXAGON (KH-9) high-resolution spy satellite system launched in 1971. Two areas in Afghanistan (Maiwand) and Iran (Gorgan Plain) were selected to train the system images extracted from HEXAGON imagery and artificial synthetic data. The training dataset was augmented using the Albumentation library, which increased the number of tiles used. The model was tested using two types of HEXAGON imagery for selected areas in Afghanistan (Maiwand), Iran (Gorgan Plain) and Morocco (Rissani), and CORONA imagery in Iran (Gorgan Plain).Our study provided a model capable of predicting the location of qanat shafts with a precision of over 0.881 and a recall of 0.627 for most of the case studies tested. This is the first case study aimed at detecting qanats in different landscapes using different types of satellite imagery. Using real, augmented, and artificial data allowed us to generalise the representation of qanats into lineal groups of circular features. Thanks to applying labelling for individual qanats and their pairs as separate classes, our approach eliminated most of the isolated and clustered false positives.

Analysis of Underground Distribution System Models for Secondary Substations

In Korea, the demand for complete underground installation of power distribution equipment installed on roads and green areas is increasing. In addition, KEPCO is making efforts to build a more reliable system for the underground distribution system. To meet these needs, this paper proposes the S-substation. In the S-substation, an RMU, a large power transformer, and an LV-Board (including ATCB and MCCB) are installed within the underground structure. This paper proposes three models to apply the S-substation to the underground distribution system. Power flow analysis is conducted for each model by simulating a variety of loads and DERs, and the frequency fluctuations are also examined under different distribution system events. An economic analysis is also conducted to select the optimal model. The economic analysis focuses on VOLL and construction costs. Based on power flow and economic analysis, one model is selected, and the underground distribution system that the model is applied is presented.

Power-Flow Simulations for Integrating Renewable Distributed Generation from Biogas, Photovoltaic, and Small Wind Sources on an Underground Distribution Feeder

The rapid expansion of distributed generation leads to the integration of an increasing number of energy generation sources. However, integrating these sources into electrical distribution networks presents specific challenges to ensure that the distribution networks can effectively accommodate the associated distributed energy and power. Thus, it is crucial to evaluate the electrical effects of power along the conductors, components, and loads. Power-flow analysis is a well-established numerical methodology for assessing parameters and quantities within power systems during steady-state operation. The University of São Paulo’s Cidade Universitária “Armando de Salles Oliveira” (CUASO) campus in São Paulo, Brazil, features an underground power distribution system. The Institute of Energy and Environment (IEE) leads the integration of several distributed generation (DG) sources, including a biogas plant, photovoltaic installations, and a small wind turbine, into one of the CUASO’s feeders, referred to as “USP-105”. Load-flow simulations were conducted using the PowerWorldTM Simulator v.23, considering the interconnection of these sources. This dataset provides comprehensive information and computational files utilized in the simulations. It serves as a valuable resource for reanalysis, didactic purposes, and the dissemination of technical insights related to DG implementation.

Experimental studies of crack growth kinetics and bearing capacity of steel pipes of underground water distribution systems

It was established that the value of the critical stress SK for all experimental steels increases with the increase in the service life, and the impact viscosity decreases, which indicates the structural embrittlement of the pipe steels associated with their sudden flooding. It is shown that the new 20 FA steel has the highest visco-plastic properties and resistance to brittle fracture, which is economically modified with a carbide-forming element (vanadium) and has a fine-grained structure and a low conten to fharm fulimpurities (sulfur, phosphorus). The microstrain of the α-Fe crystallattice, as well as the quantitative decay of cementite andt here distribution of carbon between ferrite and pearlite, were estimated by X-ray diffraction methods. The new steel grade 10FA is recommended for use in the construction of oil and gas pipelines and, for example, bridge structures, which are constantly under cyclic loads with simultaneous contact with a corrosive and aggressive environment. For the first time, the influence of thes ervice life of oil pipelines on the hydrogen content and microcracks in pipe steels of oil pipelines was determined.

Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT

Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly.

More efficient sources of water distribution for agricultural and general usage

Current irrigation systems that disperse water above ground waste an enormous amount of fresh water. Since fresh water is a limited resource, new irrigation systems are desperately needed to make agriculture more sustainable. To investigate this issue, we tested two new watering systems for water efficiency and successful plant growth compared to traditional overhead sprinklers, systems that spray droplets of water (similar to rainfall) from above, with sesame plants. One system utilizes an underground pipe to distribute water intermittently; the other utilizes an underground cloth saturated with water to provide a continuous and gradual diffusion of water to plants. We hypothesized that both underground methods would be more efficient than the sprinkler method, saving more water and resulting in comparable plant growth. Given that sesame plants have been shown to prefer well-drained soil (and do not do well in standing water), we suspected that the cloth method would be more effective at delivering the minimal amount of water needed for these plants. We found that the underground cloth-based water diffusion method saved more water compared to the other distribution systems; however, it also resulted in a slight reduction of the yield (plant growth). The underground pipe-based water distribution system outperformed the sprinkler system (used less water); however, it still produced the same yield. Based on these experimental results, we propose substitution of the conventional overhead sprinkler watering system with underground methods such as a pipe- based water distribution system or cloth-based water diffusion system to conserve water.

SOLID INSULATION DISTRIBUTION TRANSFORMER

Underground transformers with insulating oil as insulating and cooling medium have been used since the early 1960s. It adopts mineral oil, ester oil and silicone oil and the enclosure is made of corrosion resistant stainless steel. Underground, submersible and environmental conditions in which the transformer is installed are exposed to sewage, rain and surrounding chemicals. If liquid filled transformers leak due to corrosion or other damage to the tank the liquid can contaminate the surrounding soil and underground water and restoration costs can be higher than installing a new transformer. In addition, the potential risk of explosion and fire caused by the transformer failures play a role of spreading the fire, which further increases safety concerns. There has been a demand for new technology to solve these problems. This document provides technical information of a new underground, solid insulation distribution transformer (SIDT) for building a safe and eco-friendly underground distribution system.

Verification of fault location by TDR measurement on an actual line including multiple ground-mounted equipment

Currently, as a method of identifying fault location on a distribution line, Time Domain Reflectometry (TDR) measurement has been studied. In this study, the fault part is identified by injecting a pulse wave into the distribution line, measuring the reflected wave at the fault point, and comparing the difference between the waveforms before and after the fault. A Previous studies have shown that TDR measurements can be applied to overhead distribution system[1,2]. This paper reports that the fault location by TDR measurement using pulse waves is effective for the underground distribution system as well as the overhead distribution system, with verification on an actual line including multiple ground-mounted equipment.

Power Flow and Economics Analysis for RMU-based Low-voltage Distribution Networks Operation

To improve the reliability of the underground distribution system, KEPCO is considering the RING system. According to this, changes are needed in the low voltage distribution system currently supplied radially, so in this paper, we intend to analyze the power flow and suggest the optimal network for selecting a model suitable for the RING system and U-CDS (Underground Compact Distribution Station).

Economic Analysis for Replacement of 11kV overhead Koteshwor Feeder by Underground Distribution System

Cost effective, Aesthetic and Reliable energy supply is the need of any mankind. In this study, economic analysis for replacement of 11 kV overhead distribution feeder by 11kV underground cable is done with reference to Koteshwor Feeder under Baneshwor Distribution and Consumers Service. The reliability indices like SAIDI, SAIFI, ENS etc. is performed by using DigSilentPowerFactory software. The reliability of overhead distribution system is evaluated by using real system data system and similarly, historical IEEE standard data is used for underground distribution system. The reliability indices are compared for both distribution systems. Result shows that interruption in the overhead system is more than underground distribution system, the energy not supplied to the customer by overhead distribution system is also more than underground distribution system. The replacement cost estimation is performed by using Nepal Electricity Authority (NEA) unit rate and KEI industries quoted price for NEA underground project. The B/C ratio and Present Worth value for the 25-year period of useful life shows that the replacement of the existing overhead distribution system by underground distribution system is financial suitable and can be payback by revenue save from the Energy Not Supply (ENS) lower value of underground distribution system than overhead distribution system. In order to get the continuous of supply, esthetic and public safety in electricity distribution field one may have to bear initially extra cost to use underground distribution systems which finally get payback. Thus, in case of densely populated city like Kathmandu, underground distribution system is reasonable requirement for continuous supply, esthetic and public safety in electricity distribution filed.

Decision support tool for enabling resiliency in an underground power distribution system

Natural disasters cause substantial damage to power distribution infrastructure with long duration of power outages. A resilient Power Distribution System (PDS) should be able to quickly absorb, adapt and recover from the catastrophic events. Enabling resiliency in the PDS is a new imperative for utilities to reduce financial losses, enhance customer satisfaction and supply critical loads in the network. Modern underground PDS comprise of underground feeders and overhead components. Though, these PDS are considered to be highly reliable; however, they still remain vulnerable to catastrophic events by virtue of their locations, age, maintenance and other factors. These factors have a direct impact on resiliency assessment of the system. Quick and accurate decision making by the network operator during and immediately after a natural disaster can make significant impact on the restoration of the system, particularly critical loads. This paper proposes a set of metrics for evaluation of resiliency for underground power distribution networks and a decision support tool for the network operator to enable resiliency in a PDS during network planning and operational contingency scenarios. It facilitates the decision making process to supply all critical loads in the network under all possible scenarios. The proposed decision support tool to enable resiliency is tested through simulation study on a real 110 Bus, 11 kV, underground PDS of CESC Limited, in Patuli area of Kolkata, India.

Photovoltaic Maximum Penetration Limits on Medium Voltage Overhead and Underground Cable Distribution Feeders: A Comparative Study

This paper investigates the maximum photovoltaic (PV) penetration limits on both overhead lines and underground cables medium voltage radial distribution system. The maximum PV penetration limit is estimated considering both bus voltage limit (1.05 p.u.) and feeder current ampacity (1 p.u.). All factors affect the max PV penetration limit are investigated in detail. Substation voltage, load percentage, load power factor, and power system frequency (50 Hz or 60 Hz) are analyzed. The maximum PV penetration limit associated with overhead lines is usually higher than the value associated with the underground cables for high substation voltage (substation voltage = 1.05 and 1.04 p.u.). The maximum PV penetration limit decreases dramatically with low load percentage for both feeder types but still the overhead lines accept PV plant higher than the underground cables. Conversely, the maximum PV penetration increases with load power factor decreasing and the overhead lines capability for hosting PV plant remains higher than the capability of the underground cables. This paper proved that the capability of the 60-Hz power system for hosting the PV plant is higher than the capability of 50 Hz power system. MATLAB software has been employed to obtain all results in this paper. The Newton-Raphson iterative method was the used method to solve the power flow of the investigated systems.

A Dynamic-SUGPDS Model for Faults Detection and Isolation of Underground Power Cable Based on Detection and Isolation Algorithm and Smart Sensors.

This paper proposes a SUGPDS model based on Detection and Isolation algorithm and smart sensors, namely micro phasor measurement unit, smart sensing and switching device, phasor data concentrator, and ZigBee technology, etc. for the identification, classification, and isolation of the various fault occurs in the underground power cable in the distribution system. The proposed SUGPDS is a quick and smart tool in supervising, managing, and controlling various faults and issues and maintaining the reliability, stability, and uninterrupted flow of electricity. First, the SUGPDS model is analyzed using a distributed parameter approach. Then, the proper arrangement of the system required for the implantation of SUGPDS is demonstrated using figures. The Phasor data concentrator plays an essential role in developing the detection and classification report for identification and classification. Finally, smart sensing and switching device installed at a different location isolated the faulty phase from a healthy network. This approach helps to decrease power consumption. Hence, SUGPDS has super abilities compared to the underground power distribution system. The effectiveness of the proposed method and model is demonstrated via figures and tables.

Detection and Location of Aged Cable Segment in Underground Power Distribution System Using Deep Learning Approach

Aged cable segments in underground power distribution systems will gradually develop into severe faults. The location of aged cable segment is essential for ensuring system reliability and reducing maintenance cost, but is rarely studied by the existing research. In this article, a novel aged cable segment detection and location method based on wide frequency range transfer function (TF) measurement and deep learning approaches is proposed to fill the gap. The relationship between the measured TF and cable ageing parameters is analyzed, and two models with combined sparse autoencoder and convolutional neural network are trained to estimate the aging location and severity. A transfer learning approach is further developed to improve the model performance for various online situations. Experiments are conducted which prove the effectiveness and generalization ability of the proposed method. Compared with existing approaches, the proposed method shows better performance under different ageing situations, even smooth ageing scenarios.

Planificación Óptima de Alimentadores Primarios en Redes de Distribución Subterráneas empleando Algoritmos Heurísticos

En el presente artículo se presenta una propuesta metodológica para la planificación tipo Greenfield de sistemas de distribución eléctrica subterránea, empleando técnicas de Programación Dinámica y optimización basadas en algoritmos heurísticos. La metodología tiene como objetivo, la búsqueda de una solución óptima local que permita determinar la cantidad mínima necesaria de equipos de maniobra, conjuntamente con el número asociado de circuitos primarios en configuración topológica Open Loop (OL) y su trazado óptimo en el plano urbano georreferenciado.
 Para resolver los diferentes problemas de optimización se emplean varios algoritmos heurísticos, tal es así que: para determinar el número óptimo de equipos de maniobra y sus circuitos primarios asociados se emplea el Algoritmo Genético (AG), en el trazado de los primarios OL el algoritmo de Optimización de Colonia de Hormigas (ACO) y para la sectorización espacial de los circuitos primarios se aplica el algoritmo K-medoids.
 Se requiere como parámetros de entrada, las coordenadas geográficas y la potencia de los centros de transformación de medio voltaje a bajo voltaje (CT MV/BV), así como el grafo georreferenciado de las vías en la zona de estudio.
 Para la implementación práctica de la propuesta metodológica se desarrolló una herramienta computacional en Matlab, la cual fue empleada para la elaboración de la planificación de la red eléctrica subterránea de un amplio sector urbano de la ciudad de Ambato con una superficie de 2.97 km².

Reliability and Network Performance Enhancement by Reconfiguring Underground Distribution Systems

Contemporary distributions are now going to underground their overhead distribution lines due to techno-social reasons. Reliability and loss reduction are the two prime objectives for distribution system operation. Since failure rates of ungrounded cables are the function of Joules heating besides their physical lengths, the reliability evaluation of undergrounded distribution systems needs to be reviewed. This paper suggested a suitable modification in existing reliability indices in order to make them more appropriate for underground distribution systems. A multi-objective network reconfiguration problem is formulated to enhance the reliability and performance of distribution systems while duly addressing the variability and uncertainty in load demand and power generation from renewables. The application results on a standard test bench shift the paradigm of the well-known conflicting nature of reliability and network performance indices defined for overhead distribution systems.

Optimized artificial neural network to improve the accuracy of estimated fault impedances and distances for underground distribution system.

This paper proposes an approach to accurately estimate the impedance value of a high impedance fault (HIF) and the distance from its fault location for a distribution system. Based on the three-phase voltage and current waveforms which are monitored through a single measurement in the network, several features are extracted using discrete wavelet transform (DWT). The extracted features are then fed into the optimized artificial neural network (ANN) to estimate the HIF impedance and its distance. The particle swarm optimization (PSO) technique is employed to optimize the parameters of the ANN to enhance the performance of fault impedance and distance estimations. Based on the simulation results, the proposed method records encouraging results compared to other methods of similar complexity for both HIF impedance values and estimated distances.

Neuro-Fuzzy Access for Detection of Faults in an Underground Cable Distribution System

Nowadays, the interest of power system engineers In Indian Power System has increased towards the use of underground cables with the advent of cross-linked polyethylene (XLPE) insulated cables having high capacity for transmission of power. Underground cables are preferred in the densely populated regions where there is environmental constraint and right of way poses a big problem. The key limitation of underground cable is to locate and detect different types of faults in view of the fact that the cables are lying down under the surface. It is necessary that the fault must be cleared in minimum time on account of protection issues. As conventional methods for detection and classification of faults are time consuming, so, this work uses intelligent techniques for fast and more accurate detection of location and classification of faults in underground cables. Overall work has been performed in three steps, the first step is to develop a MATLAB/Simulink Model of a distribution system using underground cable with a provision to develop fault. In second step, an Artificial Neural Network (ANN) using DWT is used for fault detection & classification. In third step, ANN is hybridized with fuzzy system and discrete wavelet transform (DWT) methods to improve its performance. The training sets of adaptive neuro fuzzy inference system (ANFIS) are energy components of three phases of cable under fault (used as inputs) and fault type or different distances of faults in the cable(used as outputs). All the simulations have been carried out in MATLAB/ SIMULINK environment

IoT-based water demand forecasting and distribution design for smart city

Abstract The percentage of fresh water resource availability in the world is diminishing every year. According to a world economic forum survey, the increase in water demand will result in high scarcity globally in the next two decades. The eradication of the water demand increase and reducing the losses during the transportation of water is challenging. Thus accordingly, an Internet of Things (IoT)-based architecture integrated with Fog for underground water distribution system has been proposed. Towards designing an IoT water distribution architecture for a smart city, we need to first forecast the water demand for consumers. Hence, accordingly, water demand forecasting has been carried out on a daily basis for a period of three months as a case study using autoregressive integrated moving average (ARIMA) and regression analysis. Based on water demand forecasting analysis, a water distribution design for an IoT-based architecture has been carried out using hydraulic engineering design for proper distribution of water with minimal losses which would result in the development of a smart water distribution system (SWDS). This has been carried out using EPANET.

A study on detection water leakage of underground metal and PVC pipes using ground penetrating radar

Ground Penetrating Radar (GPR) is a high resolution electromagnetic techniques that is designed primarily to investigate the shallow subsurface of the earth, building material, roads and bridges. GPR was also able to detect water leaks in the underground distribution system. A series of laboratory experiments were conducted to determine the validity and effectives of GPR technology in detecting water leakage using two different types of pipes which are metal and polyvinyl chloride (PVC) pipes. Experiment was conducted using GPR 800 MHz antenna using 4 inch pipe with diameter of hole is ¼ inch to stimulate the leakage. GPR identify leaks in buried water pipes either by detecting underground voids created by the leaking water as it erodes the material around the pipe or by detecting anomalous change in the properties of the materials around pipes due to the water saturation.