Dispatching Automation System Research Articles

Data sharing mode of dispatching automation system based on distributed machine learning

AbstractThe difficulties of sending massive amounts of data between several data centres are examined in this work, with particular attention paid to how poorly current scheduling algorithms handle point‐to‐multipoint transfers and transmission time limits. In this research, a new method called multicast source‐based tree (MSBT) is proposed for effectively handling point‐to‐multipoint transmissions in a certain amount of time. By allowing receivers to simultaneously receive data from several source points, MSBT introduces the idea of ‘source selection’ for the creation of multicast tree structure‐based algorithms. Large data blocks are distributed as efficiently as possible using this method, which also guarantees effective transmission from a single‐source point to several recipient locations. Furthermore covered in the article is how PV producers and sellers' capacity allocation is affected by the discount rate. These results offer insightful information on how decisions are made in related sectors. The development of new energy big data platforms underscores their significance; leaders in the industry, like United Power, Vision Energy and Goldwind, serve as prime examples.

Anomaly Recognition, Diagnosis and Prediction of Massive Data Flow Based on Time-GAN and DBSCAN for Power Dispatching Automation System

Existing power anomaly detection is mainly based on analyzing static offline data. But this method takes a long time and has low identification accuracy when detecting timing and frequency anomalies, since this method requires offline screening, classification and preprocessing of the collected data, which is very laborious. Anomaly detection with supervised learning requires a large amount of abnormal data and cannot detect unknown anomalies. So, this paper innovatively proposes the idea of applying Time-series Generative Adversarial Networks (Time-GAN) in a dispatching automation system for the identification, diagnosis and prediction of massive data flow anomalies. First of all, regarding the problem of insufficient abnormal data, we use Time-GAN to generate a large number of reliable datasets for training fault diagnosis models. In addition, Time-GAN can ameliorate the imbalance between various types of data. Secondly, unsupervised learning methods such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-means are used to detect unknown anomalies that may exist in the power grid. Finally, some supervised learning methods are selected to compare with unsupervised learning methods. Experimental results show that the proposed algorithm has a higher recognition rate of known anomalies than other benchmark algorithms and it can find new unknown anomalies. It lays a good foundation for the safe, stable, high-quality and economical operation of the power grid.

A Multi-Stage Real-Time Fast Search Method for Closed-Loop Paths Based on Grid Hierarchical Partitioning Characteristics

Prior to switching operations, the dispatch automation system is required to be able to search for closed-loop paths quickly in real time. In order to improve the efficiency of closed-loop path search, this paper proposes a multi-stage real-time fast search method for closed-loop paths based on the characteristics of power grid hierarchical partitioning. First, we divide the closed-loop judgement process into three phases: initialization, acceptance of the closed-loop judgement command, and post-operation. Then, we define three types of nodes, including root nodes, same-layer contact nodes, and common nodes, and construct path data models for each type of node in accordance with the node liaison relationship in grid hierarchical zoning. In the initialization phase, we design a method for the automatic generation of real-time nodal path data models and study a hierarchical partitioned closed-loop path search method based on a nodal path data model for the phase of accepting closed-loop judgement commands. Next, we design a fast local correction method for nodal path models after the switch closure and disconnection operations in the post-operation idle phase are performed. Finally, a real power grid model is used as an example to test the above closed-loop path search method, which improves the search efficiency by eight times compared with the conventional breadth-first search method. The method is applicable to real large and complex power grids.

Time Series Prediction Method of Metrics of Dispatching Automation System Based on AI Platform

In view of the shortcomings of manual operation mode and passive anomaly perception in the current dispatching automation system, this paper provides a time series prediction method for the metrics of the dispatching automation system based on the artificial intelligence platform. Firstly, based on the collected metrics of the dispatching automation system, the time series prediction algorithm of metrics based on Long Short-Term Memory(LSTM) and LightGBM(LGB) combined model is studied. Then, the algorithm is integrated into a one-stop graphical interactive modeling tool and the model training process is drawn. Through the task is automatic split and distributed model training is automatically carried out on a regular basis. Then, the AI model service sharing technology based on Kubernetes is used to realize the model service release and automatic update, and the platform interactive development component is used to realize automatic online prediction and rolling iterative update. Finally, the actual data of the system metrics is used for example analysis, and the results show that the proposed method can realize the advance prediction of the system metrics, and realize the whole process automatic integration model training and prediction based on the artificial intelligence platform, and effectively improve the model training efficiency, meet the real-time and security requirements of the dispatching automation system, and is more suitable for engineering application scenarios.

Intelligent Identification over Power Big Data: Opportunities, Solutions, and Challenges

The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry. However, with the convergence and increase in power data flow, the data dispatching network and the main station dispatching automation system have encountered substantial pressure. Therefore, the method of online data resolution and rapid problem identification of dispatching automation systems has been widely investigated. In this paper, we perform a comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification, discuss unresolved research issues and outline future directions in this area. In particular, we divide intelligent identification over power big data into data acquisition and storage processes, anomaly detection and fault discrimination processes, and fault tracing for dispatching operations during communication. A detailed survey of the solutions to the challenges in intelligent identification over power big data is then presented. Moreover, opportunities and future directions are outlined.

Research on the Application of Artificial Intelligence Technology in Power System Intelligent Dispatching Automation

From the perspective of meeting the power quality requirements of users, the article analyses the characteristics of traditional voltage and reactive power control mode and the regional power grid reactive voltage optimization centralized closed-loop control mode (AVC system) based on the dispatch automation system (SCADA/EMS) from the perspective of technical management. Combining the reactive power/voltage real-time optimization control model, a real-time optimization control method of the regional power grid based on the improved differential evolution algorithm is proposed. The particle swarm algorithm is combined with the characteristics of reactive power/voltage control to improve the initial particle quality, reduce the optimization space, and introduce a crossover operator to improve the calculation speed and efficiency of the algorithm. Taking an actual regional power grid as an example, the simulation calculation of reactive power/voltage real-time optimization is carried out. The results show that the proposed algorithm and control strategy are feasible and effective.

Business Anomaly Detection Method of Power Dispatching Automation System Based on Clustering Under-Sampling in the Boundary Region

Timely detecting business anomaly in the power dispatching automation system is significant for the steady operation of the power grid. Though the imbalanced binary classification method in machine learning is an effective way to achieve the business anomaly detection of the system, the overlap of boundary samples is an urgent issue affecting the classification effect. An under-sampling method by removing the clustering noises of the majority samples in the boundary region is proposed. Firstly, KNN is used to search adjacent points of the majority class, and the boundary region and the safety region are divided according to the proportion of the majority samples in adjacent points. Secondly, DBSCAN is used to cluster the majority samples in the boundary region, and noise points are removed. Finally, it’s combined with the method based on model dynamic selection driven by data partition hybrid sampling (DPHS-MDS). The purpose of reducing the overlap degree of boundary samples, balancing the dataset and improving the classification effect is achieved. Experimental results show that the proposed method is superior to the relevant mainstream methods under F-measure and G-mean.

Research on Key Technologies of Automatic Acceptance of OCS Four Telemetry Signals

Generally speaking, the so-called power system dispatching automation, in fact, refers to the use of computer remote communication technology and remote control technology to monitor and coordinate the operation of the power system, and then process the problems and faults in the process of operation, and ultimately achieve the automated management and operation of the power system. In view of the development of smart grid, this paper introduces a fully automatic combined wave generator based on OCS system and human-machine interface. The power dispatching automation system needs the development of automation, intelligence and self-healing, and puts forward the importance of ensuring the normalization of the dispatching automation four remote signals. And the method of efficient point-to-point debugging starting from the master control unit or the remote engine node under the condition that the device is completely unpowered, and the functional requirements of the point-to-point debugging software using the method are elaborated in detail. Through the signal transmission, the monitoring main station analyzes and processes the information centrally, and finally realizes the unattended and remote monitoring of the substation.

Research on the Application of Integrated Technology in Power Dispatching Automation System

In order to improve the effect of power dispatching, staff must constantly explore new technical theory, perfect technical means and improve the effect of power dispatching. It is also of great significance to apply the integrated technology to the electric power dispatching automation system and to explore and extend it continuously, which is also of great significance to the exploration of the application value of the integrated technology.

Research on Power System Dispatching Automation Technology Based on Big Data

The perfect combination of power dispatch automation system and the analysis and processing of large amounts of data in big data mining technology can meet people’s needs for knowledge; at the same time, the application of mining technology in the power dispatch automation control system realizes the accurate collection and sorting of power data, Has a broad application space and practical application significance. This article introduces the source of grid data in the dispatch automation system, discusses how to extract and analyse the big data in the dispatch automation system efficiently and safely, and provide scientific data support for the economic and stable operation of the power grid and regional planning and development.

CIM/G graphics automatic generation in substation primary wiring diagram based on image recognition

With the further development of smart grids, people put forward more requirements for the intelligent level of the dispatching automation system, and the demands for unified substation standard, realization of unified association and sharing of models, data and graphics are gradually increasing. Relying on the CAD, PDF and other graphic format files of the substation, we use grid recognition technology based on image recognition and OCR to identify standard primitives, topological connections, device names and other information, and automatically draw standard CIM/G files. For the identified CIM/G file, we use related technologies of natural language to associate the primitives in the CIM/G file with the model data, and form the overall solution for a grid substation wiring diagram primitive recognition, text recognition, topology recognition, model association. We also construction substation graphic file recognition and construction system based on the image recognition to support the maintenance of the substation graphic inside the control center. Through the system deployment application, it is verified that the method can effectively reduce the workload of manual maintenance and improve work efficiency.

Cloud Platform Task Scheduling Strategy for Power Dispatching Automation System Based on Artificial Intelligence Algorithm

As the command and control center of the whole power grid operation, the power dispatching system has huge and complex data information, which makes the traditional power grid dispatching information platform difficult to meet the needs of power grid operation monitoring in information integration, analysis, calculation and storage. Therefore, cloud platform is introduced into the construction of power dispatching automation system. This paper takes the power dispatching automation cloud platform as the research object, studies its architecture, and proposes a cloud platform task scheduling model based on improved particle swarm optimization, aiming to improve the efficiency of cloud computing resource allocation, improve the quality of cloud services, and solve the task scheduling problem of the power dispatching automation system.

Research on Key Technologies of Power System Automation Application under Smart Grid

With the continuous development of the scale of the power grid and the advancement of the integrated mode of regulation and control, the amount of real-time monitoring information in the power grid system has grown rapidly today, which has imposed a great burden on all levels of dispatch monitoring. The old alarm function of the power dispatching automation system has been unable to better meet the needs of efficient monitoring. Therefore, it is necessary to brush, analyse, process and summarize the alarm information of each link in the monitoring business, so as to improve the overall operation status of the power grid. Awareness and processing speed of abnormal faults. Based on this, this paper discusses and studies the smart alarms of the smart grid, analyses the overall architecture, and analyses several smart alarm technologies used in the smart grid system on this basis, with a view to the subsequent development of smart grids and alarms the technical research provides a theoretical reference.

Low Voltage Distributed Photovoltaic Power Station Connected Estimation Model Based on Dispatch Automation System

A large number of distributed photovoltaic access grids pose great challenges to the safe and stable operation of the grid. In view of the fact that the dispatching automation system does not realize the real-time acquisition and monitoring of low-voltage distributed photovoltaic data, this paper proposes the station estimation method as an auxiliary means for real-time acquisition of low-voltage distributed photovoltaic power plants, and estimates the comprehensive low-voltage distributed photovoltaic power plants through appropriate algorithms. Access. Through case analysis, the deviation between the estimated value and the measured value is basically controlled within 8%, which proves the accuracy of the estimated model. This method is of great significance for the power dispatching department to strengthen the operation monitoring and statistical management of distributed photovoltaics, and to reasonably arrange the dispatching plan and coordinate the power supply.

Research on Integrated Construction Mode and Key Technologies of Regional Power Grid Dispatching System

This paper proposes a technical solution for the construction of an integrated system based on regional power grid dispatching system. The program is based on the principle of “economical application, resource reuse, information sharing, safety and reliability”. the scheme utilizes the software and hardware platform resources in the main network dispatching automation system in operation, and uses the modular construction method to construct the function of the distribution network automation master station. The key technologies used in the construction of the integrated system are described. The regional power grid deployment integration system is the trend and direction of power grid dispatching and distribution network dispatching system construction in small and medium-sized regions, and it is an effective way to rapidly promote power grid automation construction in small and medium-sized regions. A new scheme for the construction of the main distribution network integrated dispatch control system was explored.

Model design for big data clustering analysis of power dispatch automation system based on cloud computing platform

Cloud computing and big data are closely linked, profoundly affecting the way people live and work. They also have more established applications in power dispatch automation. This paper uses cloud computing as a technical tool to analyze the power dispatch automation system, and discusses the application aspects based on the model construction.

Fault-tolerant flexible lossless cluster compression method for monitoring data in smart grid

Big data in smart grid dispatch monitoring systems is susceptible to interference from processing delays and slow response times. Hence, a new fault-tolerant flexible lossless cluster compression method is proposed. This paper presents the Five-tuples (S, D, O, T, M) model, and builds a monitoring data processing platform based on hive. By deploying the dispatch host and monitoring servers under the cloud computing environment, where data nodes are respectively transformed by Deflate, Gzip, BZip2 and LZO lossless compression method. Taking the power dispatch automation system of Long-hai line as example, experimental results show that the cluster lossless compression ratio of BZip2 is greater than 81%; when data records reach twelve million, the compression ratio can be further improved to certain extent by using RCFile storage hive format, which has significant flexible features. Therefore, the new method proposed in this paper can improve the flexibility and fault-tolerant ability of big monitoring data processing in smart grid.

Application of Speech Recognition Technology in Power Grid Dispatching Automation

In recent years, with the rapid development of social economy, China’s investment in power grid dispatching automation system has also been increasing year by year to meet the increasing demand for dispatching of modern power grids. Under this background, the smart grid system characterized by information, automation, intelligence, and interaction has become the trend of future electric power development. Voice human-machine interaction technology as an advanced interactive technology has also started in the electric power intelligent dispatch system. Used in the application. This article mainly expounds the development status of intelligent dispatching system and the application of human-computer interaction technology in intelligent dispatching system. It also analyzes speech recognition technology, speech synthesis technology and typical Chinese speech recognition system in speech human-computer interaction technology, and focuses on intelligence. The design and implementation of voice human-computer interaction technology in the dispatching system, with a view to provide theoretical guidance for the development of China’s power dispatch system.

Integrated Smart Warning Testing Based on Testing Platform of Dispatching Automation System

With the popularization and application of power dispatching automation system in power grid, the integrated smart warning (ISW) has been widely used. A hidden hazard or problem in software may cause the dispatcher and operator to grasp inaccurate operation of power grid, which will affect the security of power grid operation in a wide range. The ISW software is tested and evaluated based on testing platform of dispatching automation system in this paper. By simulating power grid operation under fault conditions, the simulated primary and secondary steady-state signals are sent to ISW software. At the same time, WAMS and RELAY mocks are constructed to generate fault report, and the analysis results are also sent to ISW by means of message. It not only simplifies the testing environment, but also meets the requirements of ISW function testing. Finally, the testing results are analyzed, and a comprehensive quality index is given to evaluate the software quality. It will improve dispatcher ability to overall aware the power grid states and to handle emergency of equipment faults.

Integrated Modeling between Smart Substation and Dispatch Automation System

Abstract – Based on technical supporting systems for smart grid dispatch and smart substation system and according to the functional demand of dispatch master station to the substation, an integrated modeling scheme for coordinated sharing of models/images and seamless communication between dispatch master station and smart substation is proposed, by which practicable converting rules between IEC 61850-based model and IEC 61970-based model are drafted; a unified data model-based mapping approach for IEC 61850-based model and IEC 61970-based model is put forward; by means of splitting/merging technique of models and self-converting technique of Ids of graphs and so on, the integrated modeling between dispatch master station and smart substation is implemented; utilizing message bus service of dispatch master station and manufacturing message specification (MMS) protocol stack, the IEC 61850 protocol-based communication at dispatch master station side is attained, thus the coordinated sharing of models/imag...