Distribution Network Automation Research Articles

Fault indicators allocation to maximize the performance of a fault locator based on artificial intelligence

Fault location (FL) is one of the main challenges in Advanced Distribution Automation (ADA) of Active Distribution Networks (ADN). One of the commonly used strategies by utilities to deal with this challenge is the use of Fault Indicators (FIs), which indicate to the operator the path taken by the fault current. However, a good performance of this scheme depends on the number of installed devices, a high number of them could cause a high cost for the utility investment planning. In this context, this paper presents an artificial intelligence-based fault location strategy that determines the number and location of FI into ADN to maximize performance in fault section estimation. To achieve this objective, the ADN is divided into sections, and the FL problem is modeled as a classification problem to train an Artificial Neural Network (ANN). To determine the number of FIs to be installed and their location, the strategy uses the three-phase current magnitudes measured by the FI as features for an ANN model. Also, the strategy uses a feature selection and tuning scheme based on a multiverse optimization algorithm (MOA) to identify the features that maximize the accuracy of the ANN model. The strategy was validated on the IEEE123-node test feeder. The results showed accuracy close to 99.4 % with a reduction of 40 % of the number of FIs when compared with other method. The strategy shows its simplicity and promising prospects to apply it in the utility's investment planning.

Reliability Evaluation of Cabled Active Distribution Network Considering Multiple Devices—A Generalized MILP Model

With the rapid development of power electronic equipment, the automation and intelligence level of active distribution networks (ADNs) continues to improve. Against this background, soft open points (SOPs) are gradually replacing traditional segmented switches and interconnection switches. The voltage support capability and fast response characteristics of SOPs can shorten power outage time and expand load recovery range. However, the widespread integration of distributed renewable energy and new power electronic devices has made the fault characteristics of ADNs more complex, significantly increasing the computational complexity of ADN reliability assessment. At present, there are few studies that comprehensively consider ADNs with multiple devices. Therefore, this paper proposes a reliability evaluation method for ADNs that considers multiple devices. Firstly, the impact of circuit breakers, SOPs, and segmented switches on the load recovery process is analyzed. Secondly, an improved virtual fault flow model based on the action mechanisms of circuit breakers, SOPs, and segmented switches is established. The virtual fault flow is represented by logical variables to simulate post fault network reconstruction strategies that include circuit breaker tripping, SOP power supply recovery, and segmented switch isolation actions. Then, with the goal of minimizing the system average outage time after network reconstruction, a generalized mixed integer linear programming (MILP) model is given. Finally, taking the IEEE 33-node testing system as a case, the effectiveness and feasibility of the proposed method are demonstrated.

Real time validation of a control system for microgrids with distributed generation and storage resources

Faced with a scenario in which the increase in renewable energy generated near consumer centers can cause problems for the operation of the electrical network, the present work proposes a real-time simulation model for automation and control systems of electrical distribution networks with microgrids, distributed generation, and storage resources. The proposed model consists of a hardware-in-the-loop control with the aid of a simulation tool in conjunction with a Real-Time Digital Simulator (RTDS) and considers the dynamic behavior of switched elements and inverters. A communication platform using TCP/IP protocol between RTDS (power system) and MatLab/Simulink (optimization algorithms) allows the operation of the network in grid-connected and islanded mode, guaranteeing the computational time for experimental implementation. For the first mode, an algorithm is proposed to solve an optimal dispatch energy storage system problem. Second mode, an algorithm is proposed to solve a load shedding problem. The objective is to operate the microgrids optimally and evaluate the performance of a storage system based on real data from the state of Paraná, in Brazil. Results show that the optimization algorithms are experimentally applicable, obtaining reasonable computational time to find optimal solutions and an assertive decision-making to meet the objectives. Thus, the proposed framework is a potential tool to validate algorithms for active management of microgrids in real-time simulation.

Optimization and application of artificial intelligence in robotic automated distribution network overhead line engineering

INTRODUCTION: Artificial intelligence is a product of high-end technological development since the 21st century, which has subverted people's traditional cognition in many aspects and greatly enriched and improved people's lives. Artificial intelligence has covered every aspect of life, and the distribution network overhead line project is also one of them. The combination of the two symbolizes the combination of modern technology and infrastructure construction, which is of great significance for modern economic and social development and transformation and upgrading. OBJECTIVES: In order to solve the practical problems in the design of artificial intelligence and distribution network overhead line engineering, this paper focuses on the practical use of such artificial intelligence as robots in distribution network overhead line engineering. METHODS: The models of spatial perception, target recognition and automatic calculation are established, and some key technical problems of robots put into actual engineering are simulated and calculated. RESULTS: In the spatial perception model, the combination of robotic arm and laser device is utilized to solve the problem of direct sunlight, which affects the localization. In the target recognition model, combining the algorithms of minimum spanning tree and maximum critical path, the computational accuracy is improved to 1 mm. in the automatic computation model, the introduction of auxiliary lines and the secondary confirmation of manpower make the error of the work further reduced. CONCLUSION: This paper's simulation algorithm for the reality of the distribution network overhead line project provides a more detailed solution to improve the technical content of the distribution network overhead line project and the quality of construction management is not a simple task, the need for the relevant distribution network overhead line project enterprises as well as the corresponding distribution network overhead line project personnel to take targeted measures.

New approaches and digital technology automation tasks processes of control and accounting of electricity in distribution networks

This paper studies 0.4 kV power distribution networks (PDN) and automated systems for electricity monitoring and metering (ASEMM) As is known, one of the main tasks of ASEMMs is the digitalization of PDNs, aimed at further improving the efficiency and reliability of their operation. It is advisable that new models, methods, and intelligent technologies used for automation and informatization of distribution networks should also be focused on minimizing their power losses, which are currently fairly high thus significantly compromising the technical and economic performance of automation systems employed and PDNs. Modern (conventional) ASEMMs, implemented at the facilities of utilities, do not have the appropriate technical, algorithmic, and software tools designed to reduce power losses in the PDN. This is due to the fact that conventional ASEMMs mainly solve the problem of remote data collection from the system meters and their digital processing for the purpose of revenue metering of electricity. In this regard, the paper proposes methodological, algorithmic, and digital technologies designed to solve a set of new functional tasks in the conventional ASEMMs, aimed at reducing power losses in DPNs by optimizing their operating conditions.

A sustainable framework for multi-microgrids energy management in automated distribution network by considering smart homes and high penetration of renewable energy resources

This paper presents a new framework for the scheduling of microgrids and distribution feeder reconfiguration (DFR), taking into consideration the uncertainties due to the load demand, market price, and renewable power generation. The model is implemented on the modified IEEE 118-bus test system, including microgrids and smart homes. The problem has been formulated as a two-stage model, which at the first stage, the day-ahead self-scheduling of each microgrid is carried out as a two-objective optimization problem. The two objectives include the minimization of the total operating cost and maximization of the consumer's comfort index. Then, the solution, obtained from the first stage is delivered to the distribution system operator (DSO). Then, at the second stage, the DSO determines the optimal configuration of the system with the aim of minimizing operating costs of the main grid and the penalty of deviating from microgrid scheduling. Note that the penalty is due to the difference in power exchange requested by the microgrids from the power exchange finalized by the DSO. The presented two-stage optimization problem is modeled in a mixed-integer linear programing (MILP) framework with four case studies, and solved in GAMS by using the GURUBI solver. The simulation results show that in the cases the DSO is able to reconfigure the system, the deviation from the optimal scheduling of microgrids would be considerably lower than the cases with fixed system configuration. • Proposing a two-stage optimization framework for scheduling of microgrids and DFR. • Considering smart homes and traditional loads in the model. • Two-objective modeling of microgrids' scheduling problem by the fuzzy method. • Solving the DFR problem with regard to the optimal scheduling of microgrids. • Investigating the impact of different objective functions on smart homes' scheduling.

Microgrids energy management in automated distribution networks by considering consumers’ comfort index

Modern distribution networks' scheduling faces many more challenges than traditional networks. Because on the one hand, it must satisfy the technical and security constraints of the distribution system, and on the other hand, it must observe the optimal scheduling of microgrids. Hence, in this paper, a bi-level mixed-integer linear programming (MILP) model is presented in which the scheduling of the distribution network is done by considering the optimal scheduling of microgrids and smart homes. In the first level, each microgrid performs its optimal scheduling in a decentralized manner and delivers it to the distribution system operator (DSO). Then, in the second level, DSO plans the main grid according to the optimal schedule of microgrids and by implementing distribution feeder reconfiguration (DFR). Finally, the problem is solved in the form of four case studies by the CPLEX solver in GAMS software and the results show that the proposed model not only reduces the total operating cost by 27.05% but also significantly increases the consumers’ comfort index. The results also illustrate that DFR implementation and participation in the DR program reduce total operating costs by 19.11% and 14.02%, respectively.

Multi-period reconfiguration planning considering distribution network automation

This paper presents an approach for multi-period reconfiguration planning of distribution networks where remotely controlled and supervised switches (automated switches) are installed. The proposed approach employs a multi-objective mixed integer linear programming model that explicitly considers the influence of the automated switches on the interruption duration (interruption cost). It enables obtaining a set of noninferior solutions (reconfiguration plans) in each period. These plans are then used within the dynamic programming framework to identify and evaluate a number of high-quality multi-period reconfiguration plans by employing the backward induction. In this way, the proposed approach overcomes two shortcomings of the decomposition network reconfiguration planning methods: i) too short a planning horizon and ii) too few generated and evaluated alternatives. The presented results show the potential of the proposed approach to improve the multi-period reconfiguration planning process in distribution networks with automated switches.

Application Analysis of Electrical Automation Based on Artificial Intelligence Technology

The business goals of power companies are low operating costs, high asset efficiency, and low transmission and distribution losses, making the intelligent development of distribution networks an inevitable trend to improve overall operating efficiency in the future. Distribution network automation and intelligence help to optimize the operation mode of the distribution network by monitoring the operation status of the distribution network during the normal operation of the distribution network, which can improve the reliability of the distribution network equipment and reduce the labor intensity and maintenance costs of the operators. This article uses artificial intelligence technology to design an electrical automation system, and applies the system to the intelligent inspection of substation equipment failures. By comparing the common electrical automation system and the electrical automation system under artificial intelligence technology, the fault recognition rate of the substation equipment is found. The intelligent automation system has a higher recognition rate of equipment failures, reduces the workload of maintenance personnel to repair the failures, and maintains the continuous power supply of the grid.

Reliability enhancement of distribution networks with remote-controlled switches considering load growth under the effects of hidden failures and component aging

<abstract> <p>Over the last decade, automated distribution networks have grown in importance since traditional distribution networks are insufficiently intelligent to meet the growing need for reliable electricity supplies. Because the distribution network is the least reliable and the sole link between the utility and its customers, it is critical to improve its reliability. The remote-controlled switch (RCS) is a viable choice for boosting system reliability. It shortens the interruption period, which also minimizes the expected interruption cost and the amount of energy not served. Using the greedy search algorithm, this research expands the current reliability evaluation technique to include RCSs in distribution networks. The optimal location and numbers of RCSs have been evaluated with compromised cost. This study simultaneously takes into account the effects of load growth on system reliability indices, the impact of age on equipment failure rates and the hidden failure rate of fuses. The Roy Billinton test system's distribution network connected at bus 2 and bus 5 has been used to test the effectiveness of the suggested approach. The outcomes demonstrate that effective RCS deployment improves the radial distribution network's reliability indices significantly.</p> </abstract>

Development Issues of Systems for Automation and Digitalization of Power Distribution Networks

This paper studies 0.4 kV power distribution networks (PDNs) and automated systems for electricity monitoring and metering (ASEMM). As is known, a main task of ASEMMs is to digitalize PDNs, which is aimed at improving the efficiency and reliability of their operation. It is advisable that new models, methods, and intelligent technologies used for automation and informatization of distribution networks should also be focused on minimizing their power losses, which are currently fairly high and significantly compromise the technical and economic performance of automation systems employed and PDNs. Modern (conventional) ASEMMs, implemented at the facilities of utilities, do not have the appropriate technical, algorithmic, and software tools to reduce power losses in the PDN. This is due to the fact that conventional ASEMMs mainly collect remote data from the system meters and ensure their digital processing for the purpose of revenue metering of electricity. In this regard, the paper proposes methodological, algorithmic, and digital technologies to accomplish a set of new functional tasks in the conventional ASEMMs, aimed at reducing power losses in PDNs by optimizing their operating conditions.

Research on Quantitative Security Protection Technology of Distribution Automation Nodes based on Attack Tree

In order to improve the security of distribution automation system nodes and ensure the safe operation of distribution network, a quantitative security protection technology for distribution automation nodes based on attack tree is proposed. This paper analyzes the factors of node risk assessment of the distribution automation system, and through the evaluation and analysis of node vulnerabilities; it discovers the faulty nodes in the distribution automation system in advance. Based on the node vulnerability evaluation results of the distribution automation system, the risk of the distribution automation system is comprehensively evaluated using the attack tree. Establish the distribution network control model under network attack, locate the fault node, and use trusted computing technology to design trusted distribution terminals. When the amount of data is large, more effective symmetric encryption algorithm SM4 is required to achieve node security protection in the distribution network automation system. The experimental results show that the method has high fault node location accuracy, low reliability calculation time, and the distribution automation system network has certain robustness, which fully verifies the application effect of the method.

Research on Key Technologies of Power System Automation in Smart Grid

The paper summarizes the construction mode of distribution network automation system, and sorts out the operating characteristics of centralized intelligent mode and distributed intelligent mode. In view of the construction and operation of China’s distribution network automation system, point out common problems in system construction, operation and management in most regions. At the same time, the paper proposes the optimization of distribution network automation technology based on the gravity search algorithm, and improves the algorithm. Finally, the improved gravity search algorithm is applied to the IEEE 6-node power system. The calculation results show that the active power loss and voltage obtained by the algorithm are Compared with the original state, the level has been greatly improved, which greatly improves the automation efficiency of the power system. In this paper, the gravity search algorithm is used to calculate the optimization of power system automation technology, and the algorithm is improved, which overcomes the shortcoming of easy convergence to the local optimum.

Distributed transmission technology of node status in distribution network

With the rapid development of distribution network automation and the construction of DC distribution network and AC / DC hybrid distribution network, the network operation mode is more flexible. If the distribution network wants to realize rapid load transfer, such as the connection of power supply, upstream and downstream fault isolation signals and other node states need to be quickly identified. At present, the node status identification of distribution automation is basically completed by the master station. However, the master station has poor real-time transmission of status information, which is generally in seconds or minutes, and can not meet the demand of real-time load transfer. In this paper, a distributed real-time transmission method of AC and DC distribution network node status is constructed for distribution automation system. Based on IEC61850 goose communication protocol, the real-time transmission of node status is realized in distribution automation terminal. In this method, the positive direction of each tie switch is defined, which is independent of power flow direction, and the tie switch is distinguished along the user-defined positive direction When multiple tie switches have the same upstream node, they are each other’s t nodes. Each tie switch needs to be equipped with a distribution automation terminal with goose communication capability. According to different control strategies, the distribution automation terminal can realize millisecond level node state transmission step by step. Node state can be divided into unconditional transmission state and conditional transmission state. The distributed real-time transmission technology of distribution network node state proposed in this paper has been successfully applied to Tongli integrated energy service The center and Suzhou medium and low voltage DC project lay the foundation for the realization of loop closing, loop breaking control, fast fault isolation and power transfer control strategies.

Automated Distribution Networks Reliability Optimization in the Presence of DG Units Considering Probability Customer Interruption: A Practical Case Study

Automation in power distribution systems and supervisory control and data acquisition (SCADA), which perform network switching automatically and remotely, allows distribution companies to flexibly control distribution power grids. Cross-section switches also has a significant role in the automation in distribution systems, in that the operational optimization of these switches is able to enhance the supply power quality and reliability indicators, and can be a prosperous solution to increase the reliability, efficiency and overall service quality in services to customers. In this regard, in this work, the genetic optimization algorithm (GOA) approach which integrated the Steepest Descend Technique (SDT) is proposed and enhanced based on the features of the mentioned issue to sketch the optimal location and control of automatic and manual cross-section switches and protection relay systems in distribution power systems. The GOA is able to search globally that can prevent the result from locally convergence, also, GOA gives superior primary solutions for the SDT. Thus, the SDT can search locally with higher performance which increase the solutions' accuracy. Therefore, an optimization formulation is proposed to improve the value-based reliability of the suggested layout considering the cost of customer downtime and the costs related to segmentation of switches and relay protection devices. Also, a distributed generation (DG) system in distribution networks is considered based on the islanded state of generation units. The effectiveness of the optimal suggested procedure is evaluated and represented via performing a practical test system in the distribution network of Ahvaz city in Iran. The results show that using proposed method and by optimally allocating switches maneuver, energy losses without switches are reduced from 310.17 (MWh) to 254.2 (MWh), and also by using DG, losses are reduced from 554.01 to 533.61 which confirms the ability and higher accuracy of the proposed method to improve reliability indices.

Optimal Operation of Automated Distribution Networks Based-MRFO Algorithm

Nowadays, distribution utilities expend large investments on Distributed System Automation (DSA) based on smart secondary substations at load, capacitor, and distributed generator points with installed automatic sectionalizing switches on their branches. This article addresses the optimal control and operation of distribution systems that minimize the wasted energy and introducing quantitative and qualitative power services to meet consumers’ satisfaction. Simultaneous allocations of Distributed Generators (DGs) and Capacitor Banks (CBs) are handled at peak loading condition. Then, the DSA is optimally activated for optimal Distribution Network Reconfiguration (DNR), optimal DGs commitment, and optimal CBs switching for losses minimization in coordination with different loading conditions. Practical daily load variation is applied to simulate the dynamic operation of automated distribution systems. For achieving these targets, the Manta Ray Foraging Optimization Algorithm (MRFOA) is adopted. MRFOA is an effective and simple structure optimizer that emulates three various individual manta rays foraging organizations. The capability of the MRFOA is applied to the IEEE 33-bus, 69-bus and practical distribution network of 84-bus due to the Taiwan Power Company (TPC). A comparison with recent techniques has been conducted to prove the effectiveness of MRFOA. The accomplished results demonstrate that the proposed MRFOA has great effectiveness and robustness among other optimization techniques.

Switches optimal placement of automated distribution networks with probability customer interruption cost model: A case study

Sectionalizing switches (SSs) have been installed in Distribution networks with the aim of providing maneuver and ring points, so raising service reliability. It is usually assumed that these switches are totally reliable although, in practice, they have not ideal efficiency at all times. In fact, the switches might occasionally face failure, which decreases their capability with the aim of enhancing system reliability. A model with the aim of considering the failure probability of the switches in their optimal placement issue is proposed in this paper. The model aids with the aim of minimizing the whole costs of SSs and the interruption costs incurred through interrupted users. This study uses the discrete Markov chain model with the aim of obtaining the malfunction possibility under various states. Afterwards, the placement problem is solved with the aim of obtaining the global optimal solution with genetic algorithm. The advantage of the suggested model has been investigated according to sensitivity analysis and various scenarios. The research illustrates how the outcomes of the placement issue have been influenced through the uncertainty arising from the possible failure of the switches and how ignoring the uncertainty is able to cause deviation of the anticipated profit from the real one. The efficiency of the suggested procedure has been evaluated and shown through investigating on the Ahwaz city distribution network. The outcomes of simulation prove the ability and precision of the suggested procedure.

The impact of feeder reconfiguration on automated distribution network with respect to resilience concept

Owners of power systems incur high costs and investments to transfer the electrical power to customers in the distribution network. Hence, the reliability of the distribution network is particularly important in the lives of customers. Natural disasters such as hurricane and earthquake or sudden faults may threaten the reliability of the distribution network. Therefore, the focus of this study is to provide a new formulation for the distribution system resilience and voltage security. To improve the mentioned objectives in the automated distribution system, the concept of distribution feeder reconfiguration (DFR) is used in this study. Due attention of distribution network resilience and voltage security issues, energy not supplied and voltage stability index along with power loss are considered as objective functions. According to the increase of distributed generators in the distribution network, the effect of these units is considered in the DFR problem. An improved particle swarm optimization is presented to solve the complex and non-convex DFR problem. The proposed algorithm is tested into two distribution systems including IEEE 33 and 70-node.

Reliability evaluation of active distribution network considering various active adjustment means

With the large-scale configuration of distribution automation and the widespread implementation of distributed generation (DG) and flexible load (FL), the distribution network can achieve active regulation, which makes the traditional fault restoration strategy and distribution network reliability evaluation more complicated. Given this background, a method of reliability evaluation for the active distribution network considering ‘supply-grid-load’ is proposed. On the supply side, a distribution network islanding model considering DG is established, with the objective of supplying power to the maximised amount of equivalent power load. On the grid side, the influence of distribution network automation on the distribution network reliability is elaborately analysed and the time-varying failure rate model of equipment which considers the life cycle characteristics is presented. On the load side, an incentive-based FL model is proposed based on the elastic coefficient matrix. Finally, simulation results of RBTS-BUS6 system demonstrate the effectiveness of the proposed model and method.

A systematic approach to service restoration in distribution networks

The progressive automation of distribution networks, along with the large amount of information gathered by smart devices, allow Distribution Management Systems (DMS) to be endowed with decision-making tools aimed at optimizing the service restoration process. This article presents an algebraically-assisted, heuristic procedure intended to guide the DMS operators in the selection of switching maneuvers during fault isolation and supply restoration of faulted MV feeders. At each step, the proposed methodology determines, among the possible switching sequences, the one that minimizes the impact of the interruption on unserved loads. The probabilistic character of the addressed problem involves the use of several statistical parameters, such as equipment failure rates, expected traveling times between network nodes, etc. The procedure is illustrated on a tutorial example and a real distribution system. The results are very close to those obtained with more exhaustive search procedures, at much shorter execution times, which makes the proposed approach also suitable for reliability-centered investment analysis.