Medium Voltage Overhead Research Articles

Preventive Maintenance as a Key to Reliable Power Distribution in Indonesia

This study investigates the frequent disturbances in a 20 kV Medium Voltage Overhead Line (SUTM) distribution network, identifying both internal channel issues and external disruptions such as natural events and wildlife interference as primary factors. The research evaluates the effectiveness of Right Of Way (ROW) maintenance, a preventive strategy involving tree trimming, pole realigning, and component replacement. Results demonstrate that ROW maintenance significantly boosts network reliability and effectiveness, suggesting that systematic preventive maintenance is crucial for improving power distribution resilience globally. Highlights: Swift disruption resolution: Prompt response is vital for network reliability. Internal and external factors: Disturbances arise from channel issues and external elements. Preventive maintenance: ROW approach enhances network efficiency, tackling various issues. Keywords: Distribution Network Disruption, ROW Maintenance, Medium Voltage Air Line Maintenance

Long‐term and multi‐objective maintenance scheduling of medium voltage overhead lines based on LP metric method

AbstractPlanning maintenance of medium voltage overhead lines is one of the most important issues in the studies on power distribution network, which will prevent and reduce unwanted interruption. In this paper, long‐term maintenance of medium voltage networks was planned by multi‐objective function, including an extended mixed‐integer linear model to optimize costs, energy not supplied (ENS), and average interruption duration index (SAIDI). In addition, the uncertainty about the annual growth rate of the load, the increase in the cost of goods and services and the increase in the selling price of energy as well as various constraints are all included in the desired objective function, which is one of the main innovations of this paper compared to other published studies. To apply the uncertainties, information gap decision theory (IGDT) has been used, and to solve the objective functions, LP‐Metric method has been used. The proposed method was implemented on the standard 11‐bus RBTS network by MATLAB and GAMS. The results showed that three different long‐term maintenance plans proposed here lead to the optimization of the annual maintenance costs of network, reduction in ENS and interruption, and increase in the reliability of the network based on the uncertainty of each feeder.

Energy Harvesting Device for Smart Monitoring of MV Overhead Power Lines-Theoretical Concept and Experimental Construction.

Modern technological advancements have opened avenues for innovative low-energy sources in construction, with electric field energy harvesting (EFEH) from overhead power lines serving as a prime candidate for empowering intelligent monitoring sensors and vital communication networks. This study delves into this concept, presenting a physical model of an energy harvester device. The prototype was meticulously designed, simulated, constructed, and tested, to validate its foundational mathematical model, with implications for future prototyping endeavors. The findings illustrate the potential of harnessing ample power from this device when deployed on medium-voltage (MV) overhead power lines, facilitating the monitoring of electric and meteorological parameters and their seamless communication through the Internet of Things (IoT) network. The study focused on the medium voltage applications of the harvester. Two dielectric materials were tested in the present experiments: air and polyurethane. The measurement results exhibited satisfactory alignment, particularly with the air dielectric. Nevertheless, deviations arose when employing polyurethane rubber as the dielectric, due to impurities and defects within the material. The feasibility of generating the requisite 0.84 mW output power to drive process electronics, sensors, and IoT communications was established. The novelty of this work rests in its comprehensive approach, cementing the theoretical concept through rigorous experimentation, and emphasizing its application in enhancing the efficacy of overhead power line monitoring.

A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line

We introduce a data set obtained via a contactless antenna method for detecting partial discharges in XLPE-covered conductors used in medium-voltage overhead power transmission lines. The data set consists of almost three years’ worth of data, collected every hour from 9 measuring stations in Czechia and Slovakia. Each sample in the data set represents a single signal gathered for 20 ms. The contactless method is deployed on the same stations as the galvanic contact method, which is used by power distributors and can provide ground truth. Also manually curated data by human expert are present. Successful detection of partial discharges can prevent electricity shutdowns and forest fires resulting from insulation failure due to vegetation contact. The data set is particularly relevant for covered conductors used in mountainous regions where establishing a safe zone is challenging. The contactless method offers advantages such as cheaper and easier installation. The data set has the potential to develop machine learning models to detect partial discharges and facilitate safer and cheaper use of covered conductors.

Improving the efficiency of medium voltage (MV) distribution lines using risk matrix for optimized maintenance

Medium Voltage overhead lines within North-West power utility companies in South Africa are confronted by higher volumes of deficiencies leading to frequent power failures. An essential quality of service factor considered in power distribution is the electricity supply to customers free of interruptions. Due to the higher number of electrical power line faults associated with the power system life span, achieving the desired level of reliability becomes an enormous task. The paper shares the findings of a study on performance improvement of MV distribution overhead lines using a risk matrix for deficiency analysis and clearing of such defects. A pilot study was conducted, and the risk matrix strategy developed in the study improved the reliability and key performance indicators by trimming down the overhead power line deficiencies. Defect clearing lowered outage frequency, durations, and power losses. The System Average Interruption Duration Index (SAIDI) was enhanced by lowering the outage duration by 108.64 h annually. The System Average Interruption Frequency Index (SAIFI) improved by reducing the outage frequency by 45.45 sustained occurrences annually and Reticulation Supply Loss Index (RSLI) by 8.31 MVA monthly.

Hybrid steel–composite cross-arm for distribution power lines

This paper describes the development of electrically insulating hybrid steel–composite cross-arm for medium-voltage overhead distribution power lines with three conductors. The main goal was to achieve substantial weight savings compared to a common steel cross-arm with three ceramic insulators widely used in the Czech Republic. The structure has been designed as a combination of two main composite components – a pultruded horizontal profile and a braided vertical conical tube. These components are connected by a steel locking component which also serves for attaching the whole cross-arm to common concrete utility poles. The hybrid cross-arm is conceived to insulate electrical current in the default configuration thanks to the properties of the glass fiber reinforced composite materials, yet additional insulating elements can be used to further increase the electrical insulation distance. The materials and components used for the construction are chosen by combining finite element simulations of mechanical and electrical behavior with experimental testing and verification of important characteristics on selected substructures. The final design of the cross-arm is then manufactured and subjected to long-term testing in real-life environmental conditions. The achieved reduction of weight exceeds 50% while maintaining the mechanical rigidity and strength of the steel solution as well as the required insulation properties. The future trend of the cross-arm development is aiming at the weight reduction and increase of manipulation capabilities resulting in lowering many additional costs. In this work the designed cross-arm has half the weight of the original one.

Optimization of Medium Voltage Overhead Line Design for PT Algae Marine Life at PT PLN Kariango Customer Service Unit

The addition of premium customers at PLN ULP Kariango has an impact on the electricity supply burden borne by PLN. This study uses an experimental research model. These designs will be tested and graded based on established standards. Data collection was carried out by observing and opening data specifications for electric power system equipment. Data analysis in this study used ETAP software. For Option 1 the SUTM design does not meet the technical requirements because there is a % power loss of 16.3 % and a % voltage drop of 31.1 %. For financial analysis, option 1 was not implemented because the technical requirements were not met. For the 2% option, the power loss of 46.2% does not meet the technical requirements. For financial analysis option 2 already meets the requirements. For option 3, the technical criteria for shrinkage is 10.87% and the voltage drop is 0.4%, which fulfills the technical requirements. For financial analysis, option 3 already meets the financial requirements. So that the results of the optimization of the three SUTM designs were chosen the best option 3 SUTM design.

Polymeric composite crossarms as an alternative to a traditional metallic solution on E-REDES medium voltage overhead networks

Polymeric composite crossarms as an alternative to a traditional metallic solution on E-REDES medium voltage overhead networks

Single point lidar technology for ground clearance measurement in medium voltage overhead lines with the deployment of Unmanned Aerial System (UAS) in TNB distribution network division

Single point lidar technology for ground clearance measurement in medium voltage overhead lines with the deployment of Unmanned Aerial System (UAS) in TNB distribution network division

Construction Schedule of Medium Voltage Overhead Distribution Network Optimization Based on Neural Network Algorithm

INTRODUCTION: The medium voltage overhead distribution network is a complex planning problem, and monitoring the construction progress of the medium voltage overhead distribution network is an important aspect of the planning problem. Regarding the structure of the medium voltage overhead distribution network, it is one of the important components in China's distribution network system. If the construction progress of the medium voltage overhead distribution network is optimized, it will affect the normal operation of the entire power grid system in a certain region. Optimizing the construction progress of medium voltage overhead distribution networks using modern development related technologies or algorithms is one of the practical research topics. OBJECTIVES: To better predict various issues that may arise during the construction progress of the distribution network. Complex geographical conditions lead to construction difficulties, and lack of technology leads to frequent stoppages of construction, further leading to frequent power outages in various regions. In terms of the overall power supply system, the reliability of power supply is not high. METHODS: By comparing the BP neural network algorithm with the CNN network algorithm, the actual operation effect is evaluated by experts. RESULTS: This article predicts the implementation progress of the medium voltage overhead distribution network, and the results show that the accuracy of the BP model for predicting the construction progress of the medium voltage overhead distribution network can reach 88%; The accuracy of the CNN medium voltage overhead distribution network construction progress prediction model reaches 77%. CONCLUSION: The use of neural network algorithms to optimize the construction schedule of medium voltage overhead distribution networks has been evaluated by experts in practical applications, and the medium voltage overhead distribution network in power supply systems has potential application value.

Long-term maintenance planning of medium voltage overhead lines considering the uncertainties and reasons for interruption in a real distribution network

Long-term maintenance planning of medium voltage overhead lines considering the uncertainties and reasons for interruption in a real distribution network

Analysis of Maintenance Optimization on Medium Voltage Overhead Lines (SUTM) in Reducing Energy Not Supplied (ENS) at PT. PLN (Persero) ULP Tarakan

The background of this research is an analysis of equipment disturbances that occur in distributing electrical energy. The disturbance is a blackout. Power outages cause a decrease in the continuity of service to customers and result in a lot of loss of electrical energy that is not distributed to customers. The research objectives are to find out the optimization technique of distribution network maintenance, how to reduce the value of energy not supplied (ENS), find out the losses due to ENS, and find out the total electrical energy distributed after preventive maintenance is carried out. This research uses a preventive maintenance method, which is maintenance that can prevent unexpected damage to distribution system networks and equipment. This research optimized preventive maintenance actions by reducing disturbances after preventive maintenance from 7 disturbances in February to 2 disturbances in March. Before preventive maintenance, the loss due to ENS amounted to Rp. 36,192,017.626, and the total electrical energy not distributed was 25,025.76 kWh. After preventive maintenance, there was a significant decrease in the total loss due to ENS of Rp. 953,516,447, and the amount of electrical energy not distributed was 659.28 kWh. This research can increase maintenance efficiency due to electrical energy losses by 97.36% at the time interval when this research data is managed when data collection is carried out in the field.

ML-Assistant for human operators to solve faults and classify events complexity in electrical grids

Nowadays, human operators at grid control centers analyze a large volume of alarm information during outage's events, and must act fast to restore the service. Currently, after the occurrence of short-circuit faults and its isolation via feeder protection, fault location and isolation is achieved via remotely controlled switching actions defined by operator's experience. Despite operator's experience and knowledge, this makes the process sub-optimal and slower. This paper proposes two novel machine learning-based algorithms to assist human operator decisions, aiming to: i) classify the complexity of a fault occurrence (Occurrences Classifier) based on its alarm events; ii) provide fast insights to the operator on how to solve it (Data2Actions). The Occurrences Classifier takes the alarm information of an occurrence and classifies it as a “simple” or “complex” occurrence. The Data2Actions takes a sequence of alarm information from the occurrence and suggests to the operator the more adequate sequence of switching actions to isolate the fault section on the overhead medium voltage line. Both algorithms were tested in real data from a Distribution System Operator between 2017 and 2020, and showed i) an accuracy of 86% for the Data2Actions, and ii) the Occurrences Classifier reached 74% accuracy for “simple” occurrences and 58% for “complex” ones, leading to an overall 65% accuracy.

Application of Digital Twin in Medium-Voltage Overhead Distribution Network Inspection

The paper is devoted to the digital transformation of the core engineering maintenance processes involved in medium-voltage overhead distribution network infrastructure inspection. The study presents an analysis of digital twin utilization for inspection of the infrastructure of medium-voltage overhead distribution networks. At present, the infrastructure monitoring process is still manual, and its automatization is a challenging task due to the large distances between and small dimensions of the elements involved. The proposed digital twin is employed for 3D infrastructure modeling and complex analysis based on photogrammetry and aerial scanning data processing methods. The paper describes practical use cases for these data-driven methods for specific infrastructure management processes, e.g., scheduled inspection processes, including geometrical parameter measurements and visual infrastructure element defect identification, unplanned inspection processes (state of emergency, post-storm, etc.), and vegetation management processes. The proposed method allows operations to be performed remotely without physical presence in the field. At the same time, data-driven solutions provide objective results and potential automation via machine learning algorithms, which are more profitable economically. As the proposed method allows processes to be performed remotely, these data-driven solutions offer cost-effective results for automation. The digital twin concept is applied to the Latvian medium-voltage overhead distribution network with the support of the Latvian distribution system operator “Sadales tīkls” JSC.

Equipment Maintenance Effect on Energy Losses Reduction at Medium Voltage Distribution Network

The energy loss is one of primary problems at medium voltage distribution network. The declining quality of distribution network equipment is main factor of energy losses. The equipment maintenance has a significant correlation with energy losses reduction. This research discussed the effect of equipment maintenance on energy losses reduction at medium voltage distribution network. The research object was a feeder of 20 kV medium voltage overhead line at Bontoala Substation, Makassar. The research method was the quantitative calculation of energy losses in a month based on empirical formulas, with and without maintenance condition. The calculation was performed on three distribution network equipment: connector, transformer, and insulators. Based on the calculation results, the total energy losses without maintenance were 118,373.429 kWh. With maintenance, the value of losses can be reduced to 36,960.339 kWh or equal with 68.776% reduction. The research result shows the significant impact on equipment maintenance to distribution network energy losses.

Loop Optimization Noise-Reduced LSTM Based Classifier for PD Detection

Partial discharge (PD) is an important inducement of power failures such as insulation degradation. Effective, timely, and economical detection of the PD is the basis for maintaining power system stability. This paper proposes a loop optimization noise-reduced LSTM based classifier for PD detection of large-scale data disturbed with measurement noise. It establishes the loop optimization to greatly coordinate the data processing and data-driven based machine learning algorithm. The noise reduction, feature extraction, and the long short-term memory (LSTM) neural network are combined as a whole with internal linkages. The proposed method combines these three necessary steps to achieve a better solution for the PD detection, while other methods are in general single ones, and not dedicated designed for the solution. The combination of the different methods has combined advantages and can overcome each individual's drawback. This comprehensive solution is verified using large real trial data measured from medium voltage (MV) overhead power lines. It exhibits superior performance and great practicality for PD detection of MV overhead power lines with an accuracy of 95.4%. It outperforms other techniques in the literature based on the experimental results. This paper also summarizes the loop optimization rules for PD detection solutions based on extensive experiments and analysis. The loop optimization rules are competent for the optimization of wider engineering applications of PD detection.

Inductive coupling-based narrowband PLC systems for overhead MV power distribution networks: New insights

This paper advances the investigation of the adequacy of inductive coupling-based narrowband power line communication (PLC) systems in overhead medium voltage power distribution networks (MV-PDNs). Relying on raw data obtained from a measurement campaign which was carried out in urban and rural feeders in the south region of Brazil, it shows that overhead MV-PDNs may be a challenging data communication media when considering inductive coupling devices since the level of insertion losses associated with the coupling process is relevant. Also, the presence of significant loads between the source and destination nodes can severely degrade loops of currents, which are necessary to perform data communication in an inductive coupling-base PLC system, resulting in an erasure data communication media. For the reliable links (i.e., without erasure), the performance analysis shows that PLC channel impulse responses and additive noises can be respectively modeled as time-invariant systems with a quasi-flat channel frequency magnitude and white Gaussian random processes in urban and rural areas. Last but not least, an attenuation model and achievable data rates are discussed for the reliable links.

Mapping of Electrical Distribution Networks at Jampit Distribution Substations Using ArcGIS

In the Ijen sub-district, care must be taken to avoid overlapping uses of PTPN XII-owned plantations, resident fields, and the medium-voltage power distribution network. To lessen the interference factor in the distribution of electricity, the proper power distribution path must be chosen. The contact between trees and lightning is one of the variables that disturbs the distribution pathway. It is well known that the Jampit distribution substation in the Ijen district is situated in a region with plantations and private fields, making it susceptible to lightning and contact with trees. The position of distribution substations, medium-voltage overhead lines, and the location of energy users are among the issues examined in this study. In order to create a map of the electricity distribution network at Jampit distribution substations that pass through agricultural land and plantation areas, ArcGIS is used to help process spatial data including regional administration data, type of conductor, power capacity, distribution substation poles and electricity users.

DECREASING BACKFLASHOVER NUMBERS ON MEDIUM VOLTAGE OVERHEAD LINES LOCATED IN REGIONS WITH HIGH SOIL RESISTIVITY

The possibility of decreasing backflashover numbers on medium voltage overhead lines located in regions with high soil resistivity has been analyzed in this paper. Until now, activities in this field of protecting overhead lines have been limited by existing surge protection equipment and possibilities of grounding systems. The possibility of using chemical rods for getting better ground resistance and introducing metal oxide surge arresters like line arresters alongside the medium voltage overhead lines is analyzed here. The idea of this paper is based on facts that metal oxide surge arresters have become very high quality products with low prices, and so many important experiences in using them like line arresters exist in the world; and we, in Croatia, have a 10-year-old experience in using chemical rods like part of grounding system. The paper treats the problems of backflashover on medium voltage overhead lines, chemical rods working principles and ways of designing grounding systems like this. Finally the techno – economic analysis of using chemical rods and metal oxide surge arresters possibilities has been made, with determining justifiability criteria of using them. In the conclusion, comparison with knowledge until now has been made, as well as a suggestion for future use.

Fault location algorithms for active distribution systems utilizing two-point synchronized or unsynchronized measurements

This paper introduces two alternative formulations of a fault location algorithm, based on two-point measurements, which is appropriate for unbalanced medium voltage overhead distribution systems of radial configuration with or without distributed generation. The first alternative is solely based on synchronized three-phase voltage signals taken from the two measurement points. The algorithm applies fundamental bus-impedance-matrix-based fault analysis theory and calculates voltage drops to derive a fault location equation set for each fault type. The standard bus impedance matrix theory is also the basis for the second alternative. By combining the expressions correlating unsynchronized voltage and currents measurements from the two points with the elements of a modified bus impedance matrix, the need for synchronization angle is eliminated. Then, a fault location equation set is formed to obtain the fault distance and resistance. A multiple solutions elimination methodology is also proposed which is applicable for both alternative fault location algorithms addressed in this paper Extensive simulation studies demonstrate a good performance for the proposed fault location algorithms under numerous short-circuit conditions with varying pre-fault system loading conditions, fault resistances and measurement errors.