Distribution Network Equipment Research Articles

The planning method of new energy distribution network in plateau area based on local accommodation

Abstract The planning method of new energy distribution network in plateau area based on local accommodation is studied to improve the local accommodation capacity of new energy distribution network in plateau area. The framework of new energy distribution network planning in the plateau area is constructed, and the distribution network equipment suitable for the plateau environment is selected based on the harsh environment in the plateau area; in the framework of new energy distribution network planning in plateau area, a bi-level planning model considering multi-flexible resource coordinated scheduling and energy storage is established. The upper level planning model takes the maximum accommodation of new energy as the objective, and the lower level planning model takes the optimal daily operation benefit of energy storage under the given configuration as the optimization objective; the probabilistic power flow method and C-PSO are used to solve the bi-level model. The experiment shows that this method ensures the stability of the new energy distribution network in the plateau area, reduces the amount of abandoned wind energy and the operating cost, and improves the local accommodation capacity of the core higher than the distribution network.

Research on the Prediction Method of Equipment Status in Power Transformation and Distribution Based on Grey Model

With the continuous increase in the demand for electricity in our country, the reliability requirements of the power distribution network are gradually increasing, and the difficulty of predicting the state of key equipment in the power distribution network is also increasing. In response to this issue, this paper proposes a typical reliability prediction model for key equipment in the power distribution network based on an unbiased grey correlation model. Firstly, a grey model is established to model the reliability of typical key equipment in the power distribution network, and to conduct reliability analysis and life prediction. Secondly, an unbiased grey model is introduced to avoid the problem of the grey model leading to less than ideal life prediction accuracy when the growth rate of the original data sequence is high. Finally, taking the No. 1 main transformer of the 220 kV Lanshan substation under the jurisdiction of Ningxia Shizuishan Power Supply Company as an example, the oil chromatography data is cleaned using the KNN interpolation method and input into the prediction model to analyze and predict the failure rate during actual operation. The results show that this model has certain advantages in terms of life prediction accuracy and calculation time, and can play an auxiliary role in the process of predicting the state of key equipment in the power distribution network.

A Data–Physics-Driven Modeling Approach of Key Equipment for Large-Scale Distribution Network Simulation

Fueled by pressing global climate concerns, the integration of large-scale renewable distributed generation sources, including distributed wind power and photovoltaics, along with electricity substitution loads into the distribution network has been accelerated to diminish carbon emissions. This shift introduces significant challenges and necessitates the advanced operation and control of distribution systems to accommodate these changes effectively. Against this backdrop, there is a growing expectation for an open and scalable central control mode, equipped with compatible interfaces, to offer a visionary development platform for the grid. This platform is anticipated to meet the evolving needs of future distribution system development, ensuring adaptability and forward compatibility. The aforementioned platform requires open, scalable, and interface-compatible models of key distribution network equipment as its foundation. To address the challenges presented, this paper proposes a data–physics-driven modeling approach for automating simulations in distribution systems. This method employs a simplified and standardized system of linear differential equations with undetermined coefficients to capture the common physical characteristics of specific device types. The models designed through this approach are notably open, allowing for real-time data to refine undetermined coefficients and accurately depict the dynamic behavior of equipment over various periods. Their scalability also stands out, rendering them apt for large-scale distribution network simulations. The paper elaborates on models for distributed photovoltaic, wind turbine, energy storage, and electric vehicle, and demonstrates their application within an IEEE-33 node distribution network topology built on Python.

Detection of Potential Faults in the Electricity Distribution Network Using Unmanned Aerial Vehicles and Thermal Cameras Through Deep Learning Methods

In this article, a software-based unmanned aerial vehicle (UAV) prototype has been developed for exploration purposes, replacing the current manual inspection of energy transmission lines (ETLs) by human teams. The UAV's capabilities address the limitations of human viewing angles, ensuring more efficient exploration activities. Real-time exploration is now achieved through data collected with UAVs and processed using Convolutional Neural Networks (CNNs) and image processing techniques. The UAV’s path and detected objects are autonomously processed in the Cartesian coordinate system. The autonomous conductor tracking system provides bidirectional tracking of conductors in the distribution network through color space range and Faster R-CNN conductor detection. Incorporating a proportional-integral-derivative (PID) design, the UAV is capable of operating in adverse weather conditions. An additional overheating warning system protects equipment in the electricity distribution network (EDN) from potential issues related to uneven load distribution, economic life, and labor errors. Through modeling studies with convolutional neural networks and field data, impressive F-1 scores have been achieved for detecting various anomalies: 77% for trees in contact with the line, 67% for concrete equipment exceeding its economic life, 88% for bird nests, 55% for cracked porcelain insulators, 89% for foreign objects, and 97% for nonuse of original fuses.

Development of new pocket distribution network inspection equipment

This paper aims to explore a new intelligent inspection mode of pocket distribution network equipment, which realizes rapid and comprehensive inspection and inspection by using terminal +N intelligent sensors and partial discharge detection and infrared temperature measurement technology as the core. First, this paper introduces the background and motivation of the new mode, and emphasizes the limitations of the existing traditional inspection methods and the problems that need to be improved. Then, the design and manufacture of pocket devices are described in detail, including key aspects such as sensor integration, portability and user-friendliness. Finally, the paper summarizes the research results and emphasizes the potential benefits and future research directions of this new intelligent inspection model.

Research on Digital Distribution Network Micro-application and Precise Control of Distribution Operations Based on Grid Resource Business Center

Abstract This paper discusses the design and implementation of the grid intelligent micro-application, involving two core aspects: technical architecture and data architecture. First, the article successfully constructs the basic framework of grid intelligent micro-application, which realizes distribution network equipment’s inspection, operation, and maintenance control functions. It further establishes a collaborative regulation model for digital distribution network micro-applications, focuses on calculating and analyzing distribution banding operations, and proposes a precise specification for the methods easily confused in actual operations. The focus of the study includes comparative analysis of voltage and current overrun probabilities before and after regulation to assess the effectiveness of micro-applications in load forecasting and anomaly warning. The results show that using digital distribution micro-applications significantly reduced the likelihood of overruns at most weak points of the grid by an average of 68%, while the year-on-year reduction of anomalies reached 35%. In addition, the micro-application achieved over 90% accuracy in charge prediction, an impressive performance. By simplifying the distribution operation process, this study significantly improves the feedback speed and efficiency of field operation information, which is of great practical significance and application value for the digital construction of power grid distribution network.

Analysis of health state before and after fault self-healing based on a high percentage of distributed distribution grid systems

Abstract In this paper, we preprocess the equipment data using by exponential smoothing method, fit the fault information by using the distribution model, and evaluate the fitting degree of the function with the help of the K-S test to derive the equipment fault information function. In accordance with the correlation mapping between the distribution network health index and the existence of faults, the health index of the distribution network equipment in the region before and after the self-healing of faults is comprehensively calculated, and the state assessment of the equipment is carried out. Before and after the fault self-healing of the IEEE33 node system, the system loss is reduced by 58.89%, as evidenced by the results. Before and after the fault self-healing, Condition 1: the line health index ranges from 1.317 to 3.777, and the transformer health index ranges from 2.011 to 4.646. Condition 2: the line health index ranges from 2.284 to 4.059, and the transformer health index ranges from 1.653 to 4.047, respectively. And Condition 3: the health indices all increase by varying from 0.711 to 2.067. Localized equipment degradation has a significant impact on the overall health of the network, with lines affecting the system to a greater extent than transformers. To summarize, the proposed health index state assessment method can effectively determine the health state of distribution networks before and after fault self-healing.

A voltage control method for distribution networks based on TCN and MPGA under cloud edge collaborative architecture

A distribution network voltage control method based on TCN and MPGA under cloud edge collaborative architecture is proposed to address the issues of heavy computational burden and inability to balance economic efficiency in traditional decentralized and centralized voltage control methods. Firstly, under the cloud edge collaboration architecture, the power prediction model based on time convolutional networks is trained in the cloud, and the edge predicts the load demand and new energy active output in each region based on the TCN Attention power prediction model issued by the cloud. Then, considering safety and economy comprehensively, with the goal of minimizing the daily network loss and voltage regulation cost in the distribution network, the Pareto solution set for the optimal operation point of each voltage regulation equipment in the entire distribution network was solved based on an improved multi population genetic algorithm at the distribution cloud main station. Finally, the optimal distribution network voltage control scheme is obtained based on the Pareto solution set. Based on the simulation system, experimental testing was conducted on the proposed method, and the results showed that its daily voltage regulation cost and network loss were 863.4 yuan and 43.73 MW h, respectively. The average absolute percentage error of the prediction model was 4.51 %, which was superior to other comparative methods.

Exploration and application of new distribution system technology for large-scale distributed distribution network digital service access

Abstract Digital technology is leading fundamental innovation and development, and digitalization represents a great opportunity for the energy industry to take off and develop. In this paper, digital and intelligent technologies are used to integrate, analyze, and manage distribution network equipment information. Secondly, a new smart distribution terminal design is proposed and modeled using the IEC 61850 standard to monitor the status of smart distribution grid management equipment. Through the active distribution system structure, based on the decoupled PCC, a model is constructed for large-scale distributed optimal dispatching. Finally, two scenario experiments are taken as examples to simulate and analyze the distributed co-dispatch of the new distribution system. The results show that the operation reward interval of scenario 2 is [194.43, 205.44] when the decomposition convergence criterion is set to 0.05 and the threshold value of the second-order cone relaxation accuracy is set to 10−5. The novel distribution system proposed in this paper is able to achieve optimal decision-making that satisfies the distribution network operation constraints, while the multi-microgrid seeks to maximize its benefits.

Research on Energy Efficiency Loss of Typical Distribution Network Equipment by Compound Power Quality Disturbance

The development of modern science and technology causes increasing problems of power quality, such as the wide application of impact and nonlinear loads represented by power electronic devices, the emergence of a large number of single-phase users in the low-voltage distribution network, and the start and stop of various large power-using equipment. It makes the problem of power quality in the power system more and more serious. The problem of power quality will not only reduce the efficiency of the equipment in the power system and shorten the life of the equipment but also lead to an increase in the distribution network loss. The level of power loss is related to the economic benefits of the majority of users and power enterprises and is also an important reflection of social benefits and energy consumption status. Currently, most domestic and foreign research is on single power quality disturbance, but the actual low-voltage distribution network contains complex problems of power quality. Therefore, it is important to study the additional loss of key equipment in the low-voltage distribution network and LV distribution network under multiple power quality disturbances. Based on single power quality disturbance, the accurate calculation of additional loss of key equipment caused by compound power quality is further deduced and verified in the simulation platform. This paper further deduces the accurate calculation of the additional loss of key equipment caused by compound power quality and verifies the model with MATLAB/Simulink simulation.

Analysis of the Influence of Harmonics on Energy Efficiency of Typical Equipment in Distribution Network

With the continuous development of power systems, the number of non-linear loads is increasing. When harmonics flow through wires, transformers, filters, and other devices, additional harmonic losses will be generated, which will cause power loss and safety problems such as equipment overheating. However, there are few studies on loss in complex power quality environments. Considering the influence of skin effect when harmonics flow through the conductor, this paper studies the distribution of current density, explores the influence of conductor material, radius, and frequency of the current flowing through the metal on the current distribution, and proposes a calculation method of conductor harmonic resistance considering the influence of skin effect. Furthermore, the electrical energy consumption of typical devices in the distribution network is considered. Based on the theoretical calculation model, a simulation platform was established to carry out the equipment loss measurement experiment under each harmonic current, and the mutual verification between the theoretical calculation model and the experimental measurement was realized.

ANALYSIS OF ELECTROMAGNETIC TRANSIENTS IN THE LOW-VOLTAGE DISTRIBUTION NETWORK OF AN INDUSTRIAL ENTERPRISE

Analysis of a short circuit in the distribution network with a voltage of up to 1 kV of the power supply system of an industrial enterprise. The procedure for calculating the short-circuit current in accordance with the recommendations of the ANSI/IEEE standard C37 series, which regulates the calculation of the short-circuit current for the selection and verification of switchgear and protective devices according to the short circuit current rating, was used to calculate the short-circuit current in the low-voltage distribution network of an industrial enterprise. The need to automate the process of calculating short-circuit currents in the power supply system of an industrial enterprise was substantiated. The Electrical Transient Analyzer Program (ETAP) software was used as an analysis tool. The design of the low-voltage distribution network was carried out in the ETAP software environment. The Short Circuit package of the ETAP software was used to calculate the short-circuit current on any bus of the distribution network. The result of the analysis is the determination of the short circuit current values and the verification of the compliance of the characteristics of the installed electrical equipment with the short-circuit currents. The effectiveness of using ETAP software for short-circuit analysis in order to select and verify the electrical equipment of the low-voltage distribution network of an industrial enterprise according to the level of short-circuit current was proven. The results of the analysis of the short-circuit current using the ETAP software provided an opportunity to verify the correctness of the decisions made regarding the selection of low-voltage switchgear of the distribution network of the facility’s power supply system. Analysis of short-circuit current using ETAP software provides the possibility of selecting switchgear and protective devices according to the level of short-circuit current, which contributes to the design of a reliable power supply system for the facility.

A novel robust Volt/Var optimization method based on worst‐case scenarios for distribution network operation

The Volt/Var optimization (VVO) problem is used for scheduling the voltage regulation and reactive power compensation equipment in distribution networks to minimize power loss and voltage violation. In order to solve the VVO problem for a forthcoming time horizon, it is necessary to predict some parameters such as load demand and renewable energy production. The prediction of these parameters is always accompanied by uncertainty that robust optimization can be used to solve this concern. This paper presents a scenario-based robust Volt/Var optimization (RVO) method that significantly reduces the number of scenarios required for the worst-case approach. Solving the VVO problem with the worst-case scenarios reduces the computational burden and maintains the voltage security of the distribution network against the severe events. The proposed RVO is formulated based on a mixed-integer second-order cone programming (MISOCP) model in which Volt/Var control (VVC) equipment is scheduled over a two-stage strategy. The proposed method is validated using modified 33-bus and 69-bus IEEE test systems. The results demonstrate that the proposed RVO method maintains the network's voltage profile within the acceptable range against uncertainties.

Open capacity calculation method of distribution network

At present, there are few methods for quantitative calculation of installed load or new energy for distribution network equipment. Based on this, this paper proposes a calculation method for the open capacity of the distribution network. Firstly, the calculation methods of the open capacity of a 10 kV distribution transformer, 10 kV lines, and high-voltage substation three-level distribution network based on the conventional situation and new power system are studied, respectively. Then the calculation methods of the open capacity of the distribution system based on the conventional case and the new power system are studied, respectively. Finally, the empirical region is selected, and the research results are used for case analysis to verify the effectiveness and operability of the research results.

Analysis of Seasonality and Causes of Equipment and Facility Failures in Electric Power Distribution Networks

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informujące swoich czytelników o najnowszych osiągnięciach naukowych i nowoczesnych rozwiązaniach technicznych w Polsce i na świecie, popularyzuje problemy techniczne oraz poszerza wiedzę i kulturę techniczną.

Fault identification method of electrical automation distribution equipment in distribution networks based on neural network

Fault identification method of electrical automation distribution equipment in distribution networks based on neural network

Fault identification method of electrical automation distribution equipment in distribution networks based on neural network

Fault identification method of electrical automation distribution equipment in distribution networks based on neural network

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.

Estimation of acceptable failure rates for equipment of power distribution network

Regulatory requirements for reliability indexes of power distribution networks are considered. The dynamics and structure of the reliability indexes of electricity distribution companies are analyzed. Criteria for determining the acceptable number of outages of power network equipment are proposed to calculate the acceptable frequency of outages. The proposed approach is illustrated by calculation of acceptable values of reliability indexes for the power distribution network of Moscow Region.

Double-layer optimized configuration of distributed energy storage and transformer capacity in distribution network

In order to solve the problem of low utilization of distribution network equipment and distributed generation (DG) caused by expansion and transformation of traditional transformer capacity, considering the relatively high cost of energy storage at this stage, a coordinated capacity configuration planning method for transformer expansion and distributed energy storage (DES) is proposed in this paper. First, the energy storage capacity requirements is analyzed on the basis of the transformer overload requirements, and analyzing the correspondence between different capacities of energy storage and transformer expansion capacities. Besides, taking into account the impact of different action mechanisms of energy storage on the node load within a day, a location optimization method for DES based on the standard deviation of network loss sensitivity is introduced. Then, considering the net cost of coordinated planning of energy storage and transformer are minimum and the benefit of energy storage operation is maximum, a two-layer optimization model of distributed energy storage and transformer capacity is established. Finally, the solution method of the two-layer optimization model is proposed, and the feasibility of the proposed model is verified by IEEE33 bus distribution system. The results show that the coordinated planning method proposed in this paper can greatly reduce the investment cost, and the net cost of the coordinated planning scheme is reduced by 17.558 million yuan compared with the scheme of separate configuration for energy storage, which effectively improves the economics of energy storage configuration.