Construction Of Smart Grid Research Articles

Research on User Oriented Benefit Evaluation Model of Power Demand Side Management Based on Computer Software

Power demand side management (hereinafter referred to as DSM) is an important part of smart grid construction in China, which can realize scientific energy saving and power saving. Through DSM, the power grid can dispatch power based on user demand, which can support the sustainable development of national power industry. At the same time, through DSM, the power grid can transmit power intelligently, which is of great significance to the energy conservation and emission reduction of the society. With the construction of smart grid, power DSM has formed an important management system, which can better expand the intelligent and scientific power grid. Through the continuous transformation to energy-saving management system, the traditional load management is no longer suitable for the needs of the society, which requires us to comprehensively review the development of smart grid. Through the DSM system, we can expand the load analysis management means in smart grid, which will better tap the demand side resource potential. Through the effective evaluation system, we can provide more comprehensive, scientific and accurate decision-making basis. Firstly, this paper presents the current load forecasting methods. Then, a model is proposed. Finally, some suggestions are put forward.

Research on grid load model based on SPACK architecture of power big data

Big data service is the key to the construction of smart grid, and the method of analyzing electricity consumption behavior based on improved AP clustering and the method of forecasting electricity load based on random forest is proposed. To address the problem of high complexity of AP clustering analysis, the entropy weight method is used to establish the index weights and improve the similarity calculation method to realize the fast and accurate analysis of customers’ electricity consumption behavior. For the problem of power load prediction, the fuzzy C-means method is used to construct the index weights. The fuzzy C-means is used to construct the historical similarity daily sample set, and the random forest is used to predict the electric load. The SPACK multi-level data processing framework is proposed to meet the needs of parallel processing speed for large amounts of data. The simulation results verify the effectiveness of the method proposed in this article and the important guiding price for the Power grid.

Design and Improvement of Transmission Line Online Monitoring Communication Network

Absrtact: transmission line is an important part of smart grid construction, which has many factors, such as wide distribution, long distance, complex working environment, difficult maintenance and easy to be damaged by natural external forces, etc. Among them, the construction of transmission line online monitoring network plays an important role in ensuring the stability and safe operation of online monitoring technology. In this paper, through the analysis of the transmission line and on-line monitoring transmission data demand and the existing problems of the current communication network, the communication network and data transmission system for transmission line monitoring is designed, which provides some reference for the construction of stable operation of the transmission line on-line monitoring network.

Being “smart” differently: Implications of profiling the worldwide smart grids based on a two‐dimensional smartness framework

AbstractAs more than 10 years have passed since different countries started to build smart grids (SGs), a holistic review of the relative “smartness” of popular SGs may be useful to provide implications for other countries as they plan their own SG roadmaps. This study established a two‐dimensional smartness framework, including functional and technical dimensions, to describe and study the SGs’ smartness comprehensively. Scientific research was used as a reliable source to construct SG profiles for North America, Europe and China, to understand the diversity of SG potential, and the SG projects implemented in these regions were used to further explore its’ smartness. The research results revealed the following SG attributes: (1) Even if the functions performed by all SGs are not exactly the same, SGs in both North America and Europe are distinguished by their functional smartness, meaning they optimize their support for smart electricity usage; (2) China's SG contains less functional smartness than do those of North America and Europe, whereas more technical smartness related to the “energy internet” transition is highlighted; (3) since the SG transition involves both technical innovations and social reforms, although the SG in North America and Europe is superior to China's in terms of functional capabilities, when considering social acceptance, China's SG may actually grow more rapidly in the future. Finally, we analyzed the challenges and future directions in the construction of SGs, the implications for other regions in developing their own SG strategies were also discussed.

Evaluation of Low-Carbon Benefits of Smart Grid Based on Random Forest Algorithm

The eventual exhaustion of non-renewable fossil energy and the damage to the environment during its mining, processing, and consumption process have caused countries around the world to pay attention to how to improve energy efficiency, how to better develop clean energy, and how to optimize the energy structure. Electric energy is an indispensable secondary energy source of both industrial development and home life. How to convert clean energy into electric energy and improve the efficiency of electric energy used provides new ideas about solving energy shortages and environmental pressures. Smart grid is the application of advanced communication and information technology to all business links involved in the power grid. It is of great significance of the realization of information, automation and interaction of the power grid. It has become the development trend of the modern power grid. It can be seen that the construction of smart grids is an important way for countries around the world to alleviate the pressure on energy and environmental protection. This paper summarizes the current research status of smart grids at home and abroad, and combines the characteristics of smart grids with the problems existing on the research on low-carbon benefits of smart grids at home and abroad, and constructs a comprehensive evaluation index system suitable for low-carbon benefits evaluation of smart grids and low-carbon benefits of smart grids. Evaluate the model, use the analytic hierarchy process to preprocess the data, confirm the weight of each indicator system, and get the evaluation score; divide the processed data into a training set and a test set, and use the random forest algorithm to train the model; The evaluation model is used to evaluate the low-carbon benefits of smart grids. The evaluation results show that the model has high evaluation accuracy and certain practicability. Finally, based on the evaluation results and the status quo of smart grids in my country, corresponding suggestions are put forward to promote the further development of low-carbon smart grids.

Case Study of Power Plants in the Slovak Republic and Construction of Microgrid and Smart Grid

To reduce emissions worldwide, decarbonization has also affected for power engineering and its conventional methods of power generation, distribution, and transmission. This fact affects not only the production of power and supply itself, but also other parts related to it, namely systems for the protection of electricity generation facilities and the location of faults in distribution networks and transmission systems. Is this new technology of renewable energy sources (RES) mastered enough to be able to replace traditional methods of energy generation reliably and safely? If we can answer the previous question, we could proceed to the next phase of putting these technologies into practice, considering the actual state of distribution networks and transmission systems. The aim of the article will be to evaluate the current state of systems and production sources of electricity in the Slovak Republic and to provide a better insight and suggestions for rebuilding current networks on a smart grid. The proposals will also include models of some RES in the Matlab/Simulink software.

Application of 5G Communication Technology in Power Communication and Research on Key Technologies

With the rapid development of power system and the deepening construction of smart grid, 5G communication technology is favored by all walks of life because of its ultra-low delay, ultra-high reliability, deep coverage, extreme capacity and ultra-low power consumption. It has become the key technology to lead scientific and technological innovation and promote the sustainable development of power system, providing a solid guarantee for the realization of human-computer interaction and Internet of Everything. This paper first introduces the network structure, basic principle and core features of 5G communication, and expounds the core slice of 5G communication and its three application scenarios; secondly, the potential demand scenarios of 5G communication in power system are analyzed in depth, that is, high capacity, high bandwidth and low delay business scenarios; finally, the key technologies of 5G communication, such as large-scale MIMO communication technology, ultra-dense heterogeneous network technology, green communication technology and millimeter wave communication technology, are discussed, and the linkage between current communication requirements and communication technologies is studied, which provides theoretical support for the application of 5G communication in power system.

Non-intrusive load monitoring algorithm based on household electricity use habits

The construction of smart grid is an important part of improving the utilization rate of electric energy. As an important way for the construction of smart grid, non-intrusive load decomposition methods have been extensively studied. In this type of method, limited by transmission cost and network bandwidth, low-frequency data has been widely used in practical applications. However, the accuracy of device identification in this case faces challenges. Due to the relatively single characteristics of low-frequency data, it is difficult to express the operating status of complex electrical appliances, resulting in low decomposition performance. In this paper, a non-intrusive load is proposed based on household electrical habits by studying the relationship between household electricity consumption habits and load status decomposition method. The Gaussian mixture model and time information are used to model the probability distribution of the electrical appliance state. This probability distribution is then used as the observation probability distribution of the factor hidden Markov model. In such a way, the BH-FHMM model is proposed. Finally, load decomposition is carried out through the load decomposition process of the FHMM model. In order to verify the performance of the proposed method, an experimental comparison is conducted based on the REDD data set. According to the results, a significant improvement in equipment recognition accuracy is obtained.

Smart grid planning suggestions and strategies under the new electric change plan

New electric change plan is a major event in China’s power grid construction. Based on the basic content of China’s new electric change plan, this article analyzes the existing problems in combination with the current situation of smart grid construction, and proposes corresponding countermeasures for the problems. In general, in order to be able to adapt to the requirements of the new electric change plan, improvements need to be made in terms of management strategies and technical means, so as to fully promote the development of smart grid construction. At the same time, this paper establishes a multi-objective power grid planning mathematical model based on cosine sorting, and uses genetic algorithm to solve the model. Through the analysis of calculation examples and comparison with the results obtained by traditional methods, the validity and rationality of the model are verified, which has certain guiding significance for actual engineering.

Application of Intelligent Sensing in Power Test System

Smart grid is the development trend of the power industry under the new situation. As an important part of smart grid, smart power consumption directly faces the society and power users, and plays a very important role in the construction of smart grid. With the development of intelligent power construction, the traditional power service can not meet the needs of users to participate in demand side management and interact with the power grid in time. Therefore, the construction of a new intelligent sensing power measurement system to improve the quality and level of intelligent power service has become the focus of current power industry research. Firstly, according to the requirements analysis and design principles of the intelligent sensing power detection system, this paper proposes the function analysis and three-tier architecture design of the intelligent sensing power detection system. The intelligent sensing power detection system is logically divided into business application layer, network communication layer and sensing device layer. Externally, it realizes data integration and interaction with power consumption information collection system, marketing business management system and other intelligent power consumption information systems. Internally, it realizes interconnection with user side perception interactive terminal and perception unit, and realizes data acquisition, information transmission and control functions of power consumption terminal equipment. This paper presents a method of applying intelligent sensing technology to data editing environment of power simulation software, and realizes online error detection of simulation original data, automatic completion of keywords, automatic prompt of data card and intelligent help of data domain. The power simulation data editing software with intelligent sensing function developed in this paper is suitable for primary and advanced users, which can improve work efficiency and reduce error rate. The configurable rule management method applied in the implementation of intelligent sensing technology extends the application of data editor to the developers of models and algorithms, and provides a simple way for the timely upgrade and release of new models and algorithms.

Application of Power Engineering Technology in Smart Grid Construction

Application of Power Engineering Technology in Smart Grid Construction

Privacy Protection of the Smart Grid System Based on Blockchain

With the development of new technologies for smart grid construction, the smart grid is gradually developing. Smart grid construction is an important field of next generation information technology, and its value and significance have been widely recognized. Smart grid construction not only provides development opportunities, but also brings great challenges. Security and privacy have become serious problems in the development of smart grid. Based on this, this paper discusses the system structure of the block chain, and puts forward the security diagnosis scheme of the smart grid according to the existing problems in the smart grid. Based on the theoretical basis of smart grid big data technology, this paper combines the grid data encryption process with the privacy protection process under the premise of protecting privacy and security, and develops the latest network security protocol. Then use block chain distributed storage to reduce the connection protection process in privacy, and use multi-level encryption. The experimental results show that the technology can improve the rate of sensitive data hiding and has good anti-cracking ability, which provides a theoretical reference for the construction of enterprise power grid.

Resource Scheduling Algorithm for Power Wireless Service

Based on the application of LTE technology in smart grid construction, this paper studies the technical background and demand of LTE technology and carrier aggregation technology in smart grid communication network construction, and analyzes the technical principle and technical background of LTE and carrier aggregation technology used in smart grid. Aiming at the problem of insufficient spectrum resources in smart grid construction, this paper focuses on the combination of carrier allocation and wireless resource allocation faced by carrier aggregation technology in smart grid environment. Carrier aggregation technology is used to improve spectrum utilization and speed up transmission speed. This paper studies a joint resource scheduling algorithm based on service priority, evaluates the service priority by studying the characteristics of wireless private network, and designs different scheduling methods for different services according to the characteristics of wireless resource allocation. The ns-3 simulation results show that the algorithm can provide sufficient resource allocation for high QoS services in the case of traffic congestion, balance the relationship between fairness and throughput, and improve the service transmission performance.

Syncretic Application of IBAS-BP Algorithm for Monitoring Equipment Online in Power System

With the integration and development of sensor technology and control technology, the construction of smart grid is in the ascendant. But existing technology is still insufficient in the field of equipment monitoring. Therefore, it is difficult to accurately determine if SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> breaker or other equipment have faults in its operational mechanisms which can cause false action and thus impact the safety of power grids. In this paper, the IBAS (Improved Beetle Antennae Search) algorithm and the BP neural network are combined and used in the monitoring system for the first time. To improve the beetle search algorithm, a single beetle is improved into a population in the iterative process of algorithm. The measured opening (closing) current data is used to verify the accuracy of different algorithms. The results show that compared with PSO-BP (particle swarm optimization, PSO) model, GA-BP (genetic algorithm, GA) model and BAS-BP model, the IBAS-BP model not only effectively avoids the possibility of local minimums but also has higher prediction accuracy and better robustness. The number of iterations in the IBAS-BP algorithm is only 38, and the average error is only 0.1%. According to this, it is possible to make real-time diagnosis of faulty states in SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> breaker including iron core jams, low operating voltages, poor contact of auxiliary switches, jammed operating mechanisms, and barometer failures in SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> . At the same time, the IBAS-BP algorithm can be applied to wind turbine power prediction and other occasions since model regression determination coefficient R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of the training set is up to 0.9753 and the relative average error is only 0.25%. The results prove that the IBAS-BP algorithm has obvious advantages and fairly good universality. It can be further promoted and applied to power systems to provide reference for optimizing the online monitoring of power equipment.

Analysis of Failure Mechanism of Smart Meter Capacitance

In practical applications, smart meters will fail, and even have batch quality problems. In addition to the sampling inspection of the arrival quality of smart meters, the analysis of the failure mechanism of smart meters has become an important and long-term task. This article mainly analyzes the component capacitance commonly used in smart meters, and analyses the failure of chip multilayer ceramic dielectric capacitors from appearance observation, electrical parameter testing, metallographic slicing, and at the same time from electrolytic appearance observation, electrical parameter testing, X- RAY, SEM and EDS for failure analysis. The results of failure mechanism research not only help to improve the reliability of the domestic energy meter manufacturing level, but also can save energy meter maintenance and transformation costs, and have very important practical significance for the construction of smart grids.

Research on Equipment Information Sensor Information Model System in Power Internet of Things

Power Internet of Things is the application of Internet of Things technology in smart grids. It is an important technical means indispensable for the construction of smart grids. In order to solve the problem of test data imbalance caused by the positioning deviation of the power sensor out of regulation point in the dynamic test system, A method for locating power sensor out-of-regulation points based on improved association mining algorithm (IMA) and FPGA implementation is proposed, and the association mining algorithm is analysed in detail. The paper uses the Monitoring Information Database (MNIB) to realize the organization and storage of power Internet of Things information. Designed a dedicated application layer communication protocol PIOTP, and developed a set of procedures, and finally established a standardized model of information interaction and a unique identification of equipment, so that data can be interacted with a unified information model in the network layer. The thesis completed the information transmission between the monitoring centre and the remote-control terminal (RTU), which verified the feasibility of the scheme.

A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS

Abstract. Smart grid construction puts higher demands on the construction of 3D models of substations. However, duo to the complex and diverse structures of substation facilities, it is still a challenge to extract the fine three-dimensional structure of the substation facilities from the massive laser point clouds. To solve this problem, this paper proposes a method for extracting substation equipment from laser scanning point clouds. Firstly, in order to improve the processing efficiency and reduce the noises, the regular voxel grid sampling method is used to down-sample the input point cloud. Furthermore, the multi-scale morphological filtering algorithm is used to segment the point cloud into ground points and non-ground points. Based on the non-ground point cloud data, the substation region is extracted using plane detection in point clouds. Then, for the filtered substation point cloud data, a three-dimensional polygon prism segmentation algorithm based on point dimension feature is proposed to extract the substation equipment. Finally, the substation LiDAR point cloud data collected by the UAV laser scanning system is used to verify the algorithm, and the qualitative and quantitative comparison analysis between the detected results and the manually extracted results are carried out. The experimental results show that the proposed method can accurately extract the substation equipment structure from the laser point cloud data. The results are consistent with the manually extracted results, which demonstrate the great potential of the proposed method in substation extraction and power system 3D modelling applications.

Market Status and Development Prospects of Virtual Power Plants

With the development of new energies and smart grids, virtual power plants (VPPs) have gradually attracted the academia and industries all over the world. VPPs, which are expected to become the supporting framework of smart grid technologies considering new energy integration, break the boundary between power generation side and power consumption side in traditional power systems and makes full use of advanced technical means such as network communication, intelligent measurement and intelligent decision. The concept and characteristics of VPPs are first introduced as well as the market status and demonstration projects of VPPs in different countries. Then, the development prospects of VPPs are pointed out from the aspects of market scope, smart grid construction, demand side response, power trading curve and market potential. Finally, in terms of the unification of the concept, profit model, market potential, and market mechanism, the corresponding solutions to the urgent challenges of VPPs are proposed.

Substation Equipment Fault Identification Based on Infrared Image Analysis

As a key part of the power system, the substations undertake important work. With the development and construction of smart grids, the status data, image monitoring data, and environmental meteorological data of power systems are gradually being integrated and shared on a unified platform. Traditional models based on theoretical analysis are difficult to deal with multi-dimensional, massive data set information. Under this background, starting from the inherent law of the data itself, the use of machine learning methods combined with the infrared image data of the equipment can achieve intelligent identification and early warning of substation equipment failures. This paper first uses the convolutional neural network to identify the substation equipment in the picture, and then combines the infrared image to perform image registration. Finally, the deep belief network is used to determine whether the device is in wrong condition. The overall substation equipment fault identification is tested on real data, and the experimental results show that the proposed method has high accuracy.

Common fault Analysis and Countermeasures of key Components of intelligent electricity meter

In recent years, with the State Grid Corporation's vigorous construction of smart grids, smart meters have been rapidly promoted in the power system. After several years of online operation, the operating reliability of smart meters has also stabilized. However, in the process of widespread use of smart electric energy meters, the quality problems of clock chips, batteries and other components have also been exposed. This article takes the component failures encountered in the detection and operation of the smart electric energy meter as an example, analyzes the causes of the failures based on the four typical abnormal phenomena, and then conducts the opening detection for the above reasons and determines the nature of the failure based on the test conclusions. Finally, a corresponding fault management platform is established through the collection of electric energy meter fault data, which realizes all-round management and control of the fault handling process and selection of the qualifications of smart meter suppliers, thereby ensuring the quality of components and improving the operation of smart electric meters reliability.