Power Distribution Network Research Articles

A practical case study on effect of moisture ingress in power cables and methods to reduce equipment failure

Abstract Over the past few years, there has been a rise in the quantity of underground cables used in power transmission and distribution networks in many urban areas worldwide. Technological and economic considerations, along with space constraints, are responsible for this increase. As the number of cables increases, utilities face challenges in effectively maintaining and testing their condition. Particularly, the maintenance of medium-voltage cables, such as three-core 33 kV cables, is becoming increasingly challenging. One of the biggest problems with medium-voltage cables is their preference when the load is closer to the substation. Because the cables are closer to the source, the probability of the end termination kit failing is higher, leading to short-line faults (SLF). Short-line faults subject the connected switchgear and transformers to severe electrical, thermal, and mechanical stresses. Cable faults can cause equipment failure, resulting in external flashovers, which in turn raise the temperature and ultimately lead to insulator failure. Low external temperatures can increase moisture content in the environment, leading to equipment failure. This paper investigates switchgear failures in 132/33 KV substations caused by cable faults and ambient temperature and presents methods to mitigate switchgear and instrument transformer failures caused by cable faults. Over time, the proposed methods have led to a decrease in the number of failures. In recent years, protocols such as IEC61850, MODBUS, IEC60870-4, and others have transformed conventional substations into automated substations. We propose a low-cost, practically feasible solution using the GOOSE technique in the IEC61850 protocol to prevent the flashover of the circuit breakers, following a detailed investigation.

Evaluation of radiality constraints for power distribution networks

This work carried out an empirical study with the objective of determining the most efficient strategy in guaranteeing the radiality of the distribution network during the reconfiguration. The reconfiguration problem in a distribution network aims to reduce technical losses by changing the paths that energy takes through the network until it reaches consumers. In this problem, a mandatory constraint is to ensure that the network operates radially. However, the literature does not present a consensus on the best way to guarantee this restriction. Computational experiments were carried out using the two main methodologies in the literature: limiting the number of input edges; and search with removal of cycles in each partial solution. A third and new strategy was proposed as an alternative to the literature using the concept of minimal cuts in graphs. Computational tests showed that the strategy of limiting the number of input edges was the most efficient in ensuring radiality. We also point out a drawback in the applicability of this strategy to networks with high penetrations of distributed generation (DG). For this reason, our experiments also analyze the other strategies that are suitable for DG power flows. For this case, we show that the methodology proposed in this paper provides a better way to tackle modern networks arising from applications of smart grids.

Research on Typical Process Mini Programs for Overhead Distribution Lines based on Non Power Outage Operation Technology in Distribution Network

To address the challenges and risks associated with the complex design of distribution network architecture, uneven skill levels of construction personnel, and inadequate training of construction personnel, this article proposes a typical process mini program for overhead distribution lines based on uninterrupted operation of distribution networks. Through requirement analysis, the functions of the mini program were determined, and the front-end and system back-end functions of a typical process mini program for overhead distribution lines based on uninterrupted operation of the distribution network were designed. Based on the development architecture of the mini program and combined with cloud services, a typical process mini program for overhead distribution lines based on uninterrupted operation of the distribution network has been developed. The establishment of a typical process library and knowledge base for overhead distribution lines based on uninterrupted operation of the distribution network has been achieved, making it convenient for users to search, learn, and collect typical processes in a timely manner, and to learn and apply them to maintenance sites anytime, anywhere. The typical process mini program for overhead distribution lines based on uninterrupted operation of distribution network lays the foundation for better leveraging the technical advantages of uninterrupted operation of distribution network, further improving the reliability of distribution network power supply, and ensuring the accuracy of uninterrupted operation of distribution network.

Optimization of In-Motion EV Charging Infrastructure for Power Systems Using Generative Adversarial Network-Based Distributionally Robust Techniques

This paper presents an innovative optimization framework for the co-management of dynamic electric vehicle (EV) charging lanes and power distribution networks, addressing grid stability amidst fluctuating EV charging demands. Integrating generative adversarial networks (GANs) and distributionally robust optimization (DRO), the framework models uncertainties in traffic flow and renewable energy generation, optimizing system performance under worst-case conditions to mitigate risks of grid instability. Applied to a highway with eight dynamic charging lanes (500 kW per lane), serving up to 50 EVs simultaneously, the framework balances energy contributions from 15 renewable generators (60% of the mix) and 10 non-renewable generators. Simulation results highlight its effectiveness, maintaining grid stability with voltage deviations within 0.02 p.u., reducing energy losses to under 0.8 MW during peak traffic (1500 vehicles per hour), and achieving 95% lane utilization. Dynamic charging enabled EV users to save USD 0.08 per kilometer through reduced stationary charging downtime, optimized travel efficiency, and lower energy costs. Additionally, the system minimizes maintenance costs by optimizing lane and grid reliability. This study underscores the potential of GAN-based DRO methodologies to enhance the efficiency of power grids supporting dynamic EV charging, offering scalable solutions for diverse regions and traffic scenarios.

Optimal Siting, Sizing, and Energy Management of Distributed Renewable Generation and Storage Under Atmospheric Conditions

Integrating new generation and storage resources within power systems is challenging because of the stochastic nature of renewable generation, voltage regulation, and the use of microgrids. Classical optimization methods struggle with these nonlinear, multifaceted issues. This paper presents a novel optimization framework for integrating, sizing, and siting distributed renewable generation and energy storage systems in power distribution networks. To accurately reflect load variability, the framework considers four distinct load models—constant impedance, current, power, and ZIP (constant impedance, constant current, constant power). Our approach utilized three metaheuristic approaches to enhance the efficiency of power system management. The validation results on the IEEE 33 Bus System conclude that the Elephant Herding Optimization (EHO) emerged as the best performer regarding voltage stability and real power loss reduction with a voltage stability index of 0.0031346. Modified Ant Lion Optimization (ALO) achieved a best voltage stability index of 0.0024115 and power losses of 7.5092 MVA. The Red Colobus Monkey Optimization (RMO) algorithm realized a voltage stability index of 0.0052053 and real power losses of 20.7564 MVA. Overall, the results conclude that ALO is the most effective approach for optimizing distributed renewable energy systems under different climatic conditions. According to the analysis, the algorithm works best in ideal circumstances when the percentages of wind and irradiance are 60% or greater.

Determination of optimal island regions with simultaneous DG allocation and reconfiguration in power distribution networks

AbstractThe rising demand for electric energy and environmental pollution concerns have led to using renewable energy‐based distributed generators (DGs) in power distribution networks (PDN). However, the power flow may become bidirectional (non‐radial) by introducing the DGs into the system, which may cause instability in the system's operation. System instability causes an increase in system losses and implies a rising in costs. This paper proposes a methodology using Moth Flame Optimizer and Equilibrium Optimizer to reconfigure the PDN, optimizing the siting, sizing, and power factor of multiple DGs to maintain radial mode operation. Determining DGs' allocation within a radial system by optimizing multi‐parameters simultaneously leads to minimizing losses, enhancing reliability, and improving the stability of the network. Thus, the number of affected customers in a catastrophic power outage or emergency blackout scenarios can be minimized. The method has been tested on a 33‐bus distribution system where four different scenarios with three cases for each are studied to show the performance of the proposed method. The method's effectiveness is demonstrated by minimizing power loss, enhancing the voltage stability index, assuring reliability, and improving the voltage profile. Moreover, the accuracy of reliability index calculation results is confirmed with the commercial software ETAP.

Analysis of the effects of electromobility and renewable energy integration on grid power quality

In this work, the effects of renewable energy and electromobility integration into the power distribution network were analyzed. The energy systems (renewable energy sources and electromobility source systems) were modelled in a MATLAB/SIMULINK® environment. The modelled electric vehicle was simulated, and the total harmonic distortion (THD) was obtained before incorporating a passive electronic filter to lessen the effect of electric vehicle (EV) integration on the distribution network. Similarly, renewable energy sources (solar photovoltaic and wind) were integrated into the electromobility model, and their effects on the THD value were determined. It was discovered that the total harmonic distortion was within the acceptable International Electrotechnical Commission (IEC) standard of 5% when the electromobility source had a passive filter incorporated. It was discovered that the filter reduces the THD value from 195% to 0.03% both in Vehicle-to-Grid and Grid-to-Vehicle modes. Thus, filters should be incorporated into EVs to minimize the effect of their integration into the distribution network. This research work is unique because it combines the effects of electromobility (electric vehicle) load, renewable energy sources and passive filters on harmonics.

Mitigating the ferroresonance resulting from HILGF clearing in a remote area 10 kV power distribution network

AbstractTo solve the problem of high impedance line‐to‐ground fault, a solution using isolation transformers for subnetwork divisions was previously implemented in the power distribution network. As a result of that, the network has been experiencing ferroresonance more often. Through modelling and simulation based on its actual parameters on the PSCAD/EMTDC, the understanding of the situation is deepened. The ferroresonance originates from the network response to the high impedance line‐to‐ground fault clearing. The subnetwork division has certainly improved the network fault damping factor, but the line capacitance reduction it caused has exposed the system to ferroresonance. To mitigate the ferroresonance, high‐frequency components are removed from the zero‐sequence current using the morphological filtering; then, through edge detection, it is used as the input signal to the control unit. The control unit then takes the ferroresonance mitigation action intelligently. The simulation results indicate that the proposed method can restore ferroresonance‐induced overvoltage and overcurrent to normal levels within 0.05 s.

Enhancing the reliability and power quality in Burundian power distribution network: sharing an experience

Enhancing the reliability and power quality in Burundian power distribution network: sharing an experience

A Risk Assessment Framework for Large-Scale Synthetic Power Distribution Networks Considering Historical Hurricane Disasters

A Risk Assessment Framework for Large-Scale Synthetic Power Distribution Networks Considering Historical Hurricane Disasters

High‐Impedance Fault Detection in Electric Power Distribution Network Using Local Pattern Transformation Methods and Bidirectional Long Short–Term Memory

High‐Impedance Fault Detection in Electric Power Distribution Network Using Local Pattern Transformation Methods and Bidirectional Long Short–Term Memory

Improvement of load factor in power distribution networks using electric vehicles

Improvement of load factor in power distribution networks using electric vehicles

A novel MODWT–local pattern transformation feature fusion approach for high-impedance fault detection in medium voltage power distribution networks

A novel MODWT–local pattern transformation feature fusion approach for high-impedance fault detection in medium voltage power distribution networks

SGI-YOLOv9: an effective method for crucial components detection in the power distribution network

The detection of crucial components in the power distribution network is of great significance for ensuring the safe operation of the power grid. However, the challenges posed by complex environmental backgrounds and the difficulty of detecting small objects remain key obstacles for current technologies. Therefore, this paper proposes a detection method for crucial components in the power distribution network based on an improved YOLOv9 model, referred to as SGI-YOLOv9. This method effectively reduces the loss of fine-grained features and improves the accuracy of small objects detection by introducing the SPDConv++ downsampling module. Additionally, a global context fusion module is designed to model global information using a self-attention mechanism in both spatial and channel dimensions, significantly enhancing the detection robustness in complex backgrounds. Furthermore, this paper proposes the Inner-PIoU loss function, which combines the advantages of Powerful-IoU and Inner-IoU to improve the convergence speed and regression accuracy of bounding boxes. To verify the effectiveness of SGI-YOLOv9, extensive experiments are conducted on the CPDN dataset and the PASCAL VOC 2007 dataset. The experimental results demonstrate that SGI-YOLOv9 achieves a significant improvement in accuracy for small object detection tasks, with an mAP@50 of 79.1% on the CPDN dataset, representing an increase of 3.9% compared to the original YOLOv9. Furthermore, it achieves an mAP@50 of 63.3% on the PASCAL VOC 2007 dataset, outperforming the original YOLOv9 by 1.6%.

EXPERIENCES AND CHALLENGES OF INTELLIGENT REMOTE CONTROL BREAKER (IRCB) DEVELOPMENT

The growing adoption of digital technologies in power distribution networks has highlighted limitations in traditional substation circuit breaker (CB) control methods, particularly their dependence on dedicated hardware and complex installations. This study addresses these challenges by proposing an alternative solution for Remote Circuit Breaker (RCB) control using mobile devices. The primary objective is to simplify and enhance the operational flexibility of circuit breaker control without requiring extensive infrastructure modifications. The proposed method utilizes mobile devices equipped with a Human-Machine Interface (HMI) that connect directly to network ports located outside power distribution substation buildings. This approach minimizes the need for additional hardware installations and reduces operational complexity. Preliminary findings demonstrate that this solution provides reliable control capabilities while maintaining ease of deployment and cost-effectiveness. The results suggest that adopting mobile-device-based RCB control can significantly streamline substation operations and contribute to the modernization of power distribution systems.

A time-variant power distribution network voltage sag identification method based on the concept of inheritance

The present paper introduces a novel method for identifying voltage sags in time-variant power distribution networks, effectively addressing the challenges arising from the temporal variability of network topology and data. The proposed method is founded on the concept of inheritance, which is bifurcated into breadth and depth inheritance strategies. The breadth inheritance strategy employs transfer learning to manage topological temporality, utilizing the Euclidean distance between samples to ascertain the sequence of sample migration, and implements multitask learning to share feature representations across different tasks. The depth inheritance strategy, on the other hand, utilizes incremental learning to handle data temporality, building upon the initial model parameters to learn new sample features, which in turn reduces the time required for model updates and enhances the accuracy of target tasks. Case study findings validate the suitability of the proposed methods for reconstructing fault identification models in scenarios characterized by topological temporal variability and for rapidly updating fault identification models in scenarios with data temporal variability. The approach presented herein holds significant implications for the enhancement of power supply reliability and the adaptability of electrical grids.

POWER LINE COMMUNICATION SYSTEM

Power Line Communication System (PLCS) is an emerging technology that utilizes existing electrical power infrastructure for data transmission. Devices can exchange data and access communication via the power grid thanks to its ability to provide communication across power lines. This approach has many benefits, including as cost-effectiveness, quick implementation, and broad availability without out the need for additional cabling. Smart grid management, home automation, industrial control systems, and Internet of Things connectivity are just a few of the fields in which PLC has found use This abstract provides an overview of PLCS, highlighting its benefits, challenges, and key technologies. It also discusses the potential of PLCS in transforming power distribution net-works into intelligent and interconnected systems. Additionally, emerging trends and future directions for PLCS research and development are explored, emphasizing the potential for enhanced reliability, speed, and efficiency in data transmission over power lines. This paper proposed a two-way communication from source to load sides using BPSK (Binary phase-shift keying) and QPSK (Quadrature phase-shift keying) modulation techniques. Monte Carlo simulation is used to predict the transformer theoretical channel AWGN (Additive White Gaussian Noise) and compare the efficiency of the proposed methods. To compare the performance curve, randomly chosen data with sizes ranging from 10 k to 50 k are employed. Key Words: Transformer, Transmission line, Arduino nano, ATmega328p

Research on Voltage Stability Strategy of Energy Storage Access to High Penetration Wind and Solar Power Distribution Network System with SOP (Soft Open Point)

Research on Voltage Stability Strategy of Energy Storage Access to High Penetration Wind and Solar Power Distribution Network System with SOP (Soft Open Point)

Evaluating Hydrogen Storage Systems in Power Distribution Networks: A Comparative Study with Battery Storage

Evaluating Hydrogen Storage Systems in Power Distribution Networks: A Comparative Study with Battery Storage

Power Line Communication System

Power Line Communication System (PLCS) is an emerging technology that utilizes existing electrical power infrastructure for data transmission. Devices can exchange data and access communication via the power grid thanks to its ability to provide communication across power lines. This approach has many benefits, including as cost-effectiveness, quick implementation, and broad availability without out the need for additional cabling. Smart grid management, home automation, industrial control systems, and Internet of Things connectivity are just a few of the fields in which PLC has found use This abstract provides an overview of PLCS, highlighting its benefits, challenges, and key technologies. It also discusses the potential of PLCS in transforming power distribution net-works into intelligent and interconnected systems. Additionally, emerging trends and future directions for PLCS research and development are explored, emphasizing the potential for enhanced reliability, speed, and efficiency in data transmission over power lines. This paper proposed a two-way communication from source to load sides using BPSK (Binary phase-shift keying) and QPSK (Quadrature phase-shift keying) modulation techniques. Monte Carlo simulation is used to predict the transformer theoretical channel AWGN (Additive White Gaussian Noise) and compare the efficiency of the proposed methods. To compare the performance curve, randomly chosen data with sizes ranging from 10 k to 50 k are employed