Engineering › Electrical and Electronic Engineering

Smart Grid and Power Systems

Works Count: 37095

Wikipedia

Description

This cluster of papers focuses on the technology, development, and applications of smart grid systems, including topics such as cloud computing, big data, renewable energy integration, distribution automation, intelligent control, and reliability analysis in the context of electric power systems. The papers also discuss energy efficiency and the impact of advanced metering infrastructure (AMI) on power supply.

Keywords

Smart Grid; Cloud Computing; Big Data; Power System; Renewable Energy; Distribution Automation; Electric Power; Intelligent Control; Reliability Analysis; Energy Efficiency

Advancing China?s Smart Grid: Phasor Measurement Units in a Wide-Area Management System

2015-08-14

Chao Lü , Shi Bonian , Xiaochen Wu +1 more

In developing a smart grid the measurement technology used plays a fundamental role for advanced power-system analysis and control. Phasor measurement units (PMUs), as part of a wide-area measurement system … In developing a smart grid the measurement technology used plays a fundamental role for advanced power-system analysis and control. Phasor measurement units (PMUs), as part of a wide-area measurement system (WAMS), increasingly constitute the critical measurement infrastructures for transmission and generation systems. As of 2013, approximately 2,400 PMU sets had been deployed in power grids in China, covering all 500-kV substations in the country and a number of important power plants and 220/110-kV substations. In addition, more than 30 WAMS center stations are in service, providing important dynamic information about power system operation. Most of these PMU devices were deployed after 2006, when an article introducing the basic PMU/WAMS architectures and functions in China was published in IEEE Power & Energy Magazine. Here, we will briefly summarize recent and emerging developments in China?s PMU/WAMS communication and synchronization network and then present some major advanced applications and novel pilot projects utilizing synchrophasor measurement technology.

Applications of Internet of Things on smart grid in China

2011-04-07

Jianming Liu , Xiangzhen Li , Xi Chen +2 more

Smart grid can apply Internet of Things (IoT) technologies for creating various intelligent services. In this paper, the basic requirements of the smart grid in China are reviewed. The development … Smart grid can apply Internet of Things (IoT) technologies for creating various intelligent services. In this paper, the basic requirements of the smart grid in China are reviewed. The development of most aspects of the smart grid would be enhanced by the applying the technologies of IoT. The architecture of IoT for the smart grid in China is introduced, which can be expressed as three layers: the perception layer, the network layer and the application layer. Various information and communication techniques of IoT applied on smart grid is discussed. Particularly, the IoT application solutions are provided in detail for power transmission line monitoring, smart patrol, smart home and electric vehicle management.

Advanced Pattern Discovery-based Fuzzy Classification Method for Power System Dynamic Security Assessment

2015-02-03

Fengji Luo , Zhaoyang Dong , Guo Chen +4 more

Dynamic security assessment (DSA) is an important issue in modern power system security analysis. This paper proposes a novel pattern discovery (PD)-based fuzzy classification scheme for the DSA. First, the … Dynamic security assessment (DSA) is an important issue in modern power system security analysis. This paper proposes a novel pattern discovery (PD)-based fuzzy classification scheme for the DSA. First, the PD algorithm is improved by integrating the proposed centroid deviation analysis technique and the prior knowledge of the training data set. This improvement can enhance the performance when it is applied to extract the patterns of data from a training data set. Secondly, based on the results of the improved PD algorithm, a fuzzy logic-based classification method is developed to predict the security index of a given power system operating point. In addition, the proposed scheme is tested on the IEEE 50-machine system and is compared with other state-of-the-art classification techniques. The comparison demonstrates that the proposed model is more effective in the DSA of a power system.

Analysis, Synthesis and Design of Hydraulic Servosystems and Pipelines

1981-03-01

T.J. Viersma , B. W. Andersen

Analysis, synthesis, and design of hydraulic servosystems and pipelines , Analysis, synthesis, and design of hydraulic servosystems and pipelines , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی Analysis, synthesis, and design of hydraulic servosystems and pipelines , Analysis, synthesis, and design of hydraulic servosystems and pipelines , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

View PDF Chat

Substation automation. IED integration and availability of information

2003-03-01

John D. McDonald

The advent of power industry deregulation has placed greater emphasis on the availability of information, the analysis of this information, and the subsequent decision-making to optimize system operation in a … The advent of power industry deregulation has placed greater emphasis on the availability of information, the analysis of this information, and the subsequent decision-making to optimize system operation in a competitive environment. Intelligent electronic devices (IEDs) being implemented in substations contain valuable information, both operational and nonoperational, needed by many user groups within the utility. The challenge facing utilities is determining a standard integration architecture that meets the utility's specific needs, can extract the desired operational and nonoperational information, and deliver this information to the users who have applications to analyze the information. This article provides an overview of substation integration and automation fundamentals and focuses on best practices.

Review of Smart Grid Comprehensive Assessment Systems

2011-01-01

Qiang Sun , Xubo Ge , Lin Liu +4 more

Smart Grid is an inevitable trend of power grid, and smart grid comprehensive assessment system can conduct a comprehensive assessment of the overall characteristics of smart grid, which can reflect … Smart Grid is an inevitable trend of power grid, and smart grid comprehensive assessment system can conduct a comprehensive assessment of the overall characteristics of smart grid, which can reflect the current level of the development, find the weakness and the constraints in the network development, identify the distance to the target, ensure the smart grid development achieve a unification of the quality, speed and efficiency. At present, many countries are studying on the smart grid comprehensive assessment systems. This paper analyzes the IBM Smart Grid Maturity Model, the DOE Smart Grid Development Evaluation System, the EPRI Smart Grid Construction Assessment Indicators, and the EU Smart Grid Benefits Assessment System, and compares the development levels, evaluation objects, target ranges, applications differences between these systems and the "two type" grid index system, the smart grid development assessment index system, and the smart grid pilot project evaluation indicator system suggested by China. The thoughts and the principles of building smart grid comprehensive assessment system, and the issues which should be noted are proposed here, which can provide necessary references and supports to construct the smart grid comprehensive assessment system.

Internet-based SCADA display system

2002-01-01

Bin Qiu , Hoay Beng Gooi , Yilu Liu +1 more

In the deregulated environment, information is the key to secure operation, profitability, customer retention, market advantage, and growth for the power industry. The rapid development of the Internet and distributed … In the deregulated environment, information is the key to secure operation, profitability, customer retention, market advantage, and growth for the power industry. The rapid development of the Internet and distributed computing have opened the door for feasible and cost-effective solutions. This article describes and demonstrates a unique Internet-based application in a substation automation system that is implemented based on the existing system control and data acquisition (SCADA) system and very large-scale integration (VLSI) information technologies (IT). The user can view the real-time data superimposed on one-line diagrams generated automatically using VLSI placement and routing techniques. In addition, the user can also control the operation of the substation at the server site. The choice of Java technologies, such as Java Native Interface (JNI), Java Remote Method Invocation (RMI), and Enterprise Java Bean (EJB), offers unique and powerful features, such as zero client installation, on-demand access, platform independence, and transaction management for the design of the online SCADA display system.

Technique for contingency monitoring and voltage collapse prediction

1998-01-01

M. Moghavvemi , F.M. Omar

Investigation and online monitoring of power system stability have become vital factors to electric utility suppliers. At present power system utilities operate very close to the limit of system stability … Investigation and online monitoring of power system stability have become vital factors to electric utility suppliers. At present power system utilities operate very close to the limit of system stability owing to an increasing number of new economic and environmental restrictions. Researchers have been trying to find out the most effective way for online system status monitoring, so that necessary precautions can be taken prior to voltage collapse. Several methods have been proposed for analysing voltage collapse phenomena. An effective method for online system status monitoring and thus voltage collapse prediction is described. The basic methodology implied in this technique is the investigation of each line of the system through calculating line stability indices. The proposed method was tested on the IEEE 24-bus reliability test system and has been found to be accurate and precise in voltage collapse prediction. A comparative study with other methods has also been carried out indicating that the proposed method has some advantages over the others.

Next-Generation Monitoring, Analysis, and Control for the Future Smart Control Center

2010-07-29

Pei Zhang , Fangxing Li , Navin Bhatt

This paper proposes a vision of next-generation monitoring, analysis, and control functions for tomorrow's smart power system control centers. The paper first reviews the present control center technology and then … This paper proposes a vision of next-generation monitoring, analysis, and control functions for tomorrow's smart power system control centers. The paper first reviews the present control center technology and then presents the vision of the next-generation monitoring, analysis, and control functions. The paper also identifies the technology and infrastructure gaps that must be filled, and develops a roadmap to realize the proposed vision. This smart control center vision is expected to be a critical part of the future smart transmission grid.

Blackout Model Based on OPF and its Self-organized Criticality

2006-08-01

Shengwei Mei , Yadana , Weng Xiaofeng +1 more

Based on the essence of self-organized criticality and optimal power flow (OPF), this paper develops a model to capture the cascading failures and blackouts in power systems, which avoids some … Based on the essence of self-organized criticality and optimal power flow (OPF), this paper develops a model to capture the cascading failures and blackouts in power systems, which avoids some shortcomings of existent blackout models. The proposed model contains two dynamics, one is the fast dynamics which simulates the serial blackouts in power system, and the other is the slow dynamics which reflects the growth of the power system. Simulations in IEEE-30 bus system with the proposed model show that, the processing of the cascading and blackout can be captured by the fast dynamics, together with the self-organized criticality property of fast dynamic respect to the micro-scale. Besides, the macro-scale of self-organized criticality of power system can be revealed from the viewpoint of total load demand vs. the total network transfer capability. Furthermore, improving the transmission ability of network could effectively prevent blackout and reduce its risk.

Application of load survey systems to proper tariff design

1997-01-01

C.S. Chen , Jenq-Neng Hwang , C.W. Huang

This paper proposes a proper rate making strategy for a public owned utility by taking into account the customer load characteristics. The load survey system has been well designed by … This paper proposes a proper rate making strategy for a public owned utility by taking into account the customer load characteristics. The load survey system has been well designed by sampling theory to find the customers for power consumption information collection. By this manner, the typical load patterns derived can effectively represent the load behavior of each customer class. The load patterns of each test customer during different seasons are solved by statistical analysis according to the load information collected. The seasonal typical load pattern of each customer class is then determined by integrating the load patterns of the same type customers. The power consumption of the customer class is then estimated by the typical class load pattern and the energy consumption of all customers in the same class, which can be retrieved from the customer information database. The typical load pattern of whole power system is then determined by aggregating the power consumption of all customer classes. The estimated system load consumption is then compared to the actual system load profile, it is found that a rather accurate system load profile can be predicted by the load survey system.

Effective Load Carrying Capability of Generating Units

1966-08-01

L. L. Garver

The theory of loss-of-load probability mathematics has been generalized so that the effective load carrying capability of a new generating unit may be estimated using only graphical aids. A parameter … The theory of loss-of-load probability mathematics has been generalized so that the effective load carrying capability of a new generating unit may be estimated using only graphical aids. A parameter m is introduced to characterize the loss-of-load probability as a function of reserve megawatts.

Feature selection for transient stability assessment based on kernelized fuzzy rough sets and memetic algorithm

2014-08-23

Xueping Gu , Yang Li , Jinghua Jia

View PDF Chat

A New Algorithm for Service Restoration in Distribution Systems

1989-01-01

Kenichi Aoki , K. Nara , Masaru Itoh +2 more

This paper proposes a new algorithm to quickly. restore the deenergized loads in a distribution system by using the sectionalizing switches. The computational burden and the solution accuracy of the … This paper proposes a new algorithm to quickly. restore the deenergized loads in a distribution system by using the sectionalizing switches. The computational burden and the solution accuracy of the algorithm is improved by using the concept of the dual effective gradient method. Test results on practical system are given to demonstrate that the algorithm can be used in actual, large scale urban distribution system applications.

An Online Intelligent Alarm-Processing System for Digital Substations

2011-04-06

Liuhong Wei , Wenxin Guo , Fushuan Wen +3 more

A flood of alarm messages in an automatic digital substation makes the monitoring task a significant challenge for the operators in a remote control center, especially under fault scenarios. An … A flood of alarm messages in an automatic digital substation makes the monitoring task a significant challenge for the operators in a remote control center, especially under fault scenarios. An online intelligent alarm-processing system is developed based on the architecture of the digital substation. First, real-time alarms are classified according to the IEC 61850 standard in order to provide synthesized and organized alarms for the alarm-processing procedure in the next step. Then, a new and systematic alarm-processing approach for digital substations is developed. Two modules (i.e., the generation of candidate hypotheses and the truth evaluation for the hypotheses) are included in the developed approach, and these two modules are operating in parallel in online implementation. This approach could not only determine the fault/disturbance cause but also the missing or false alarms as well as the causes of the false alarms. According to actual application requirements, an online intelligent alarm-processing system is developed and applied in the Xingguo substation-the first digital substation in Jiangxi Province, China. Finally, an actual alarm-processing scenario serves to demonstrate the presented alarm-processing method as well as the developed software system.

Effects of unbalanced voltage on the operation performance of a three-phase induction motor

1999-06-01

Ching-Yin Lee

This paper uses a real load test to investigate the effects of an unbalanced voltage supply on an induction motor's performance. Based upon various experiments, including: (1) cases with the … This paper uses a real load test to investigate the effects of an unbalanced voltage supply on an induction motor's performance. Based upon various experiments, including: (1) cases with the same unbalance voltage factor but different unbalanced voltages; (2) cases with only one unbalanced voltage but different degrees of unbalance; and (3) cases with the same positive-sequence voltage but different negative-sequence voltages, the importance of the positive-sequence voltage in the motor's apparent performance and of the negative-sequence voltage in the hidden damage are pointed out. Finally, it is strongly suggested that the related regulations, and a motor's derating factor and temperature rise curves should be based on not only a voltage unbalance factor, but also the magnitude of the positive-sequence voltage.

Application of the Shapley Value on transmission cost allocation in the competitive power market environment

2002-01-01

Tan Xiao , Tek Tjing Lie

The Shapley Value of cooperative game theory is proposed to allocate the transmission cost incurred to accommodate all the loads. This method overcomes the drawbacks of conventionally used methods, such … The Shapley Value of cooperative game theory is proposed to allocate the transmission cost incurred to accommodate all the loads. This method overcomes the drawbacks of conventionally used methods, such as postage-stamp method and MW-miles method, and encouraging the economically optimal usage of the transmission facilities. The simulation results showed that the allocation solution met the requirements of an appropriate pricing strategy and generated the allocation solution that impartial observers would consider fair and desirable.

Application of a Real-Time Data Compression and Adapted Protocol Technique for WAMS

2014-07-02

Fang Zhang , Lin Cheng , Xiong Li +3 more

This paper proposes a real-time data compression and adapted protocol technique for wide-area measurement systems (WAMS). The compression algorithm combines exception compression (EC) with swing door trending (SDT) compression. The … This paper proposes a real-time data compression and adapted protocol technique for wide-area measurement systems (WAMS). The compression algorithm combines exception compression (EC) with swing door trending (SDT) compression. The compression logic is designed to perform this algorithm in real time. Selection of compression parameters and data reconstruction are presented. An adapted protocol is introduced by improving the format of data frames defined by IEEE standard C37.118 for compressed data packets. The proposed compression technique and protocol were applied to the phasor measurement units (PMUs) of a hydropower plant in Guizhou Power Grid in Southwest China. A low-frequency oscillation incident was recorded by this technique. The raw, compressed and reconstructed data were analyzed to verify the compression and determine the accuracy of the proposed technique. Also, the wavelet-based data compression, the standalone EC and SDT are compared with the proposed compression technique. Our results demonstrated that this compression can reach the compression ratios in the range of 6 to 11. Also, this compression and adapted protocol technique can reduce the size of data packets by approximately 75% with high accuracy in both dynamic and steady states.

Protective Relaying of Power Systems Using Mathematical Morphology

2009-01-01

Qiong Wu , Zhengyu Lü , Tianyao Ji

The Origin and Spread of the Grid-Pattern Town

2018-01-01

Dan Stanislawski

Research Status and Development Trend of Smart Grid

2009-01-01

Xusheng Yang

The future development trend of electric power grid is smart grid, which include such features as flexible, clean, secure, economic, friendly and so on.The concept and function characteristics of smart … The future development trend of electric power grid is smart grid, which include such features as flexible, clean, secure, economic, friendly and so on.The concept and function characteristics of smart grid are introduced in this paper firstly;then the progress of research on smart grid home and abroad as well as the relation between key technologies and smart gird are analyzed in detail, and it is pointed out that the Agent based distributed cooperation, control, simulation and decision-making, system integeration of distributed enengy, knowledge based comprehensive decision support are the key development trend of smart grid in future.The construction of smart grids in China is a very complicated system engineering, for this reason some concrete suggestions are made, such as fully taking advantages of integrated management, carrying out architectural design of smart grids in China;drafting pilot plans and implementation schemes;coordinating secure and economic operation of power generation, transmission and distribution;paying special attention to theoretical and technological innovation and application;overall considering the planning, construction, renovation and technology upgrating of power grid, to push the research and construction of smart grid in China actively and orderly.

Consideration of Technology for Constructing Chinese Smart Grid

2009-01-01

Shijie Xiao

Taking the current situation of smart grid research as the background,and from the analysis of the difference between smart grid and traditional grid as well as situation of constructing smart … Taking the current situation of smart grid research as the background,and from the analysis of the difference between smart grid and traditional grid as well as situation of constructing smart grid at home and abroad,some viewpoints of constructing Chinese smart grid are expatiated,and the research directions of concern about constructing Chinese smart grid are analyzed emphatically.

Survey on Smart Grid Technology

2009-01-01

Jie Shen

In this paper the connotation of smart grid is expounded, the present research status of smart grid home and abroad as well as the practical significance of developing smart grid … In this paper the connotation of smart grid is expounded, the present research status of smart grid home and abroad as well as the practical significance of developing smart grid in China are summarized. As a reference for relative researchers, this paper analyzes the conditions to develop smart grid in China, and points out the key technological problems to be solved for the development of smart grid in the fields of power network topology, communication system, metering infrastructure, demand side management, intelligent dispatching, power electronic equipments, distributed generation integration etc..

The Fault Causes of Overhead Lines in Distribution Network

2016-01-01

Li Wang

The paper introduces the typical fault causes in distribution system, especially the fault in overhead line. The data in the paper are from the surveys by different agencies all around … The paper introduces the typical fault causes in distribution system, especially the fault in overhead line. The data in the paper are from the surveys by different agencies all around the world. It is noted that the statistics are different with each other for many reasons, and some of them are old which was finished in 1980s. The fault causes in different areas (Nordic, North American and China) are introduced separately. Some typical fault causes (trees, animals, lightning, and vehicles) are subdivided and analyzed in detail. Some waveforms of different faults are shown in the paper too. At last, the most frequent fault causes which should be focused on are proposed by the paper.

View PDF Chat

Digital Signal Processing in Power System Protection and Control

2011-01-01

Waldemar Rebizant , Janusz Szafran , Andrzej Wiszniewski

Cascading failure model in power grids using the complex network theory

2016-07-25

Wenli Fan , Zhigang Liu , Ping Hu +1 more

The massive power flow transferring triggers the node overload cascade, which further activates the protection system hidden failures. In this study, we propose a cascading failure model based on complex … The massive power flow transferring triggers the node overload cascade, which further activates the protection system hidden failures. In this study, we propose a cascading failure model based on complex network theory by combining the node overload failures and hidden failures of transmission lines in blackouts together. The model concerns the electrical characteristics, which has not been involved in the existed cascading failure model when modelling node loads. The cascading failure simulations on the 500 kV Center China power grid and the IEEE‐300‐bus test system demonstrate that the proposed cascading failure model with node load built on electrical characteristics can bring better network invulnerability than the model with that constructed on pure structure topology. Meanwhile, the proposed model can better exhibit the negative aspects of hidden failures in the blackouts. The deliberate attacks based on high‐risk nodes can decrease the invulnerability of power grids more seriously compared with those based on high‐degree and high‐load nodes. The results provide a new way to analyse the power grid cascading failure mechanism based on the complex network theory.

Application and analysis of ZigBee technology for Smart Grid

2010-12-01

Qiang Zhang , Yugeng Sun , Zhenhui Cui

Aiming at the requirement for monitoring and controlling information in Smart Grid, the applications of ZigBee technology for Smart Grid were analyzed. After ZigBee technology and its features for Smart … Aiming at the requirement for monitoring and controlling information in Smart Grid, the applications of ZigBee technology for Smart Grid were analyzed. After ZigBee technology and its features for Smart Grid were introduced, the prospects of ZigBee applications for Smart Grid were discussed in the cases of ZigBee applications in Smart Grid HAN, fault locating and UHV transmission lines monitoring. Some attentions should be paid to ZigBee applications for Smart Grid were proposed. Finally, ZigBee technology would be integrated with Smart Grid gradually and become an indispensable basic wireless communication technology in constructing Smart Grid were pointed out.

Study on technology system of self-healing control in smart distribution grid

2011-10-01

Dongli Jia , Xiaoli Meng , Xiaohui Song

Smart distribution grid is an important part of smart grid, which connects the main network and user-oriented supply. As an "immune system", self-healing is the most important feature of smart … Smart distribution grid is an important part of smart grid, which connects the main network and user-oriented supply. As an "immune system", self-healing is the most important feature of smart grid. Major problem of self-healing control is the 'uninterrupted power supply problem', that is, real-time monitoring of network operation, predicting the state power grid, timely detection, rapid diagnosis and elimination of hidden faults, without human intervention or only a few cases. First, the paper describes major problems, which are solved by self-healing control in smart distribution grid, and their functions. Then, it analysis the structure and technology components of self-healing control in smart distribution grid, including the base layer, support layer and application layer. The base layer is composed of the power grid and its equipments, which is the base for smart grid and self-healing control. The support layer is composed of the data and communication. High-speed, bi-directional, real-time and integrated communications system is the basis of achieving power transmission and the use of high efficiency, reliability and security, and the basis for intelligent distribution network and the key steps of self-prevention and self-recovery in distribution grid. The application layer is composed of Monitoring, assessment, pre-warning/analysis, decision making, control and restoration. Six modules are interconnected and mutual restraint. The application layer is important means of self-prevention and self-recovery in distribution grid. Through the research and analysis on the relationship and the technical composition of six modules in the application layer, the paper divides running states of smart grid distribution grid having self-healing capabilities into five states, which are normal state, warning state, critical state, emergency state and recovery state, and defines the characteristics and the relationship of each state. Through investigating and applying self-healing control in smart distribution grid, smart distribution grid can timely detect the happening or imminent failure and implement appropriate corrective action, so that it does not affect the normal supply or minimize their effects. Power supply reliability is improved observably and outage time is reduced significantly. Especially in extreme weather conditions, the distribution grid will give full play to its self-prevention and self-recovery capability, give priority to protecting people's life and provide electricity for the people furthest.

Research on practical power system stability analysis algorithm based on modified SVM

2018-05-08

Kaiyuan Hou , Guanghui Shao , Haiming Wang +4 more

Stable and safe operation of power grids is an important guarantee for economy development. Support Vector Machine (SVM) based stability analysis method is a significant method started in the last … Stable and safe operation of power grids is an important guarantee for economy development. Support Vector Machine (SVM) based stability analysis method is a significant method started in the last century. However, the SVM method has several drawbacks, e.g. low accuracy around the hyperplane and heavy computational burden when dealing with large amount of data. To tackle the above problems of the SVM model, the algorithm proposed in this paper is optimized from three aspects. Firstly, the gray area of the SVM model is judged by the probability output and the corresponding samples are processed. Therefore the clustering of the samples in the gray area is improved. The problem of low accuracy in the training of the SVM model in the gray area is improved, while the size of the sample is reduced and the efficiency is improved. Finally, by adjusting the model of the penalty factor in the SVM model after the clustering of the samples, the number of samples with unstable states being misjudged as stable is reduced. Test results on the IEEE 118-bus test system verify the proposed method.

View PDF Chat

Analysis and recommendations for the adaptability of China's power system security and stability relevant standards

2017-12-25

Yinbiao Shu , Yong Tang

In developing power grids, setting standards is critical to its success. The development of China's power industry has proposed new requirements for power systems to ensure secure and stable operations. … In developing power grids, setting standards is critical to its success. The development of China's power industry has proposed new requirements for power systems to ensure secure and stable operations. The principal standards for the security and stability of China's current power systems are analyzed in terms of operational control, generator-grid coordination and simulation. The shortcomings are pointed out and the directions of future development are discussed. In the end, the study highlighted the following key areas that require further research and improvement: the evaluation criteria of power system security and stability should be improved to ensure the secure and stable operation of China's power systems; the operational control standards should be constantly enhanced to increase the reliability and flexibility of operational control strategies; generator-grid coordination standards should be upgraded to improve the coordination between the generator control protection system and the grid; and the simulation methodology should be standardized in future power system security and stability research.

Real-time transient stability assessment in power system based on improved SVM

2018-10-09

Wei Hu , Zongxiang Lu , Shuang Wu +4 more

Due to the strict requirements of extremely high accuracy and fast computational speed, real-time transient stability assessment (TSA) has always been a tough problem in power system analysis. Fortunately, the … Due to the strict requirements of extremely high accuracy and fast computational speed, real-time transient stability assessment (TSA) has always been a tough problem in power system analysis. Fortunately, the development of artificial intelligence and big data technologies provide the new prospective methods to this issue, and there have been some successful trials on using intelligent method, such as support vector machine (SVM) method. However, the traditional SVM method cannot avoid false classification, and the interpretability of the results needs to be strengthened and clear. This paper proposes a new strategy to solve the shortcomings of traditional SVM, which can improve the interpretability of results, and avoid the problem of false alarms and missed alarms. In this strategy, two improved SVMs, which are called aggressive support vector machine (ASVM) and conservative support vector machine (CSVM), are proposed to improve the accuracy of the classification. And two improved SVMs can ensure the stability or instability of the power system in most cases. For the small amount of cases with undetermined stability, a new concept of grey region (GR) is built to measure the uncertainty of the results, and GR can assessment the instable probability of the power system. Cases studies on IEEE 39-bus system and realistic provincial power grid illustrate the effectiveness and practicability of the proposed strategy.

View PDF Chat

XGBoost-Based Algorithm Interpretation and Application on Post-Fault Transient Stability Status Prediction of Power System

2019-01-01

Minghua Chen , Qunying Liu , Shuheng Chen +3 more

The artificial intelligence (AI) techniques have been widely used in the transient stability analysis of a power system. They are recognized as the most promising approaches for predicting the post-fault … The artificial intelligence (AI) techniques have been widely used in the transient stability analysis of a power system. They are recognized as the most promising approaches for predicting the post-fault transient stability status with the use of phasor measurement units data. However, the popular AI methods used for power systems are often "black boxes," which result in the poor interpretation of the model. In this paper, a transient stability prediction method based on extreme gradient boosting is proposed. In this model, a decision graph and feature importance scores are provided to discover the relationship between the features of the power system and transient stability. Meanwhile, the key features are selected according to the feature importance scores to remove redundant variables. The simulation results on the New England 39-bus system have demonstrated the superiority of the proposed model over the prior methods in the computation speed and prediction accuracy. Finally, an algorithm is proposed to interpret the prediction results for a specific fault of the power system, which further improves the interpretability of the model and makes it attractive for real-time transient stability prediction.

View PDF Chat

A review of machine learning for new generation smart dispatch in power systems

2019-11-19

Linfei Yin , Qi Gao , Lulin Zhao +4 more

Bibliography on the Application of Probability Methods in Power System Reliability Evaluation 1971-1977

1978-11-01

Power System Engineering Committee

This paper presents a bibliography of selected papers on the subject of power system reliability evaluation. This paper presents a bibliography of selected papers on the subject of power system reliability evaluation.

The Origin and Spread of the Grid-Pattern Town

1946-01-01

Dan Stanislawski

Bibliography on the application of probability methods in power system reliability evaluation

1999-01-01

R.N. Allan , R. Billinton , A.M. Breipohl +1 more

This paper presents a bibliography of papers on the subject of power system reliability evaluation. Papers in such areas as probabilistic load flow, probabilistic production costing, probabilistic transient stability evaluation … This paper presents a bibliography of papers on the subject of power system reliability evaluation. Papers in such areas as probabilistic load flow, probabilistic production costing, probabilistic transient stability evaluation etc. have not been included except where they specifically address power system reliability evaluation. It includes material which has become available since the publication of the five previous papers. "Bibliography on the Application of Probability Methods in Power System Reliability Evaluation", IEEE Trans. on Power Apparatus and Systems PAS-91, 1972, pp.649-60; PAS-97, 1978, pp.2235-42; PAS-103, 1984, pp. 275-82; IEEE Trans. on Power Systems, Vol. 3, No. 4, Nov. 1988, pp. 1555-64, and Vol. 9, No. 1, Feb. 1994, pp. 41-9.

Bibliography on the application of probability methods in power system reliability evaluation: 1982-7

1988-11-01

K-Means and Alternative Clustering Methods in Modern Power Systems

2023-01-01

Seyed Mahdi Miraftabzadeh , Cristian Giovanni Colombo , Michela Longo +1 more

As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data accessibility and advancements in … As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data accessibility and advancements in computational capabilities, clustering algorithms, including K-means, are becoming essential tools for researchers in analyzing, optimizing, and modernizing power systems. This paper presents a comprehensive review of over 440 articles published through 2022, emphasizing the application of K-means clustering, a widely recognized and frequently used algorithm, along with its alternative clustering methods within modern power systems. The main contributions of this study include a bibliometric analysis to understand the historical development and wide-ranging applications of K-means clustering in power systems. This research also thoroughly examines K-means, its various variants, potential limitations, and advantages. Furthermore, the study explores alternative clustering algorithms that can complete or substitute K-means. Some prominent examples include K-medoids, Time-series K-means, BIRCH, Bayesian clustering, HDBSCAN, CLIQUE, SPECTRAL, SOMs, TICC, and swarm-based methods, broadening the understanding and applications of clustering methodologies in modern power systems. The paper highlights the wide-ranging applications of these techniques, from load forecasting and fault detection to power quality analysis and system security assessment. Throughout the examination, it has been observed that the number of publications employing clustering algorithms within modern power systems is following an exponential upward trend. This emphasizes the necessity for professionals to understand various clustering methods, including their benefits and potential challenges, to incorporate the most suitable ones into their studies.

View PDF Chat

Fusion application of intelligent sensing technology and artificial intelligence algorithm in information verification of new energy grid connection monitoring

2025-06-23

Jianwei Ma , Zhongqiang Zhou , Sheng Chen +4 more | International Journal of Emerging Electric Power Systems

Abstract Traditional monitoring systems rely on different types of sensors in the field of new energy grid connection monitoring. The collected data have inconsistent problems; the monitoring method is not … Abstract Traditional monitoring systems rely on different types of sensors in the field of new energy grid connection monitoring. The collected data have inconsistent problems; the monitoring method is not real-time enough; the fault detection and anomaly recognition accuracy is low. This paper combines intelligent sensing technology and GNNs (Graph Neural Networks) to design a more efficient, smart, and precise new energy grid connection monitoring information verification method. High-precision intelligent sensors are used to collect multidimensional data of the new energy grid connection system in real-time, and data fusion technology is used to solve the data inconsistency problem between different sensors to ensure efficient and accurate data collection. The graph neural network algorithm framework is used to build the relationship diagram of nodes and edges, and the GNN model is used for information verification and fault detection. The advantages of graph structure are used to accurately obtain the information transmission of each node and improve the accuracy and real-time performance of fault detection. The collected data of the intelligent sensor and the graph neural network model are synergistically optimized to form a closed loop of data processing, model training, and fault prediction. The experimental results show that among the 10 different folds, the GNN model has a lower loss value, with an average loss value of 0.312, which can reduce the error in the information transmission process when processing the monitoring information of the new energy grid connection system; the fault recognition rates of the GNN model in abnormal voltage, current, frequency, and temperature scenarios are 0.92, 0.87, 0.9, and 0.85, respectively, which is suitable for complex fault detection tasks.

Research on Fault Diagnosis of Synchronous Generators Based on Dual Path SeNet and Improved ViT

2025-06-16

Haijie Mao , W. Li , Xianyong Feng +1 more | Engineering Research Express

Abstract To tackle the challenges in fault diagnosis of synchronous generators, which often rely heavily on expert knowledge and result in low diagnostic accuracy, and to address the overfitting issues … Abstract To tackle the challenges in fault diagnosis of synchronous generators, which often rely heavily on expert knowledge and result in low diagnostic accuracy, and to address the overfitting issues associated with Vision Transformer (ViT)-based models due to their large parameter size when applied to limited data samples, this paper introduces an innovative fault diagnosis approach that integrates Dual-Path SeNet with an enhanced&#xD;ViT architecture. Initially, continuous wavelet transform (CWT) is applied to convert raw one-dimensional electrical signals into two-dimensional time-frequency images, effectively capturing both temporal and frequency characteristics. These images are then processed by the Dual-Path SeNet for deep and multi-scale feature extraction.&#xD;Subsequently, depthwise separable convolutional neural networks are used to transform the extracted feature maps into long vectors, significantly reducing the parameter size associated with patch processing and linear mapping operations in the original ViT.&#xD;These vectors are then fed into a multi-head attention mechanism to extract temporal features. To further reduce the parameter size, sequence pooling is employed to replace the classification head in the original ViT, enhancing the model’s lightweight design.&#xD;Experimental results on three fault types demonstrate that the proposed method reduces parameter size by over 50% and achieves a diagnostic accuracy of 99.07%, highlighting its effectiveness in synchronous generator fault diagnosis.&#xD;

Application Exploration of Multi-Scale Edge Detection and SIFT Feature Fusion in Digital Twin Pattern Recognition for Power Grids

2025-06-13

Chunmei Zhang , Xingque Xu , Yongjian Li +2 more | International Journal of Pattern Recognition and Artificial Intelligence

Research on smart grid data encryption algorithm based on new complex chaotic system

2025-06-09

Li Liu | Journal of Computational Methods in Sciences and Engineering

Smart grid systems necessitate robust data encryption to safeguard sensitive data. Hardware limitations and computational complexity, however, restrict the real-time applicability of encryption in certain smart grid environments. This investigation … Smart grid systems necessitate robust data encryption to safeguard sensitive data. Hardware limitations and computational complexity, however, restrict the real-time applicability of encryption in certain smart grid environments. This investigation proposes a novel encryption algorithm, the Genetic Algorithm-Enhanced 8-Dimensional Chaotic System (GA-8D chaotic system), based on a complex chaotic system enhanced by a genetic algorithm, to secure smart grid data. The data was collected from a simulated smart grid environment, comprising real-time grid load data and sensor inputs. The proposed GA-8D chaotic system technique integrates a Genetic Algorithm (GA) and an 8D chaotic system for strong key generation and encryption. This approach enhances encryption speed and security by evolving optimal parameters using genetic algorithms, thereby ensuring higher performance in smart grid applications. The 8D chaotic system encryption technique is utilized to securely encrypt data and sensor images within the smart grid, guaranteeing data integrity and confidentiality within the smart grid architecture. The proposed algorithm demonstrated superior performance in encryption speed (0.1 ms), training accuracy (0.98), security strength (98%), and computational efficiency (450 bits). The results indicate that the algorithm is scalable for smart grid data encryption. The GA-Enhanced 8D chaotic system encryption algorithm successfully addresses the security challenges in smart grid data transmission.

Topology detection of distribution grid using wavelet-based Graph Attention Network

2025-06-04

Hengfeng Zhang , Wei Sun , S Y Zhu +3 more | Electric Power Systems Research

A Fault Diagnosis Method for UHV DC Control and Protection Based on Dynamic Time Window

2025-06-01

Ninglang Zheng , Wujie Chao , Lei Gan +2 more | Journal of Physics Conference Series

Abstract In this paper, a fault diagnosis method based on a dynamic time window is proposed to enhance the accuracy and efficiency of fault diagnosis in a DC control system … Abstract In this paper, a fault diagnosis method based on a dynamic time window is proposed to enhance the accuracy and efficiency of fault diagnosis in a DC control system protection mechanism. In the DC transmission system, the normal operation of the control and protection device is very important to ensure the stability and security of the power grid. However, traditional fault diagnosis methods frequently encounter difficulties in promptly and precisely pinpointing faults, especially when dealing with complex and variable fault information. The core of the proposed method is to use the time window technology to efficiently process the fault information in the DC control and protection system.Specifically, an initial time window is established to capture and filter the event list pertaining to the fault. Subsequently, a multi-dimensional and multi-level analysis of this event list is conducted, enabling the precise identification of the fault’s type, location, and cause, which provides strong support for subsequent fault handling and system recovery. The experimental results show that the fault diagnosis method based on dynamic time window has high accuracy and practicability, significantly enhancing both the efficiency and effectiveness of fault diagnosis.

Power Stability Management for Renewable Energy Resources using Big Data Analysis

2025-06-01

Ming Shi , Yan Deng , Jince Wang +2 more | Scalable Computing Practice and Experience

The power sector plays a major role in the world’s economic growth. However, the high energy demand and depleting energy resources make the power sector operates in a stressed condition. … The power sector plays a major role in the world’s economic growth. However, the high energy demand and depleting energy resources make the power sector operates in a stressed condition. In recent times, the power sectors are facing various challenges like power instability, high consumption rate, etc. In this article, a Honey Pot-based Recurrent Neural Network (HPbRNN) Big Data Analysis model was presented to predict the power instability in the grid system. Power stability determination is important in a grid system to maintain stable power flow and system operation. In the developed scheme, a huge amount of data is collected from the grid network to predict power stability. The application of big data in the grid network enables the process of this huge collected dataset by analyzing the dataset features. Initially, to make the prediction accurate and easy the dataset is splitted and pre-processed. Then the input and output attributes are tracked and extracted to predict the grid stability. In addition, to achieve the finest results the honey pot fitness solution is integrated into the optimization layer of the proposed model. Furthermore, the outcomes of the developed model are validated and the performance enhancement score is determined from the comparative analysis.

Conditional denoising diffusion probabilistic model based ante-hoc explainable scenario generation for power systems dispatch

2025-06-01

Wenhao Ma , Guofeng He , Liang Che | Energy

Fault handling technology of new energy photovoltaic access in low-voltage power grid

2025-06-01

Zhihua Xu , Gang Ma , Song Hu +2 more | Journal of Physics Conference Series

Abstract Due to long lines, insufficient redundancy, and low automation levels of distribution networks in remote areas in China, it is difficult to guarantee the reliability of power supply and … Abstract Due to long lines, insufficient redundancy, and low automation levels of distribution networks in remote areas in China, it is difficult to guarantee the reliability of power supply and power quality, and the vulnerability of power grids has increased after new energy photovoltaic access. These regional power grids have problems such as weak network topology, poor distribution line conditions, and poor communication conditions, which make it difficult for existing technologies to meet the needs of fault handling. This paper researches the operation fault of low-voltage power grids in remote areas, analyzes the characteristics of short circuit faults and small current grounding faults after the new energy photovoltaic is connected, and finds that its impact is closely related to the power supply type, access location, grounding mode and other factors, which provides new ideas and methods for solving low-voltage power grid fault in remote area.

Research on Multi-source Data Fusion Methods in Distribution Networks

2025-06-01

Xiaoyan Guo , Youqin Wang , Tiange Wang +2 more | Journal of Physics Conference Series

Abstract Multi-source data represents a complex data type. This article proposes a method for the comprehensive utilization of multi-source data suitable for distribution network line loss calculation. Firstly, to facilitate … Abstract Multi-source data represents a complex data type. This article proposes a method for the comprehensive utilization of multi-source data suitable for distribution network line loss calculation. Firstly, to facilitate data fusion, multi-source measurement data is converted. Secondly, to ensure consistency in measurement time snapshots, a specific measurement time from a Distribution Phasor Measurement Unit (D-PMU) is selected as the benchmark. SCADA data undergoes time registration and data interpolation, while smart meter data is time-aligned using a combination of “measured values + predicted values.” Subsequently, the time-series data is filtered to obtain more accurate distribution network data, and then multi-source data fusion is achieved based on the Dempster-Shafer (D-S) evidence theory. By conducting power flow state analysis based on the high-quality fused data, distribution network data can be utilized in a more refined manner, addressing the shortcomings of traditional methods. Finally, a 10kV distribution network is selected as a case study to obtain the power flow state using the multi-source data fusion method, upon which the distribution network line loss is calculated. The results demonstrate that the proposed method can effectively accomplish the comprehensive utilization of multi-source data and improve the accuracy of distribution network data applications.

Research on Low-Energy Consumption Strategies for Substation Buildings

2025-06-01

Weihan Zou , Xi Luo , Zhijia Huang +1 more | Journal of Physics Conference Series

Abstract The significance of energy conservation in the design of substation buildings is escalating. This study examines energy-saving design strategies for substation buildings in summer hot winter warm climates. This … Abstract The significance of energy conservation in the design of substation buildings is escalating. This study examines energy-saving design strategies for substation buildings in summer hot winter warm climates. This research utilizes a 500kV substation located in Guangzhou, China, as a case study to dissect its energy consumption patterns and inform strategies for energy-efficient operations. The assessment of cold-load demand, energy-saving potential, and energy use characteristics incorporates enclosure structure, fresh air load, solar photovoltaic (PV) generation, and lighting electricity consumption. The methodology combines on-site testing with simulation analysis. The study reveals significant energy reduction potentials: (1) Optimizing enclosure thermal performance can decrease summer cold loads by 25-30%; (2) Fresh air load reduction of approximately 28% is achievable through zone-specific volume control; (3) Lighting electricity consumption can be slashed by 72% by enhancing natural lighting utilization; (4) Solar PV electricity generation can elevate the building’s integrated energy savings to 43.63 %, demonstrating substantial energy conservation. The research of this project can provide energy-saving design reference for the low-energy transformation of substations in summer hot winter warm areas.

Power supplying unit Delineation Method Using an Equal-Angle Centerline Clustering Algorithm

2025-06-01

Zhi Guan , Hejun Yang , Jingjing Yu +2 more | Journal of Physics Conference Series

Abstract Aiming at the existing medium-voltage (MV) distribution grid power supplying unit delineation without considering load complementarity, and the delineation scheme cannot reflect the optimization. This paper proposes a power … Abstract Aiming at the existing medium-voltage (MV) distribution grid power supplying unit delineation without considering load complementarity, and the delineation scheme cannot reflect the optimization. This paper proposes a power supplying unit delineation method using an equal-angle centerline clustering algorithm. Firstly, this paper proposes a power supplying unit delineation method based on a centerline clustering algorithm. Secondly, the centerline clustering algorithm is improved based on Particle Swarm Optimization (PSO) to seek the optimal result of block delineation. Then, the feeder blocks are combined into power supplying units by the maximum weight matching method. Finally, a power supplying area with the integration of three substations is used to verify the rationality and effectiveness of the proposed method.

The Study on Effective Capacity Evaluation Methods for Variable Energy Resources to Secure Resource Adequacy in the Korean Power System

2025-05-31

Hyobin Oh , Hyeong-Seok Yun , Hyo-Jeong Yoon +3 more | The Transactions of The Korean Institute of Electrical Engineers

Research Trends on Probabilistic Power Flow Calculation

2025-05-31

Takuto Ohsawa | IEEJ Transactions on Power and Energy

Automatic Fault Detection and Isolation System in Distribution System

2025-05-29

Prof. Pandurang M. Pujari | International Journal for Research in Applied Science and Engineering Technology

Abstract: Our project focuses on developing a cutting-edge, internet-based fault detection system for electrical distribution networks, aiming to address the critical need for rapid and accurate fault identification. Given the … Abstract: Our project focuses on developing a cutting-edge, internet-based fault detection system for electrical distribution networks, aiming to address the critical need for rapid and accurate fault identification. Given the indispensable role of electricity in powering industries and daily life, particularly in urban areas, any disruption in the distribution system can have significant economic and operational repercussions. Our solution integrates advanced sensor technology with real-time data analysis and internet connectivity to swiftly detect and precisely locate faults within the distribution network. This innovative approach not only enhances the speed of fault detection but also minimizes downtime and expedites the restoration of power supply, thereby ensuring a more reliable and efficient electricity distribution system. By leveraging smart technology to streamline fault management, our project contributes to maintaining uninterrupted power flow and supporting economic stability and everyday convenience.

Correction: Day-ahead photovoltaic power forecasting with multi-source temporal-feature convolutional networks

2025-05-27

Zongguang Ouyang , Zhaohui Li , Xiangdong Chen

Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions

2025-05-27

Yuxiang Guo , Qiang Han , Tan Li +3 more

The rapid expansion of global photovoltaic (PV) capacity has imposed higher demands on forecast accuracy and timeliness in power dispatching. However, traditional PV power forecasting models designed for distributed PV … The rapid expansion of global photovoltaic (PV) capacity has imposed higher demands on forecast accuracy and timeliness in power dispatching. However, traditional PV power forecasting models designed for distributed PV power stations often struggle with accuracy due to unpredictable meteorological variations, data noise, non-stationary signals, and human-induced data collection errors. To effectively mitigate these limitations, this work proposes a dual-stage feature extraction method based on Variational Mode Decomposition (VMD) and Principal Component Analysis (PCA), enhancing multi-scale modeling and noise reduction capabilities. Additionally, the Whale Optimization Algorithm is adopted to efficiently optimize the hyperparameters of iTransformer for the framework, improving parameter adaptability and convergence efficiency. Based on VMD-PCA refined feature extraction, the iTransformer is then employed to perform continuous active power prediction across time steps, leveraging its strength in modeling long-range temporal dependencies under complex meteorological conditions. Experimental results demonstrate that the proposed model exhibits superior robustness across multiple evaluation metrics, including coefficient of determination, mean square error, mean absolute error, and root mean square error, with comparatively low latency. This research provides valuable model support for reliable PV system dispatch and its application in smart grids.

The development of an intelligent comprehensive detection instrument for circuit breakers in power systems and its key technologies

2025-05-27

Weimin Guan , Han Hu , Chao Sun +1 more

Phasor measurement unit optimization in smart grids using artificial neural network

2025-05-26

Ashpana Shiralkar , Suchita Ingle , Haripriya Kulkarni +2 more

The wide area measurements systems (WAMS) play a vital role in the operation of smart grids. The phasor measurement units (PMU) or synchrophasors are one of the principle components under … The wide area measurements systems (WAMS) play a vital role in the operation of smart grids. The phasor measurement units (PMU) or synchrophasors are one of the principle components under WAMS. PMU in a smart grid converts power system signals into phasor from voltage and current which enhances the observability of the power system. A variety of operations is performed by the PMUs such as adaptive relaying, instability prediction, state estimation, improved control, fault and disturbance recording, transmission and generation modeling verification, wide area protection and detection of fault location. The PMUs can improve the performance of grid operations and monitoring. Thus, PMU optimization is very necessary to achieve the desired power system observability. The performance of the PMUs can be optimized using artificial intelligence (AI) technologies. The novice method of monitoring maximum power transfer using PMUs equipped with artificial neural networks has been discussed in this paper. In this paper, a two-bus system model is developed that can be generalized to multiple bus systems. The proposed method is novel, simple, feasible, and cost effective for smart grids.

A Study of IOT Based Real-Time Monitoring Multiple Solar Power Remote Monitoring

2025-05-24

Dipali E. Bhatkar

ABSTRACT This paper presents the design and implementation of an IoT-based real-time remote monitoring system for multiple solar power sources using the ESP32 microcontroller. The system is developed to monitor … ABSTRACT This paper presents the design and implementation of an IoT-based real-time remote monitoring system for multiple solar power sources using the ESP32 microcontroller. The system is developed to monitor and compare the performance of two solar panels-one monocrystalline and one polycrystalline-under similar environmental conditions. Voltage and current sensors are integrated with each panel to accurately measure electrical output. The ESP32 collects data from the sensors and transmits it via Wi-Fi to the ThingSpeak cloud platform, where it is visualized and analyzed in real time. This setup enables users to remotely track and evaluate the efficiency, stability, and behavior of both solar panel types. The system offers a scalable and cost-effective solution for solar energy monitoring, supporting further research and practical applications in renewable energy optimization and management. Keywords: IoT, ESP32, Solar Power Monitoring, Monocrystalline Solar Panel, Polycrystalline Solar Panel, Voltage Sensor, Current Sensor.

Application of Handheld Buried Pipeline Detection Method in Non-Metallic Pipelines of Shaanbei Gas Field

2025-05-23

Dong Xu , Qiang Li , Wu Jia +2 more

Non-metallic pipelines have partially replaced metal pipelines due to their corrosion resistance, anti-scaling, and long service life, effectively alleviating pipeline corrosion problems caused by surface system corrosion in oil fields. … Non-metallic pipelines have partially replaced metal pipelines due to their corrosion resistance, anti-scaling, and long service life, effectively alleviating pipeline corrosion problems caused by surface system corrosion in oil fields. However, due to the insulation properties of non-metallic pipelines, the detection technology for existing non-metallic pipelines is not mature, and most of the non-metallic pipelines in oil fields are in an invisible and hard to find state. They are easily damaged during construction, which brings great inconvenience to the operation and management of oil field pipelines. To solve the safety accidents and geological hazards caused by the unclear distribution of underground pipelines, this paper conducts corresponding research on the detection technology of buried non-metallic pipelines, analyzes the adaptability of existing non-metallic pipeline detection methods to non-metallic pipelines in oil fields, and proposes a new non excavation pipeline detection method - handheld buried pipeline detection method, which is applied and tested in the Shaanbei gas field. The test results have demonstrated the reliability of the handheld buried pipeline detection method and provided its applicable range.

Real-time monitoring and early warning system for hydropower safety based on the internet of things

2025-05-22

Jian Xu , Junzhong Chen

With the development of Internet of Things (IoT) technology, the current system has the problem of data processing delay, making it challenging to capture complex long-term dependencies and identify potential … With the development of Internet of Things (IoT) technology, the current system has the problem of data processing delay, making it challenging to capture complex long-term dependencies and identify potential risks and failures in advance. This paper introduces the LSTM (Long Short-Term Memory) model in combination with the IoT, aiming to process time series data effectively, dynamically adjust warning thresholds, and predict potential risks. The real-time monitoring and early warning system for hydropower safety based on the IoT combines NB-IoT (Narrowband Internet of Things) technology and the LSTM model to achieve key parameter monitoring, data transmission, anomaly detection, and dynamic threshold adjustment. Sensors are deployed to cover important areas of the hydropower station, and LSTM captures long-term dependencies and predicts potential risks. After preprocessing, the data is transmitted through a lightweight protocol to ensure safety and accuracy. The early warning system integrates multiple modules, supports dynamic alarms and continuous optimization, and improves the safety and efficiency of hydropower station operations. Experimental results show that the LSTM model is superior to the comparison model in multiple indicators. In water level monitoring, the LSTM accuracy rate is as high as 98.50%, and the F1 score is 96.14%, significantly better than linear regression and decision trees. In gas concentration monitoring, the LSTM delay is only 70.8 ms, and the real-time rate is 99%. In the system stability assessment, the LSTM error rate was 1.8% under pressure monitoring, and the normal operation stability reached 99.6%, showing strong robustness and rapid recovery capabilities, suitable for scenarios with high real-time and high stability requirements. The real-time monitoring and early warning system for hydropower safety based on the IoT, combined with NB-IoT technology and LSTM model, can efficiently process complex time series data, adapt to high-load environments, and significantly improve the performance and reliability of the hydropower safety monitoring and early warning system.

Analysis of Precision Regulation Pathways for Thermal Substation Supply–Demand Balance

2025-05-22

Junwei Yin , Pengpeng Zhao , Jinda Wang

Under the dual imperatives of air pollution control and energy conservation, this study proposes an enhanced optimization framework for combined heat and power (CHP) district heating systems based on bypass … Under the dual imperatives of air pollution control and energy conservation, this study proposes an enhanced optimization framework for combined heat and power (CHP) district heating systems based on bypass thermal storage (BTS). In contrast to conventional centralized tank-based approaches, this method leverages the dynamic hydraulic characteristics of secondary network bypass pipelines to achieve direct sensible heat storage in circulating water, significantly improving system flexibility and energy efficiency. The core innovation lies in addressing the critical yet under-explored issue of control valve dynamic response, which profoundly impacts system operational stability and economic performance. A quality regulation strategy is systematically implemented to stabilize circulation flow rates through temperature modulation by establishing a supply–demand equilibrium model under bypass conditions. To overcome the limitations of traditional feedback control in handling hydraulic transients and heat transfer dynamics in the plate heat exchanger, a Model Predictive Control (MPC) framework is developed, integrating a data-driven valve impedance-opening degree correlation model. This model is rigorously validated against four flow characteristics (linear, equal percentage, quick-opening, and parabolic) and critical impedance parameters (maximum/minimum controllable impedance). This study provides theoretical foundations and technical guidance for optimizing secondary network heating systems, enhancing overall system performance and stability, and promoting energy-efficient development in the heating sector.

Pipeline intrusion events recognition method based on AWTFE image enhancement for DAS

2025-05-22

XU Jing-cai , Lang Xie , Shibo Han +2 more

Safety Assessment of Loop Closing in Active Distribution Networks Based on Probabilistic Power Flow

2025-05-22

Wenchao Cai , Yuan Gao , Xiping Zhang +3 more

To investigate the security issues of loop-closing operations in medium–low-voltage distribution networks under the influence of stochastic fluctuations from distributed generators (DGs) and loads, probabilistic power flow is introduced for … To investigate the security issues of loop-closing operations in medium–low-voltage distribution networks under the influence of stochastic fluctuations from distributed generators (DGs) and loads, probabilistic power flow is introduced for analyzing loop-closing currents in active distribution networks. A novel method combining Latin Hypercube Sampling (LHS) and the Gram–Charlier (GC) series, termed the LHS-GC method, is proposed to calculate the probability distribution of loop-closing currents. By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. Based on a linearized formulation of loop-closing current equations, the cumulants of loop-closing currents are calculated, ultimately reconstructing the probability distribution function of loop-closing currents in active distribution networks. Subsequently, a security assessment framework for loop-closing operations is established using the probability distribution of loop-closing currents. This framework provides a quantitative evaluation from two dimensions: preliminary loop-closing success rate and the severity of current limit violations, offering data-driven decision support for loop-closing operations. Taking the IEEE 34-node distribution network as an example for feeder loop-closing current assessment, the proposed LHS-GC method achieves results with less than 4% deviation from simulation values in terms of cumulative probability distribution of loop-closing currents and safety assessment metrics. Under a sampling scale of 500 points, the computational time is 0.76 s, demonstrating its efficiency and reliability. These outcomes provide actionable references for decision-making support in loop-closing operations of active distribution networks.

Decision Making Model for Frozen Distribution using Cross-dock

2025-05-20

Minh Nhat Vu , Hoai-Phuc Tran , Huu‐Thanh Nguyen +1 more

Power System Operation Stability Assessment Method Based on Deep Convolutional Neural Network

2025-05-19

Jinman Luo , Yuqing Li , Qile Wang +1 more

INTRODUCTION: For the assessment of power system stability, a power system assessment method based on a deep convolutional neural network is studied. OBJECTIVES: Through the improvement of the integrated convolutional … INTRODUCTION: For the assessment of power system stability, a power system assessment method based on a deep convolutional neural network is studied. OBJECTIVES: Through the improvement of the integrated convolutional neural network (CNN) network model, the impact of insufficient transient stability assessment caused by sample misjudgment and sample omission is effectively reduced. METHODS: We adopt the hierarchical real-time prediction model to evaluate the stability and instability of the determined stable samples and unstable samples, thereby improving the timeliness and accuracy of transient evaluation. RESULTS: Through experimental comparison, the integrated CNN network model in this study has obvious advantages in accuracy compared with the single CNN network. Compared with other algorithm reference models, this model has a higher evaluation accuracy of 98.39%, far exceeding other comparison models. CONCLUSION: By further evaluating the model’s accuracy, it is proved that the model can provide an effective reference for the follow-up power system stability prevention and has important application value.

Winding Fault Detection in Power Transformers Based on Support Vector Machine and Discrete Wavelet Transform Approach

2025-05-14

Bonginkosi Thango

Transformer winding faults (TWFs) can lead to insulation breakdown, internal short circuits, and catastrophic transformer failure. Due to their low current magnitude—particularly at early stages such as inter-turn short circuits, … Transformer winding faults (TWFs) can lead to insulation breakdown, internal short circuits, and catastrophic transformer failure. Due to their low current magnitude—particularly at early stages such as inter-turn short circuits, axial or radial displacement, or winding looseness—TWFs often induce minimal impedance changes and generate fault currents that remain within normal operating thresholds. As a result, conventional protection schemes like overcurrent relays, which are tuned for high-magnitude faults, fail to detect such internal anomalies. Moreover, frequency response deviations caused by TWFs often resemble those introduced by routine phenomena such as tap changer operations, load variation, or core saturation, making accurate diagnosis difficult using traditional FRA interpretation techniques. This paper presents a novel diagnostic framework combining Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM) classification to improve the detection of TWFs. The proposed system employs region-based statistical deviation labeling to enhance interpretability across five well-defined frequency bands. It is validated on five real FRA datasets obtained from operating transformers in Gauteng Province, South Africa, covering a range of MVA ratings and configurations, thereby confirming model transferability. The system supports post-processing but is lightweight enough for near real-time diagnostic use, with average execution time under 12 s per case on standard hardware. A custom graphical user interface (GUI), developed in MATLAB R2022a, automates the diagnostic workflow—including region identification, wavelet-based decomposition visualization, and PDF report generation. The complete framework is released as an open-access toolbox for transformer condition monitoring and predictive maintenance.

Research on Missing Data Estimation Method for UPFC Submodules Based on Bayesian Multiple Imputation and Support Vector Machines

2025-05-14

Xiaoming Yu , Jun Wang , Ke Zhang +6 more

With the increasing complexity of power systems, the monitoring data of UPFC submodules suffers from high missing rates due to sensor failures and environmental interference, significantly limiting equipment condition assessment … With the increasing complexity of power systems, the monitoring data of UPFC submodules suffers from high missing rates due to sensor failures and environmental interference, significantly limiting equipment condition assessment and fault warning capabilities. To overcome the computational complexity, poor real-time performance, and limited generalization of existing methods like GRU-GAN and SOM-LSTM, this study proposes a hybrid framework combining Bayesian multiple imputation with a Support Vector Machine (SVM) for data repair. The framework first employs an adaptive Kalman filter to denoise raw data and remove outliers, followed by Bayesian multiple imputation that constructs posterior distributions using normal linear correlations between historical and operational data, generating optimized imputed values through arithmetic averaging. A kernel-based SVM with RBF and soft margin optimization is then applied for nonlinear calibration to enhance robustness and consistency in high-dimensional scenarios. Experimental validation focusing on capacitor voltage, current, and temperature parameters of UPFC submodules under a 50% missing data scenario demonstrates that the proposed method achieves an 18.7% average error reduction and approximately 30% computational efficiency improvement compared to single imputation and traditional multiple imputation approaches, significantly outperforming neural network models. This study confirms the effectiveness of integrating Bayesian statistics with machine learning for power data restoration, providing a high-precision and low-complexity solution for equipment condition monitoring in complex operational environments. Future research will explore dynamic weight optimization and extend the framework to multi-source heterogeneous data applications.

A quantitative assessment method for regulating capacity sufficiency under medium- and long-term supply and demand risk scenarios of provincial power grids with high proportion of new energy sources driven by multilevel temporal and spatial combinatorial optimization algorithms

2025-05-12

Linux Dual Kernel System Based on Domestic Realtime Kernel

2025-05-09

Zaiping Nie , Shiyu Gan | 2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)

Methodology for incisive foraging of high-risk junctions and elimination of injected false data in smart grid

2025-05-09

Pinki Ghosh , Subrata Biswas , P. Purkait

The present work represents a method for identification of the vulnerable nodes in smart grid as well as assessment of the performance of voltage stability indicator technique with the help … The present work represents a method for identification of the vulnerable nodes in smart grid as well as assessment of the performance of voltage stability indicator technique with the help of weighted least square scheme. in today’s smart grid system, false data injection (FDI) is the major issue to supply uninterruptedly at demand side in advanced metering infrastructure (AMI). The recent blackouts are the consequence of non-identifying FDI as research on FDI is not considered under power system analysis. In our research, vulnerable nodes of a power system network have been identified and a state estimation method was used to eliminate superfluous data for those identified nodes. Voltage stability indicator (VSI) based state estimation have been used successfully to make the smart grid system error free as possible. VSI method has been used first to find the vulnerable nodes of the grid after that the efficient state estimation method i.e. optimal weighted least square (optimal WLS) have been employed to get refined result. Results show that VSI based technique in concurrence with optimal WLS has potential to eliminate undesirable data with sensible level of precision.