Low-voltage Line Research Articles

ERIRMS Evaluation of the Reliability of IoT-Aided Remote Monitoring Systems of Low-Voltage Overhead Transmission Lines.

Researchers have studied instances of power line technical failures, the significant rise in the energy loss index in the line connecting the distribution transformer and consumer meters, and the inability to control unauthorized line connections. New, innovative, and scientific approaches are required to address these issues while enhancing the reliability and efficiency of electricity supply. This study evaluates the reliability of Internet of Things (IoT)-aided remote monitoring systems specifically designed for a low-voltage overhead transmission line. Many methods of analysis and comparison have been employed to examine the reliability of wireless sensor devices used in real-time remote monitoring. A reliability model was developed to evaluate the reliability of the monitoring system in various situations. Based on the developed models, it was found that the reliability indicators of the proposed monitoring system were 98% in 1 month. In addition, it has been proven that the reliability of the system remains high even when an optional sensor in the network fails. This study investigates various IoT technologies, their integration into monitoring systems, and their effectiveness in enhancing the reliability and efficiency of electrical transmission infrastructure. The analysis includes data from field deployments, case studies, and simulations to assess performance metrics, such as accuracy, latency, and fault detection capabilities.

Identification of low-voltage phase lines using IEC 61850 and K-means clustering

Accurate phase line topology identification of LV lines facilitates the handling of line faults, which is of great significance for the safe and stable operation of distribution networks. In this paper, we model and analyze the LV lines based on graph theory, and propose a phase line relationship identification scheme based on the combination of HPLC and k-means clustering for the problem of missing or dynamically changing phase line relationships of LV lines in the station area. Aiming at the known phase-line relationship in the station area such as distribution panel, two phase-line configuration schemes, Terminal extension and new phase-line description logical node PPLD, are proposed. The area is divided by combining the configuration information of IEC 61850 SCL and the information of metering automation system. If HPLC is configured in the unknown region, HPLC is used to identify the phase line relationship. If HPLC is not configured, k-means based algorithm is used for correlation analysis between voltage measurements. Example results from a place in Shandong show that the accuracy of the method proposed in this paper is 93.96 % on average, which is higher compared to the existing methods.Significance: Accurate identification of phase-line relationships in LV lines is essential for optimising load through phase-change switches. In this study, we propose a novel phase line relationship identification scheme that combines HPLC and k-means algorithm based on the existing equipment in the station area. Leveraging the known topology within the existing equipment (LTU, switchboard, etc.) in the station area, we introduce two phase line configuration schemes, Terminal extension (extending the known phase line relationship) and the new phase line description logical node PPLD (a novel approach for configuring known phase line relationships). Additionally, we suggest a method of regional division to recognise phase line relationships in unknown regions. If HPLC is configured, it is used for phase line identification; otherwise, a k-means based algorithm analyses voltage measurements. By tailoring identification schemes to the actual characteristics of the station area, we significantly reduce the amount of data to be identified, improving accuracy and resource efficiency.

Lightning-induced voltages on low-voltage distribution lines

Special attention has been drawn to transients in low-voltage systems in recent years. As the surge withstand capabilities of low-voltage networks are much lower than those of medium-voltage lines, they are more susceptible to lightning-caused disturbances. One of the primary sources of overvoltages is related to indirect lightning strokes. Such overvoltages are highly dependent on the soil characteristics and generally tend to increase with the soil resistivity. Considering realistic conditions, this paper discusses the effects of different parameters on the phase-to-ground and phase-to-neutral lightning-induced voltages on the low-voltage side of a typical distribution transformer. In the case of high-resistivity soils or high ground resistance values, phase-to-ground voltages induced by indirect strokes can reach several tens of kilovolts. Phase-to-neutral voltages higher than 5 kV may be common if surge protective devices are not applied.

Investments in transmission lines and storage units considering second-order stochastic dominance constraints

Increasing intermittent renewable generation to meet the climate goals entails a deep transformation of current power systems. The transmission system must adapt to ensure a rapid and flexible response to the changes in the energy flows. Flexibility can be provided by reinforcing the interconnection among all the market agents and/or by installing facilities with fast response to the changes. In this work, we study the investment problem of a central planner that seeks to expand the transmission network and install storage units considering decarbonizing measures. We propose a two-stage stochastic problem with uncertainty on the demand growth and including representative days to characterize the hourly demand and renewable power variability. To obtain better expansion strategies according to a limit on the carbon emissions, second-order stochastic dominance constraints are imposed. Numerical analyses based on the power system of the Canary island (Spain) are provided. The results show that to install storage units is key to efficiently integrate renewable generation. The investments in the transmission system are mostly in lower-voltage lines. The formulation with stochastic dominance constraints results in higher second-stage investments, allowing a better adaptation to the demand growth evolution.

Decision Process for Identifying Appropriate Devices for Power Transfer between Voltage Levels in Distribution Grids

During the energy transition, new types of electrical equipment, especially power electronic devices, are proposed to increase the flexibility of electricity distribution grids. One type is the solid-state transformer (SST), which offers excellent possibilities to improve the voltage quality in electricity distribution grids and integrate hybrid AC/DC grids. This paper compares SST to conventional copper-based power transformers (CPT) with and without an on-load tap changer (OLTC) and with additional downstream converters. For this purpose, a corresponding electricity distribution grid is set up in the power system analysis tool DIgSILENT PowerFactory 2022. A DC generator like a photovoltaic system, a DC load like an electric vehicle fast charging station, and an AC load are connected. Based on load flow simulations, the four power transformers are compared concerning voltage stability during a generator-based and a load-based scenario. The results of load flow simulations show that SSTs are most valuable when additional generators and loads are to be connected to the infrastructure, which would overload the existing grid equipment. The efficiency of using SSTs also depends on the parameters of the electrical grid, especially the lengths of the low-voltage (LV) lines. In addition, a flowchart-based decision process is proposed to support the decision-making process for the appropriate power transformer from an electrical perspective. Beyond these electrical properties, an evaluation matrix lists other relevant criteria like characteristics of the installation site, noise level, expected lifetime, and economic criteria that must be considered.

Monitoring Energy Flows for Efficient Electricity Control in Low-Voltage Smart Grids

Modern low-voltage distribution lines, especially those linked with renewable energy sources, face technical hurdles like unaccounted and illegal electricity use, increased power losses, voltage control issues, and overheating. Tackling these challenges effectively requires continuously monitoring power flows and identifying problematic network spots. This study introduces a method involving ongoing energy flow monitoring from distribution transformers and other sources to end-users through auxiliary facilities. The algorithm seamlessly integrates with consumers’ existing smart power meters and supporting infrastructure, eliminating the need for extra equipment or data. Deployed in several distribution networks totaling about 40 GWh/year over two years, this diagnostic system showed promising results. It notably cut total power consumption by around 6% by detecting and mitigating illegal energy waste and addressing technical issues. Additionally, it reduced technical personnel involvement in operational tasks by approximately twentyfold, significantly enhancing network profitability overall.

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Optimal sizing and power losses reduction of photovoltaic systems using PSO and LCL filters.

The integration of renewable energy systems into electricity grids is a solution for strengthening electricity distribution networks (SEDNs). Renewable energies such as solar photovoltaics are suitable for reinforcing a low-voltage line by offering an electrical energy storage system. However, the integration of photovoltaic systems can lead to problems of harmonic distortion due to the presence of direct current or non-linear feedback in networks from other sources. Therefore, connection standards exist to ensure the quality of the energy before injection at a point of common coupling (PCC). In this work, particle swarm optimization (PSO) is used to control a boost converter and to evaluate the power losses and the harmonic distortion rate. The test on the IEEE 14 bus standard makes it possible to determine the allocation or integration nodes for other sources such as biomass, wind or hydrogen generators, in order to limit the impact of harmonic disturbances (LIHs). The evaluation of the harmonic distortion rate, the power losses as well as the determination of the system size is done using an objective function defined based on the integration and optimization constraints of the system. The proposed model performs better since the grid current and voltage are stabilized in phase after the photovoltaic source is injected.

Impact of the Integration of the Electric Vehicle on Low-Voltage Rural Networks

The electric vehicle deployment, due to the plans defined according to the energy transition objectives, produces new challenges for the electrical system. These challenges are associated with the charging infrastructure of these vehicles since they require a high current during specific periods, which can increase losses in the network, overload the lines, or cause voltage drops that affect the system’s stability. To solve these challenges, one of the possible solutions is the investment in new network infrastructure to face the increase in demand, such as the construction of new transformation centers or new medium and low-voltage lines. However, in the case of rural networks with a small number of users, these investments may not be viable. This article analyzes the possible impacts of connecting electric vehicles in a rural low-voltage network located in a Spanish municipality, as well as possible implementable solutions that do not require investment in new infrastructure. The number of connected vehicles has been calculated based on the national plan for 2030, and the network model used is based on actual data provided by the distribution company that operates in the area.

Calculation of excessive losses in low voltage line caused by computers

This work estimates excessive losses in low voltage line caused by nonlinear loads. Typical examples of nowadays nonlinear loads are computers, which numbers is especially increased in different types of companies as well as universities. In the case study the excessive losses in low voltage lines caused by the old and new computers are evaluated. The results presented show that the new technologies applied in the new generations of computers increased level of excessive losses in low voltage lines.

Performance Evaluation of Microgrid Management Function in KERI pilot plant

As usual, the microgrid operates in grid-connect mode, but, when a fault occurs in the upstream grid, it should disconnect and shift into islanded operation mode. In grid-connect mode, the controlling power flow at PCC is necessary management function rather than the frequency and voltage. However, the controlling the frequency and voltage is asked in islanded mode. To achieve these management goals appropriately, the cooperative control strategy among microsources is needed. This supervisory control action is executed at MMS. In this paper, the cooperative control strategy of microgrid components is presented and the management performance is evaluated by using microgrid pilot plant. The pilot plant consists of the PV, PV/Wind Hybrid system, BESS, diesel generators, and RLC loads, which are connected to 380V low voltage lines. The test results show that the proper control strategy can ensure stability of microgrid in islanded mode and maintain the power flow of PCC at desired value successfully.

Low-voltage overhead lines topology identification method based on high-frequency signal injection

Low-voltage overhead lines topology identification method based on high-frequency signal injection

Uticaj solarnih panela i skladišta električne energije na gubitke u niskonaponskoj mreži

The largest part of technical losses of electricity in electricity distribution are technical losses in low-voltage lines. Technical losses of electricity are losses that occur in the distribution of electricity from transformers to consumers in electrical distribution equipment. Commercial losses include unauthorized use of electricity and losses due to errors in metering equipment. The main source of technical losses of electricity is caused by the flow of electric current through conductors. Solar panels installed by consumers can affect the reduction of losses by reducing the flow of electric current, i.e. of electricity through low-voltage lines. The introduction of electricity storage (batteries) can have an additional impact on the reduction of electricity losses by using the stored electricity in batteries at times of peak loads. The paper presents the assumed daily diagram of the symmetrical load of the low-voltage line with the calculation of hourly losses without the influence of solar panels and with the influence of solar panels without electricity storage and with electricity storage. The impacts of solar panels without and with electricity storage are also shown in a daily diagram, as well as the voltage values at the end of the low-voltage line. In the calculation, an equivalent line with half the length and full hourly load is used for the low-voltage line.

Алгоритмы оценки основных параметров надежности низковольтного оборудования схем цеховых сетей

The article presents the classification of fuses, breakers, circuit breakers and packet switches. The laws of change of probabilistic reliability characteristics of the studied devices, as well as low-voltage cable lines are determined. Types of functions of change of basic reliability parameters are determined and corresponding graphical dependences are shown. The comparison of the obtained results of the values of probability of failure-free operation time with the requirements of GOST and passport data is carried out. The investigated probabilistic parameters of lowvoltage devices and cable lines are checked for compliance with the accepted law of distribution of random variables.

Research on configuration strategies for reducing low-voltage line losses through distributed photovoltaics

Photovoltaic power generation is currently one of the primary ways to harness solar energy in the world. In the face of the severe fossil fuel and environmental crises that the world is currently confronting, photovoltaic power generation has clear advantages from both the perspectives of resource sustainability and environmental friendliness. This paper explores the configuration strategy for addressing power losses in voltage elevation and distribution by studying methods of distributed photovoltaic power generation that focus on local generation, local grid connection, local conversion, and local utilization. Finally, the effectiveness of the configuration strategy is demonstrated through case analysis.

Methods for assessing the reliability of in-shop power supply

Research activities in the field of development of electrical power and electrical equipment include the development of new approaches to assessing the reliability indicators of electrical equipment elements and in-house power supply systems in general. The study has examined methods for assessing the reliability of electrical equipment in intra-shop power supply systems using the example of a workshop network section, including its main elements: power transformer, low-voltage cable lines, distribution points, circuit breakers, magnetic starters, contactors, switches. The reliability parameters of the circuit are calculated relative to the distribution cabinet of the power (DCp) and the distribution point of the power (DPp); regarding each connection of DCp and DPp. The methods under consideration are recommended to be used to clarify the frequency and timing of maintenance and repairs of electrical equipment of the in-shop power supply system, as well as to analyze the reliability of operation and identify the least reliable sections of network diagrams. The presented calculation using the logical-probabilistic method by constructing a fault tree is advisable to use to estimate the frequency of power loss of DCp and DPp, as well as individual connections. For the studied circuits, graphical dependences of the probability of failure-free operation of electrical equipment and the occurrence of a failure over time have been constructed.

Assessment of fault potential and touch voltage in the low-voltage distribution line system of the residential community

Considering the increasing risk of electric shock in old residential communities, this paper investigated fault potential and consequential human-body touch voltage in the low-voltage (LV) distribution network under typical line-fault conditions by numerical simulation with a circuit approach. Three protective grounding configurations of the LV distribution system were of concern, and the electric shock scenarios considering practical situations were introduced for assessment. It has been observed that the phase-to-ground fault potential of equipment increases when the fault location is closer to the faulty equipment itself and decreases when it moves further toward the circuit end. The equipment in a building is likely exposed to the dangerous phase-to-ground fault potential under the line fault. As for line-to-neutral short circuit and neutral-line-open fault, the fault potential distribution mainly depends on the specific grounding configurations. Bonding of non-exposed steelwork in the buried building foundation to the nearby grounded grid may not be recommended in the literature, but it could effectively mitigate the touch voltage in and around the building of concern in this paper. Note that this measure, together with the local equipotential bonding method inside a flat, can provide enhanced protection against electric shock even if the protective device fails to operate or is unavailable. Among three grounding configurations, the one with multiple grounding points of the neutral wires up to the entrance of a building leads to the least dangerous touch voltage cases.

Traceability analysis for low-voltage distribution network abnormal line loss using a data-driven power flow model

The abnormal behavior of end-users is one of the main causes of abnormal line loss in distribution networks. The integration of a large amount of distributed renewable energy into a low-voltage distribution network (LVDN) complicates line loss analysis. Traceability analysis for abnormal line loss aims to identify the specific end-user responsible for the anomaly in line loss. This paper proposes, for LVDNs with incomplete topology and line parameters, a practical traceability analysis approach using a data-driven power flow model. A data-driven power flow model based on a neural network is first established to capture the power flow mapping relationship without topology and line parameter information. A backpropagation algorithm is then presented to correct the actual power consumption data according to the measured voltage data. By comparing actual power consumption data with measured power data, users with abnormal behavior can be accurately identified and tracked. Finally, the effectiveness of the proposed approach is verified by actual data.

Research on CNN-LSTM DC power system fault diagnosis and differential protection strategy based on reinforcement learning

Introduction: With the development of artificial intelligence technology, more and more fields are applying deep learning and reinforcement learning techniques to solve practical problems. In the power system, both the direct current (DC) power system and the power grid substation are important components, and their reliability and stability are crucial for production efficiency and safety. The power grid substation is used to convert power from high-voltage transmission lines to low-voltage transmission lines, or from alternating current to direct current (or vice versa), in order to efficiently transmit and distribute power in the power system. However, diagnosing faults and designing cascaded protection strategies has always been a challenge due to the complexityand uncertainty of the DC power system.Methods: To improve the reliability and stability of the DC power system and power grid substation, this paper aims to develop an intelligent fault diagnosis system and cascaded protection strategy to reduce faults and downtime, lower maintenance costs, and increase production efficiency. We propose a method based on reinforcement learning and a convolutional neural network-long short-term memory (CNN-LSTM) model for fault diagnosis and cascaded protection strategy design in the DC power system. CNN is used to extract features from raw data, while LSTM models time-series data. In addition, we use reinforcement learning to design cascaded protection strategies to protect the power system from the impact of faults.Results: We tested our method using real 220V DC power system data in experiments. The results show that our method can effectively diagnose faults in the DC power system and formulate effective cascaded protection strategies.Discussion: Compared with traditional methods, this intelligent method can diagnose faults faster and more accurately, and formulate better cascaded protection strategies. This method helps reduce maintenance costs, increase production efficiency, and can be applied to other fields.

Model-based Optimization of the Switching Performance of a Switch Disconnector

Low voltage switch disconnectors (SD) combine rated load switching with disconnector functionality, providing safe electrical isolation. Electrical contacts are separated forming an arc discharge that needs to be quenched at first current zero (CZ) to protect the load and the SD itself. With increased line voltage, interruption at first CZ crossing is getting more difficult due to increased transient recovery voltage (TRV) and larger post arc current, leading to excessive contact erosion with longer arcing time. Arc simulation methodology was utilized to improve the design for better arc cooling close to CZ. Therefore, benchmark values of arc resistance and thermal time constant were evaluated close to CZ for a successful test at lower line voltage. The cooling efficiency of different designs at higher line voltage was analyzed by 3D arc simulation. A revised design was able to clear overload currents at lower and higher line voltages at first CZ, preventing excessive contact damage.