Electrical design problems and improvement countermeasures of transmission lines under the background of big data and artificial intelligence

Abstract

This paper studies the feasibility of intelligent power design mode, and proves that the intelligent power design mode has significant advantages over the traditional mode by using the method of comparative study. Comparative studies are more distinctive in the breadth and depth of content. With the further acceleration of the urbanization process and the popularization of electronic equipment, people’s demand for electricity is gradually increasing. The overall operation of the transmission line is actually highly related to the design mode of the line. The quality of electrical design will be closely related to people’s electricity consumption. The stability of the electrical design is directly linked to the sustainability, and it will also be linked to the reputation of the power design company and the safety of public life. The use of a variety of new technologies in the electrical design process to guide the design scheme and identify design problems as soon as possible is the latest trend in the electrical design of current transmission lines. In the context of the rapid development of data science, the functions of comprehensive sorting and providing suggestions provided by big data technology have become the mainstream choice for solving problems in various industries. At present, big data technology has begun to be associated with the power industry, and big data technology has been applied to transmission lines. Electrical design can also solve various dilemmas that exist in current design. Artificial intelligence technology enables computers to have the ability to think like ordinary people through algorithms and training data. Applying artificial intelligence technology to electrical design of transmission lines can make scheme design more intelligent. In order to analyze the current status of electrical design of transmission lines, this paper conducts a questionnaire survey on professionals and practitioners of electrical design of transmission lines. Through a detailed analysis of the questionnaire data, it is found that the electrical design of current transmission lines mainly includes unreasonable line path arrangement, line support towers unreasonable models and insufficient consideration in safety protection design, and combined with big data and artificial intelligence technology, the intelligent arrangement of line paths, tower-shaped intelligent matching and intelligent safety protection strategies are designed. The respondents of the questionnaire conducted a second survey and found that the efficiency, cost, intelligence, sustainability and safety of the electrical design of transmission lines were improved after combining big data and artificial intelligence technology. The intelligent circuit design scheme constructed by big data and artificial intelligence technology can improve the quality of circuit transportation, solve the problems of unreasonable route layout, unreasonable line support tower type and insufficient consideration of safety protection design. Intelligent circuit design scheme compared to the traditional circuit design scheme in the design efficiency, cost, sustainability is significantly improved.

Keywords

Big data artificial intelligence transmission line electrical design

1. Introduction

Public literature has shown that the development of intelligent power operation design mode is the trend of power design development, but the current power design is still facing many difficulties, so it is meaningful to further study the intelligent power operation mode. This article is obtained through a questionnaire survey conducted by team researchers. The originality and quality of the article are guaranteed.

This paper is mainly to improve the power supply performance of power enterprises. Previous research has pointed out the trend of power enterprises to develop intelligent power supply design mode. On the basis of previous research, this study deepens the intelligent design idea and makes the abstract design concrete. This article is of great significance for improving the stability and efficiency of power supply enterprises.

1.1 Big data

The modern network social mode accelerates the interaction of data. Under the background of the continuous development of big data and artificial intelligence technology, the ability to collect and process data has become one of the core competitiveness of enterprises. A good data management mode can also help enterprises to achieve more information resources, and win more opportunities in the industry competition, so as to obtain more benefits. The standard definition of big data by scholars in recent years is to search and make decisions based on massive data sets, and the data that can be used for analysis is the internal data of big data. The key to big data is not the massive data set, but the method to analyze the data [1, 2]. At present, big data has penetrated into the development and analysis of all industries, for example, the medical industry records the personal diagnostic data of patients with different diseases. Through comparative analysis and decision-making with the diagnostic data of other historical cases, a third-party reference is provided for the treatment of current patients, thereby avoiding misjudgment and misdiagnosis. The current development trend of big data forecast by various institutions is shown in Fig. 1.

Figure 1.

The development trend of big data.

1.2 Artificial intelligence

Artificial intelligence technology has entered a stage of rapid development, which mainly has three characteristics. The first notable feature of artificial intelligence is that the main difference from other machines and related products is that artificial intelligence has certain human intelligence-related algorithms, data and basic hardware, enabling the realization of the high-tech nature of artificial intelligence. The soul of smart technology. Because of the intelligence of artificial intelligence and the efficiency of coding operations, the work efficiency of artificial intelligence is generally higher than that of humans [3]. For example, expressive reasoning ability, semantic understanding ability, sentiment analysis ability, etc., these are all difficult problems that must be improved and strengthened in the development of artificial intelligence, and the solution of these problems will push artificial intelligence to a higher level. Since artificial intelligence is controlled by programming settings, etc., the efficiency of artificial intelligence will run at a high speed according to the programming settings. The second notable feature of artificial intelligence is that its autonomous learning is different from the design and function of other products, and it needs to be completely upgraded through human instructions and continuous updating of the system [4]. In the case of artificial intelligence based on basic data, through deep learning, autonomous learning and other algorithms, it constantly adapts and grows. Although artificial intelligence technology cannot currently think about problems like humans, it has the ability to learn, and the realization of its intelligence relies on a large number of Data and learning may also often be wrong at first, but it can learn from it, which ensures that artificial intelligence can deal with more complex situations [5, 6]. The third notable feature of the development of artificial intelligence is that its related application products have a subversive impact on current life. At present, artificial intelligence application systems have made progress in industries such as heavy industry, communication, scientific discovery and entertainment. Application systems in many aspects are the most direct production tools and greatly improve production efficiency. At the same time, in human social life, the application of artificial intelligence will also change or even subvert people’s way of life. For example, Tesla’s different levels of autonomous driving AI systems, Ecovacs’ sweeping robots, etc., many artificial intelligence products have shown a huge impact and influence on traditional production and life.

1.3 Transmission lines

In January 2022, Chen Jiangyuan published ‘Research on Power Design Technology in Smart Grid’, proposing smart grid and its advantages, analyzing the performance of smart grid, and analyzing and discussing the power design technology in smart grid. In April of the same year, Liu Fei published “Discussion on the application of digital technology in power engineering design”. This paper expounds the improvement of engineering design drawing effect by means of digital technology, and puts forward the concept of intelligent electronic design. Overhead and cable power transmission are the most common power transmission methods. Among them, cable power transmission has the risk of being accidentally damaged by natural disasters and man-made malicious damage, while the overhead method can avoid natural damage to the greatest extent, and minimize the intersection of lines and human daily life. The line warranty process will also be smoother [7]. The current transmission mode used in the electrical design of transmission lines is mainly carried out in an overhead way. The electrical design of transmission lines is related to people’s electricity consumption and personal safety issues, and the degree of stability required is also extremely high. The power is maintained by the high voltage of the line. The laying of most transmission lines is relatively poor. Due to the breadth of the spanning area, power transmission is usually arranged in high-risk areas such as mountains, cliffs, and rivers, which makes the construction of transmission line projects exist in the environment [8]. The predicament of poor, high requirements, time-consuming and high investment, while further increasing the complexity of the transmission line design stage, especially the need to comprehensively design the convenience of the later maintenance of the line, consider all possible problems, and arrange a reasonable plan.

The audience of this article is the power companies, to enhance the power supply stability and power supply efficiency services. With the gradual development of computer computing towards the mode of human-like thinking, the application of data processing and intelligent processing technology to the electrical design of transmission lines has become the trend of current scholars’ research. The combination of new technologies can avoid personal involvement in the electrical design of transmission lines. The existing ill-considered problems can also be used as an auxiliary tool to help designers make some decisions and make the electrical design of transmission lines more complete.

Based on the premise of the previous article, this paper applies big data technology and artificial intelligence technology to power design, constructs intelligent design mode, solves the problems existing in the existing power design, so as to improve the stability and continuity of power supply, and better meet the needs of people’s production and life.

2. Questionnaire survey and analysis

In order to analyze the current situation of transmission line electrical design and the development prospect of intelligent circuit design, the author conducted a questionnaire survey on 300 transmission line electrical design professionals and practitioners from different enterprises. The content of the questionnaire on the one hand is the current line electrical design of the line path layout, line tower type matching, safety protection measures, design and other issues. On the other hand, it is the suggestion of these practitioners to improve power design. A total of 600 questionnaires were distributed and 598 questionnaires were recovered. The recovery rate met the standard requirements. Among them, the design of the transmission path needs to be completed in combination with the actual environmental changes [9]. The line design is closely related to the later construction and maintenance. The data about the transmission line path in this questionnaire survey are shown in Table 1.

Table 1
Design of transmission line paths

Num	Crossover issues with other lines	Comprehensive consideration of construction weather	Project error rate
1	NO	NO	0.69
2	NO	NO	0.73
3	NO	NO	0.78

The compression resistance and stability of the transmission tower type are two of the foundations that ensure the long-term operation of the line. The data about the tower type matching situation in this questionnaire survey is shown in Table 2.

Table 2

Transmission tower type matching degree

Num	Transmission project	Tower material rationality	Late stability
1	A	0.16	0.13
2	B	0.19	0.15
3	C	0.26	0.21

High-voltage transmission lines are high-risk affairs for human beings, and their safety design is extremely important. The data about lightning protection safety design of transmission lines in this questionnaire survey is shown in Table 3.

Table 3

Lightning protection safety design of transmission lines

Num	Transmission project	Lightning resistance	Lightning strike safety incident rate
1	A	0.12	0.63
2	B	0.13	0.71
3	C	0.18	0.78

In the extremely cold north, the line antifreeze design is also the focus of the electrical design of the transmission line. The data about antifreeze design of transmission lines in this questionnaire survey is shown in Table 4.

Table 4

Antifreeze design of transmission lines

Num	Transmission project	Antifreeze rate	Frozen safety incident rate
1	A	0.17	0.68
2	B	0.14	0.72
3	C	0.12	0.85

The key to the questionnaire survey is whether the entire survey process is in a valid state. Based on the reliability and validity theory, the data of this questionnaire is comprehensively counted and the reliability and validity of the entire questionnaire are calculated as shown in Table 5.

Table 5

Reliability and validity analysis

	Reliability	Validity
Value	Alpha $=$ 0.82	KMO $=$ 0.93

By further comparing with the standard reference value of reliability and validity theory, it is found that the data of this questionnaire conforms to the credible and effective standards, so it is determined that this transmission line electrical design questionnaire is an effective investigation.

3. The current dilemma of electrical design of transmission lines

3.1 Unreasonable route arrangement

The path design in the electrical design of the transmission line needs to comprehensively consider the resources, climate, temperature and humidity changes, geography and subsequent human activities of the transmission line. In the case of ensuring the convenience of the later construction, it is also necessary to ensure the convenience of the later line due to unexpected maintenance [10, 11]. By summarizing the questionnaire data, it can be found that due to the lack of understanding of the environment that the transmission line passes through, the electrical designers of the current transmission line cannot guarantee an effective and reasonable route arrangement. A big obstacle, thus forming a vicious cycle. Especially in the process of making construction drawings of transmission lines, due to the lack of real understanding of environmental information, most of the design drawings have great errors [12].

3.2 The model of the line support tower is unreasonable

Through the analysis of the questionnaire data of the electrical designer of the transmission line, it is found that the current transmission line designer’s choice of support towers has a low degree of matching with the actual transmission project demand, resulting in poor design effect, difficulty in later construction, and instability of the transmission line. In most cases, the transmission line is carried on overhead, and the pole tower plays the role of supporting the line in the process [13]. The type of the support tower is related to the height of the line. After the current transmission line is designed, there will always be straight lines because the line passes through the hillside continuously. When it is delivered to the construction team, the line construction personnel also need to adjust the design content according to the environment, which will cause a large deviation between the entire project and the design, which will eventually lead to more problems in the later stage of the transmission project and more maintenance times, the maintenance difficulty is also high.

3.3 Insufficient consideration of safety protection design

Transmission lines often involve a wide area, and the environment is the key point that affects the safety of the line. It is also considered as the main parameter in the electrical design of the transmission line. Through questionnaires and interviews, it is found that the current design of transmission lines generally has insufficient consideration of lightning protection and anti-freezing. Because the high voltage of transmission lines is harmful to the human body, they are often laid away from gathering buildings, but this is easy to cause the lines to be affected by lightning. In some alpine areas, lines are also easily affected by freezing weather [14]. These are due to the design omissions of transmission line designers who are unfamiliar with the line environment. Under normal circumstances, citizens’ electricity consumption may be affected. In some extreme cases, short circuits and fires may occur. A situation where the sway angle of the tower pole exceeds a predetermined limit may lead to a problem that the distance between the line and the footpegs supporting the tower is no longer safe. In addition, the corner design of the commonly used support towers is mostly set to 0 ${}^{\circ}$ , but when the line operation is actually carried out according to the design drawings, there are often obstacles in the construction environment, so the tower cannot complete the design of the 0 ${}^{\circ}$ angle, which is also different from the tower type. The choice is highly correlated, a situation that is mostly ignored by current transmission line designers.

4. Circuit electrical design strategy based on big data and artificial intelligence

To solve the problems of circuit transportation efficiency and instability, in theory, we can adopt the intelligent arrangement of big data technology and the tower intelligent matching intelligent security strategy of the combination of big data and AI technology. Big data and artificial intelligence are new technologies, which have advantages in intelligent operation, analysis and decision-making. The application of big data and artificial intelligence technology to the process of power design plays a theoretical role in solving the dilemma of power design.

4.1 Intelligent arrangement of route routes combined with big data technology

With the advent of non-relational databases, data science has gradually become the focus of attention in academia and engineering. The data generated by human social networking is also gradually increasing, and big data technology appears in this context. Its main purpose is to obtain key information from complex data sets and realize the role of comprehensive analysis. In view of the unreasonable arrangement of the current transmission line routing, the Hadoop tool in the big data technology combined with the crawler technology can obtain all the data of the transmission project on the line routing from social media and search engines, and obtain it according to the data analysis rules defined by the designer [15, 16, 17]. Data such as geography, temperature, humidity, and climate near the line are combined with drawing tools such as CAD and 3DMAX to intelligently draw the best path for the transmission line, thereby solving the problem of unreasonable transmission line design [18, 19]. The big data algorithm formulas used are shown in Eqs (1)–(4).

$\displaystyle X({\delta\leqslant\eta_{0}\ast RT})=QE-QE^{-T_{0}/OP}$ (1) $\displaystyle\textit{QYR}=WL-\frac{EW_{9}}{TQ+RQ_{2}}\times\textit{Data}$ (2)

The formula of big data in the processing of questionnaire data is as follows:

$\displaystyle{W}=\tau+\frac{\frac{\sum\limits_{i=1}^{N}{V_{i}}}{2}-{D}_{{e}-1}% }{C{z}}\times\Phi$ (3) $\displaystyle QA=\frac{FD_{1}G_{1}+P_{2}O_{2}+\cdots+FJL_{k}}{GD_{1}+GD_{2}+% \cdots+GD_{k}}=CX\tau\zeta$ (4)

Equations (1)-(4) are Structural Equation Models. After a second interview with the respondents of the questionnaire, it was found that after the adoption of big data technology, the designed transmission line was more reasonable, and the later maintenance rate and cost of the transmission line were also reduced. The specific situation is shown in Figs 2 and 3.

Figure 2.

Changes in the rationality of transmission line design.

Figure 3.

Changes in the later maintenance costs of transmission lines.

In summary, big data and artificial intelligence play a significant role in enhancing the intelligence of power grid design.

4.2 Tower type intelligent matching combining big data and AI technology

For the mismatch of supporting towers, it can be solved by combining the intelligent processing capabilities of big data technology and AI algorithms [20, 21]. For example, if the rocking angle of the support tower exceeds the predetermined limit, big data technology can be combined to design parameters such as vertical and horizontal spans, insulator strings, insulator wind pressure, wire cross-sectional area, wire wind pressure specific load, wire self-weight and rocking angle [22, 23]. Compare with the historical design success case data, and use the AI algorithm to comprehensively calculate the gap between parameters, design intelligent identification rules according to the swing angle safety limit value, increase the allowable value in combination with the value in the historical success case data of the electrical design of the transmission line, reduce the design angle value or increase the weight seat. In addition, when the angle of the supporting tower is required, the combination of AI and big data technology can intelligently determine the requirements of the supporting tower and air gap during design, and match other types of towers if necessary to solve the problems existing in the line design of the transmission project [24, 25]. The above is just an enumeration of common problems of tower type in transmission line design. In fact, after combining big data and AI technology, other aspects of tower type matching can be further improved [26, 27]. After a second interview with the survey respondents, it was found that after using big data and AI technology, the tower design was more reasonable and the degree of matching became higher. The specific situation is shown in Fig. 4.

Figure 4.

Tower type matching degree change.

Figure 5.

Changes in the incidence of security incidents.

4.3 Intelligent security protection strategy

The intelligent analysis capabilities of big data and AI technology can provide solutions for the shortcomings of current transmission line safety design [28, 29]. For example, big data technology can obtain the historical weather conditions of the line, analyze the needs of safety design in combination with the historical data of local lightning strikes and extreme icy weather, and mark it in the drawing tool with a special color to reduce the risk of electric leakage in the later line, and after using AI technology to search for news about lightning strikes around the line, you can summarize the lightning reporting section where the line passes, and use lightning protection lines in this section [30, 31]. The cable is laid overhead, other monitoring equipment is installed, and the outermost layer is coated with an insulating layer for reinforcement to ensure the overall cleaning safety of the line, thereby avoiding the risks caused by lightning and freezing [32, 33]. After a second visit to the questionnaire respondents, it was found that after the adoption of big data and AI technology, the safety protection design was more complete, and the probability of electricity safety incidents caused by lightning strikes and freezing was less [34, 35]. The specific situation is shown in Fig. 5.

5. Conclusion

This paper compares the traditional power design mode with the intelligent design mode supported by big data and artificial intelligence technology. Through comparison, it is concluded that the intelligent design mode has significant advantages in solving the problems of unreasonable line path layout, unreasonable line support tower type and insufficient consideration of safety protection design. It plays an important role in improving power supply efficiency, stability, and continuity. There are many steps involved in the electrical design of transmission lines, and there are many things to consider. At this time, there will be many problems. Effective technical solutions can solve the problems from the root cause, so as to avoid the subsequent line operation process. The safety and maintenance problems that arise also save more costs for power companies. In order to completely solve the existing problems in the electrical design of transmission lines, this paper introduces big data and artificial intelligence technology as an aid, and designs intelligent site selection, intelligent tower selection and intelligent safety strategies for the existing problems. The performance of the electrical design of transmission lines improved by big data and artificial intelligence technology is better than that of traditional design methods.

Footnotes

Fund

Shenzhen Power Supply Bureau Technology Project (No. 090000KK52190178).

References

Yang

Kang

Hou

. Research on state perception method of electrical equipment in substation. J Artif Intell Pract. 2021; 1(1): 46-51.

Kai

. AI technology for real-time control of FA equipment develop by Mitsubishi electric and AIST. Acquis Partnership; 2021.

Song

Zhang

. Research on automatic control technology of low voltage electrical equipment based on artificial intelligence. Adult Higher Edu. 2021; 3(3): 113-116.

Chen

Yang

. Electrical automation control technology of electromechanical equipment based on artificial intelligence technology. In: 3rd International Conference on Computer Science, Electronics and Engineering Management (CSEEM 2020); 2020.

Lai

C-F

Chien

W-C

Yang

Qiang

. LSTM and edge computing for big data feature recognition of industrial electrical equipment. IEEE Trans Ind Inf. 2019; 15(4): 2469-2477.

Miao

Zhang

Chen

. Two-level fault diagnosis of SF6 electrical equipment based on big data analysis. Big Data Cognit Comput. 2019; 3(1): 4.

Gong

. Research on electrical equipment intelligent detection device based on big data and Internet of Things. Electr Auto. 2020; 42(5): 109-111+118.

. Intelligent analysis of big data for the preventing of external force destruction on high-voltage transmission Lines. J Phys: Conf Ser. 2020; 1673: 012018.

Jung

S-H

Huh

J-H

. A novel on transmission line tower big data analysis model using altered k-means and ADQL. Sustainability. 2019; 11(13): 3499.

10.

Zeng

Luo

Wang

Huang

Liang

Sun

Lin

. Fast image recognition of transmission tower based on big data. Prot Control Mod Power Syst. 2018; 3: 15.

11.

Yan

Sheng

Qiu

Jiang

. Big data modeling and analysis for power transmission equipment. A novel random matrix theoretical approach. IEEE Access. 2018; 6: 7148-7156.

12.

Perçuku

Minkovska

Stoyanova

. Big data and time series use in short term load forecasting in power transmission system. Proc Comput Sci. 2018; 141: 167-174.

13.

Perçuku

Minkovska

Stoyanova

. Modeling and processing big data of power transmission grid substation using Neo4j. Proc Comput Sci. 2017; 113: 9-16.

14.

Wang

. Exploration on electrical design problems and improvement countermeasures of high-voltage transmission lines. Electr Power Equipment Manage. 2021; (9): 71-72+74.

15.

. Research on electrical design technology of transmission lines. Lamps Light. 2021; (8): 129-131.

16.

Liu

. Problems in electrical design of high-voltage transmission lines and suggestions for improvement. Electrical Equip Economy. 2020; (6): 15-16+19.

17.

Sun

. Analysis of problems and countermeasures in electrical design of high-voltage transmission lines. Electr Technol Software Eng. 2020; (23): 208-209.

18.

Liu

. Analysis of problems and measures of electrical design of high-voltage transmission lines. Intell City. 2020; 6(22): 75-76.

19.

Huang

. High-voltage line protection in electrical operation. Power Equip Manage. 2020; (6): 61-62.

20.

Xiao

. Analysis of common problems and solutions in electrical design of high-voltage transmission lines. Comput Knowl Technol. 2020; 16(16): 231-232.

21.

Zhang

. Research on the electrical design of high-voltage transmission lines. Low Carbon World. 2020; 10(5): 57+59.

22.

. Electrical design problems and perfect countermeasures of high-voltage transmission lines. Urban Constr Theory Res (Electr Ed). 2020; (14): 6-7.

23.

Sun

. Development of electrical equipment and technology in hydropower stations. Northwest Hydropower. 2020; (2): 23-25+31.

24.

Wang

Li.

,Discussion on problems and countermeasures in electrical design of high-voltage transmission lines, Commun World, 2019,; 26(10): 229-230.

25.

Sheng

Qian

Luo

Song

Liu

Jiang

. Key technologies for operation and maintenance of power equipment for new power systems and their application prospects. High Voltage Technol. 2021; 47(9): 3072-3084.

26.

Chen

Tang

Huang

Yuan

Jiang

. Exploration of multi-disciplinary cross-integration talent training mode in transmission line engineering. China Electr Power Edu. 2021; (8): 74-75.

27.

. The application of artificial intelligence in the safe operation of transmission lines. Heilongjiang Sci. 2021; 12(6): 100-101.

28.

. Practical teaching reform of transmission line engineering specialty. China Electr Power Edu. 2019; (10): 58-59.

29.

Zhu

Huo

. Discussion on LineStat emergency early warning mode of power transmission network under the background of big data. Electr Appl. 2015; 34(S1): 565-569.

30.

Liu

. Explore the application of digital technology in power engineering design. Inf Technol. 2022; 39(7): 1-11.

31.

. Application of digital technology in power engineering design. Digital Technol Appl. 2021; 39(11): 112-114.

32.

Zhu

Fang

. Application of digital technology in power engineering design. Light Source Light. 2021; (5): 131-132.

33.

. Application of digital control technology in safety management of power engineering construction. China Electr Power. 2021; (3): 82-83.

34.

. Application of three-dimensional digital transfer technology in chemical engineering design. Eng Constr Des. 2020; (24): 240-241.

35.

. Application of three-dimensional digital transfer technology in chemical engineering design. Contemp Chem Res. 2019; (1): 43-44.

Electrical design problems and improvement countermeasures of transmission lines under the background of big data and artificial intelligence

Abstract

Keywords

1. Introduction

1.1 Big data

1.3 Transmission lines

2. Questionnaire survey and analysis

Table 1 Design of transmission line paths

3.1 Unreasonable route arrangement

3.2 The model of the line support tower is unreasonable

3.3 Insufficient consideration of safety protection design

4. Circuit electrical design strategy based on big data and artificial intelligence

4.1 Intelligent arrangement of route routes combined with big data technology

5. Conclusion

Footnotes

Fund

References

Table 1
Design of transmission line paths