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1.INTRODUCTIONIn the steady development of China’s economy, power resources as one of the essential energy in daily life, substation is the basic component to ensure the operation of the power system, only comprehensive operation and maintenance of the substation, in order to ensure the normal operation of the grid and continuous production of electricity, to ensure the normal production and life of urban users. Under the development trend of economic globalization, the design and application of power system have become more and more complicated, and there are more and more factors affecting the stable operation of power system. Moreover, these influencing factors are not uniform and will constantly change with the change of time, which ultimately leads to the difficulty of substation operation and maintenance management. If human factors cause problems in a certain link during the operation of the substation, it will have a great impact on the operation of the whole system. Under normal circumstances, according to the substation operation and maintenance risk differences are divided into two types, on the one hand refers to the internal risk, most of the reasons are caused by the internal power equipment itself; On the other hand, it refers to external risks, which are safety failures caused by external natural disasters or weather factors. For example, in the long-term operation of the substation, some of the internal power equipment will be aging because of the use of too long problems, if the equipment begins to age, some internal devices will inevitably fail, such as cable broken chain, wire skin off, although these failures are relatively small, but the operation of the power equipment caused great harm; In the context of increasing electricity consumption in urban production and living, power enterprises will appropriately increase the number of substations in order to meet people’s electricity demand, which leads to an increasing number of equipment requiring daily operation and maintenance, but the number of internal staff can not meet this trend. Within the substation, the failure causes of different substation equipment are different, and the scope of the same staff is increasingly wide, which will inevitably affect the work efficiency, improve the difficulty of equipment operation and maintenance, and eventually lead to improper personnel management becoming one of the main factors affecting the safety and stability of the substation. External factors will also cause serious harm to substation equipment, such as internal enterprises, staff and natural organisms, etc. These problems should be effectively controlled according to relevant laws and regulations, and the use of big data technology 24-hour monitoring and management to find problems as soon as possible and effectively deal with them; In addition, the security risks posed by extreme weather and natural disasters are extremely high. When the equipment is in extreme weather, it is easy to have some safety failures because of weather reasons, such as the equipment wire is easy to break in cold weather, and the thunderstorm weather is extremely easy to cause fire, etc. These disasters cannot be predicted and effectively controlled, and will cause unpredictable damage to the operation of the transformer equipment and system. Therefore, on the basis of understanding the application and research status of big data technology, this paper systematically analyzes the substation operation and maintenance management system with big data technology as the core, and identifies effective measures to improve substation operation and maintenance capabilities and reduce power costs, in order to provide technical support for the reform and development of power enterprises in the new era. 2.METHOD2.1System ArchitectureUnder the background of deepening application and design reform of power enterprise information system, the substation operation and maintenance system architecture with big data technology as the core is shown in Figure 1 below: The system module design is shown in Figure 2 below: According to the above analysis, the overall module includes five contents: data collection, data storage, batch analysis and calculation, knowledge base and self-service customer service. From the perspective of system operation, the data acquisition module mainly collects the operation and maintenance data after processing in the specified host server directory. Data storage module will use distributed file system to store and obtain various information; Batch analysis and calculation module is the core content of the system operation. It mainly studies and analyzes different types of substation operation and maintenance data, and understands the clustering relationship and similarity relationship between the data. Input questions when users need to search, understand the classification in the problem processing module, analyze the syntax, semantics, vocabulary, etc., use appropriate data algorithms to detect solutions with high matching degree to the problem, and finally give the user a process. The flow chart of text processing is shown in the following 3; The knowledge base module will store the data information related to substation operation and maintenance. The data base obtained after quantitative similarity analysis includes data dictionary information, system user information, operation log information record table, etc. The self-service customer service module is proposed with web browser page as the core. In the customer service operation and maintenance system, the intelligent analysis technology of big data is applied to maintain and process basic data, and the results of the intelligent analysis platform for customer service operation and maintenance are displayed. The specific process is shown in Figure 4 below: Based on the above analysis, it can be seen that the problem processing module means that after obtaining the questions raised by users, it deeply analyzes the categories, keywords and word segmentation weights of the questions, and then carries out search analysis and logical comparison with the data knowledge base according to the results obtained by the analysis and calculation module, and finally outputs the answers to the questions. In the information retrieval module, the whole operation is divided into two parts: information collection and information filtering. The former is to find the corresponding information in memory or database, while the latter is to filter effectively according to the problem conditions. The substation equipment library is constructed according to the existing data equipment, and Class A maintenance, Class B maintenance, preventive test and secondary equipment decay cycle are designed according to different equipment types. This module consists of two parts: on the one hand, it refers to the professional team entry of equipment maintenance records; on the other hand, it refers to the equipment owner’s follow-up investigation of equipment maintenance. The practice workflow is shown in Figure 5 below: From the perspective of practical application, professional team maintenance in the record of the specific time, the system will automatically update the latest maintenance time, and automatically generate the next maintenance time, it also has the expansion function, users can input processing points and generate processing experience according to demand. At the same time, the system will reverse arrange the equipment of the same substation according to the next maintenance time, and the professional team and the equipment owner can check the working condition of the equipment that is about to expire at any time, and finally find the problem in real-time monitoring and effectively deal with it. The substation operation and maintenance management system with big data as the core studied in this paper has simple structure, rich application functions, clear and concise man-machine presentation interface, faster grass-roots staff to get started, rapid and effective data processing, and provides technical support for the operation and maintenance management of electric power enterprises. On this basis, cost control is carried out, and effective countermeasures for substation management are actively discussed. It can guide the substation of electric power enterprises to develop steadily in the direction of specialization and intelligence. 3.RESULT ANALYSIS3.1Analysis of countermeasures to improve substation operation and maintenance capacityIn order to optimize the operation and maintenance management of the substation and improve the efficiency and quality of practical work, power enterprises should rationally use the telemetry, remote communication, remote control and remote adjustment of the telecontrol system under the role of conventional signals and power protection devices, and switch from manned to unattended based on the intelligent function of technical equipment. At the same time, from a security perspective, video surveillance, fire detectors and anti-theft access control devices are installed near the equipment. Taking the substation of an enterprise as an example, it mainly uses conventional relay protectors without background computers, and conventional relay protectors cannot effectively communicate with the computer system, so it is necessary to carry out technical transformation and replace them with instruments and equipment with crisis memorial protection and communication functions. After setting up a local background computer, The operation data of each distribution interval is transferred to the monitoring computer and transmitted from the local background to the substation background. Operation and maintenance personnel can directly monitor the running data of each distribution interval in the background, and truly realize remote operation and management. From the perspective of practical application, the efficiency and quality of remote control with microcomputer monitoring as the core are significantly higher than manual operation, and the overall operation level meets the needs of technological reform in the new era. According to the analysis of reference data obtained in recent years, the unattended operation rate will be reduced to about 25%, so after the transformation, the staff can directly remote control operation, scientific handling of safety accidents, simplify complex work steps, speed up the transfer of normal load, improve the comprehensive level of power grid management, so that the substation truly realize the integrated management of operation and maintenance. 3.2Analysis of power cost reduction schemeIn the process of social construction and development, the significant rise in labor costs will lead to higher and higher substation operation and maintenance expenditure. Therefore, enterprises can improve their own intelligence level, so that the substation can achieve unattended work needs, reduce unnecessary work links, and control the number of substation operation and maintenance workers. When the equipment is performing fault prevention experiments, outsourcing schemes are adopted and other operation and maintenance teams are temporarily called to handle the problems. It should be noted that although this model can reduce labor costs, it needs to set up a professional operation and maintenance team with a certain number of technical staff. At the same time, with the continuous improvement of the intelligent level of the substation, timely monitoring of the load, the use of background data information to optimize the cost of electricity, according to the preferential policies and technical equipment methods proposed by the state, to guide the power enterprises to continue to reform and innovation in the direction of energy saving and cost reduction. For example, tracking the substation operating load, system analysis of production efficiency and application technology, forecast and control the load size during the work, in the case of the maximum load rate does not exceed 66.7%, according to the maximum demand approved value of not less than 40% of the policy document requirements, scientifically adjust the billing mode, so that the transformer capacity is adjusted to the maximum. According to the transformer capacity 50MVA accounting, thereby reducing the fixed cost expenditure; With the continuous improvement of the intelligent level of substation, the effective power and reactive load are monitored in time, and the power department needs to charge interest rate electricity when charging electricity. When dealing with the situation of non-compliance, focus on improving power quality and power factor, calculate and analyze the feasibility of cost, and optimize the cost of the enterprise by reducing the monthly continuous deduction expenses of the power department and obtaining monthly continuous incentives. From the perspective of the long-term development of power enterprises, the effective power cost reduction plan for development needs can fundamentally reduce resource consumption and lay a solid foundation for achieving sustainable development goals. 4.CONCLUSIONTo sum up, at present, China’s substation operation and maintenance management is facing an important stage of reform and development, the use of big data technology to propose intelligent operation and maintenance management mode, integration and analysis of human resources in each link, effective control of various costs, deep mining potential data value and technical advantages, according to the relevant departments of our country proposed preferential policies for electricity consumption, Guide the power enterprises to reduce the cost of electricity to the greatest extent, improve their own operation and maintenance capabilities, and ultimately provide rich power resources for urban construction and residents’ lives. 5.5.REFERENCEBo Gao, Di Wu, Zhihao Yang, et al,
“Research on equipment condition maintenance technology of Power substation based on Big Data [J],”
Microcomputer Applications,
(004), 038
(2022). Google Scholar
Linwei LI, Zhe Zhao, Bangcheng Liu,
“Effect evaluation and optimization path of China’s electric power system reform under the background of “decentralization service” : Based on power panel data analysis of 1486 household electricity enterprises in Chongqing [J],”
Review of Public Administration, 14
(5), 21
(2021). Google Scholar
Zelong Zhang, Dongni Wei, Mengyuan Tang, et al,
“Research on Optimization Strategy of Power load Forecasting and cost Perception based on Improved LSTM [J],”
Electronic Design Engineering, 31
(21), 132
–136
(2023). Google Scholar
Qiwei Du, Chao Zhang, Hongfu Han,
“Research on key technologies of intelligent substation operation and maintenance based on interval subgraph [J],”
Power Grid and Clean Energy, 39
(7), 67
–72
(2023). Google Scholar
Junkai Ge, Zhen Li, Xiufeng Zhang, et al,
“Spark implementation of intelligent operation and Maintenance System Intrusion Detection based on Mutual Information Method [J],”
Automation Instrumentation, 43
(3), 4
(2022). Google Scholar
Shanshan Li, Chao Jing,
“Research on Power cost optimization Method of multi-tenant data Center based on improved Polar Bear algorithm [J],”
Applied Research of Computer, 40
(3), 7
(2023). Google Scholar
Bo Su, Peng Cheng, Xiaohui Ding, et al,
“Research and Application of Substation intelligent Alarm signal Eventization based on Big Data [J],”
Microcomputer Applications,
(005), 038
(2022). Google Scholar
Yaqi Cao, Bo Zhao, Lijie Wang, et al,
“Research on operation efficiency improvement strategy of light storage power station based on genetic ant colony [J],”
Electric Power of China, 55
(2), 10
(2022). Google Scholar
Xiangye Fan,
“Research on state repair of intelligent operation and Maintenance System of Harmonious Locomotive Running Unit [J],”
Ergonomics, 2022
(003), 028 Google Scholar
Haiyong Jin, Qile Wu and Tengze Liu,
“Power operation and maintenance fault diagnosis equipment Method based on fuzzy control and big data algorithm model [J],”
Computer Measurement and Control, 30
(11), 71
–76
(2022). Google Scholar
Gang Li, Yue Wang, Guozheng Zhang,
“Construction method and application of Port Intelligent operation and Maintenance System based on global awareness [J],”
Microcomputer Applications,
(011), 037
(2021). Google Scholar
Yiliang Wang, Weiqiang Qi, Yaqiong Guo, et al,
“Research on multi-dimensional data aggregation scheme for smart grid Communication security based on Elliptic curve [J],”
Manufacturing Automation, 45
(2), 114
–119
(2023). Google Scholar
Kai Wang, Hao Xu, Mengyan Zhang, et al,
“Application and research of digital twin technology in the field of waterway transportation [J],”
Chinese Ship Research, 18
(5), 1
–10
(2023). Google Scholar
Yingting Xie,
“Application of Five-ring history management System in Shanghai Rail Transit operation equipment operation and maintenance [J],”
Urban Rail Transit Research, 26
(3), 232
–237
(2023). Google Scholar
Changjun CAI, Xijun Chen, Yougen Peng, et al,
“Application of Suiteng Operating System Cloud Platform in Guangzhou Metro Vehicle active operation and maintenance project [J],”
Urban Rail Transit Research,
(010), 026
(2023). Google Scholar
|
