scholarly journals Research on Identification and Measurement Methods of Influencing Factors of Investment in Operation and Maintenance

2021 ◽  
Vol 236 ◽  
pp. 04010
Author(s):  
Ma Lin ◽  
Tong Ruigang ◽  
Ren Yan ◽  
Zhao Lei ◽  
Sun Xizhen
Keyword(s):  
Influencing Factors ◽  
Capital Expenditure ◽  
Power Grid ◽  
Influencing Factor ◽  
Fish Bone ◽  
Current Status ◽  
Operating Pressure ◽  
Equipment Operation ◽  
Electricity Cost ◽  
Operation And Maintenance

Operation and maintenance investment is an important part of the capital expenditure of power grid enterprises. In recent years, affected by multiple profit-cutting factors such as the macroeconomic downturn, the slowdown in electricity growth, the implementation of transmission and distribution price reform requirements, the narrowing of electricity price space, and the state's phased reduction of electricity cost policies, the profitability of power grid companies has dropped significantly, and power grid investment. The capacity was significantly weakened, and the operating pressure was unprecedented. Identifying and measuring the influencing factors of power grid operation and maintenance investment is an important supporting role for enterprises to formulate scientific and reasonable investment strategies for power grid equipment operation and maintenance. Therefore, this paper first applies the fish-bone method, combined with the current status of equipment operation and maintenance management of power grid enterprises, and scientifically identifies the factors that affect the investment level of operation and maintenance; then, based on the grey correlation theory, analyzes the degree of influence of each influencing factor.

scholarly journals Research on operation and maintenance cost of power grid equipment based on standard operation-taking 220kV transformer substation as an example

2021 ◽  
Vol 292 ◽  
pp. 01005
Author(s):  
Xuefei Zhang ◽  
Zhiwei Li ◽  
Chengzhi Wang ◽  
Xuejun Tang ◽  
Sen Yang
Keyword(s):  
Cost Management ◽  
Power Grid ◽  
Maintenance Cost ◽  
Cost Calculation ◽  
Operating Pressure ◽  
Operation And Maintenance ◽  
Grid Operation ◽  
The Cost ◽  
Operation And Maintenance Cost ◽  
Power Grid Enterprise

In view of the inadequate implementation of the grid operation and maintenance standards and specifications current, the lack of planning in cost usage, and the inability to achieve single equipment collection of costs, taking 220kV substation as an example, this paper proposes a single asset operation and maintenance cost calculation method based on grid standard operations, and puts forward suggestions on the cost management of grid equipment operation and maintenance. Through verification and analysis with the relevant provisions of the cost supervision and examination method, the power grid company will face greater operating pressure, and the cost management level needs to be further improved. Through the calculation of the operation and maintenance cost of a single asset, it provides a reference basis for the distribution of the operation and maintenance cost of the power grid enterprise, and at the same time provides a reasonable explanation for the power grid enterprise to adapt to the cost supervision and review of the transportation dispatching pricing.

scholarly journals Application of Augmented Reality (AR) Technology in Power Grid Emergency Training

2021 ◽  
Vol 2074 (1) ◽  
pp. 012095
Author(s):  
Qishen Pan ◽  
Min Zhang ◽  
Haichang Zhou
Keyword(s):  
Augmented Reality ◽  
Integrated Management ◽  
Power Grid ◽  
Auxiliary Information ◽  
Holographic Display ◽  
Equipment Operation ◽  
Emergency Training ◽  
Operation And Maintenance ◽  
Augmented Reality Technology ◽  
Substation Equipment

Abstract Strong reality has been applied to training operations, and the use of virtual and augmented reality in aerospace, manufacturing and shipbuilding industries has yielded significant results. This paper mainly studies the application of Augmented Reality (AR) technology in power grid emergency training. This paper designs and implements an intelligent operation and maintenance system based on mobile augmented reality under the Android operating system. Augmented reality technology is applied to substation equipment operation and maintenance. Through the design and development of modules such as data management, equipment identification, holographic display of equipment information, integrated management and remote assistance, the application of Augmented Reality technology in substation equipment operation and maintenance is realized. Based on augmented reality and identification technology, the auxiliary information is transmitted to the intelligent terminal display of field operators in real time to assist the power grid emergency training and improve efficiency.

scholarly journals Grey Relational Grade Based Quantitative Analysis of the Factors Influencing the Load Characteristics of A Power Grid

2018 ◽  
Vol 53 ◽  
pp. 01012 ◽  
Author(s):  
Wei Pan ◽  
Caijia Lei ◽  
Wei Jia ◽  
Hui Gao ◽  
Binghua Fang
Keyword(s):  
Quantitative Analysis ◽  
Influencing Factors ◽  
Power Grid ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Affecting ◽  
Grey Relational Grade ◽  
Load Characteristics ◽  
Grey Relational ◽  
Main Factor

Regarding analysis of load characteristics of a power grid, there are multiple factors that influence the variation of load characteristics. Among these factors, the influence of different ones on the change of load characteristic is somewhat different, thus the degree of influence of various factors needs to be quantified to distinguish the main and minor factors of load characteristics. Based on this, the grey relational analysis in the grey system theory is employed as the basis of mathematical model in this paper. Firstly, the main factors affecting the load characteristics of a power grid are analysed. Then, the principle of quantitative analysis of the influencing factors by using grey relational grade is introduced. Lastly, the load of Guangzhou power grid is selected as the research object, thereby the main factor of temperature affecting the load characteristics is quantitatively analysed, such that the correlation between temperature and load is established. In this paper, by investigating the influencing factors and the degree of influence of load characteristics, the law of load characteristics changes can be effectively revealed, which is of great significance for power system planning and dispatching operation.

scholarly journals Extracting relationship between air pollution and precipitation using spatio-temporal analysis in Tehran metropolis

2019 ◽  
Vol 2 ◽  
pp. 1-7
Author(s):  
Shokouh Dareshiri ◽  
Mohammadreza Sahelgozin ◽  
Maryam Lotfian ◽  
Jens Ingensand
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Regression Model ◽  
Influencing Factors ◽  
Polynomial Regression ◽  
Human Life ◽  
Pearson Correlation ◽  
Influencing Factor ◽  
Polynomial Equation ◽  
Temporal Analysis

<p><strong>Abstract.</strong> Precipitation is one of the main stages of the water cycle, and it is required for the organisms to survive on the planet. In contrast, air pollution is a phenomenon that has greatly affected the human life nowadays. Population growth, development of factories and increasing number of fossil fuel vehicles are the most influencing factors on air pollution. In addition to understand nature of precipitation and air pollution, finding relationship between these two phenomena is necessary to make appropriate policies for reducing air pollution. Furthermore, studying trends of precipitation and air pollution in the past, is helpful to forecast the times and places with less precipitation and more air pollution for a better urban management. In this study, we tried to extract any probable relationship between these two parameters by investigating their monthly measured amounts in 22 municipal districts of Tehran in three epochs of time (2009, 2013 and 2017). Carbon Monoxide (CO) was considered as the indicator of air pollution. Results of the study show that the parameters have a significant relationship with each other. By using Pearson Correlation Coefficient and One-Way Variance (ANOVA) test, relationship between the data for each month and for each district of Tehran were studied separately. As the time has passed and the air pollution has increased, the correlation between the parameters in districts has decreased. In addition, during the cold months of the year, the correlations decrease since the fact that precipitation is not the only influencing factor on the air pollution due to the rise of air “Inversion”. Finally, the polynomial regression model of carbon monoxide based on precipitation was extracted for each of the three years. The model suggests a degree three polynomial equation. The obtained coefficients from the regression model show that the relationship between parameters was stronger in the years with more rainfalls. This can be due to the more significant impact of other influencing factors on air pollution, such as population density, wind direction, vehicles and factories in the areas or conditions with a less rainfall.</p>

Analysis of Operation of AVC System in Fuzhou Power Grid

2014 ◽  
Vol 1061-1062 ◽  
pp. 1013-1016
Author(s):  
Jun Jie Xiong ◽  
Wei He ◽  
Hao He
Keyword(s):  
Success Rate ◽  
Closed Loop ◽  
Power Grid ◽  
Value Management ◽  
Operation And Maintenance ◽  
Equipment Availability

Through the statistics of AVC system equipment availability, closed loop rate, action number and success rate, analyses the operation of AVC system in Fuzhou power grid, there are still many problems, such as closed loop rate is not high, some AVC substation remote low success rate.In order to effectively improve the pertinent measures from the design, operation and maintenance, fixed value management etc..

scholarly journals Analysis of Revenue Incentive Dynamic Mechanism of Financial Supply Chain from the Perspective of the Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yue Yin
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
Influencing Factors ◽  
Incentive Mechanism ◽  
Influencing Factor ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
The Incentive Mechanism ◽  
Relationship Factors ◽  
The Internet Of Things

With the rapid development of society, all walks of life need the support of the Internet of Things, and the financial industry is no exception. This article integrates blockchain technology with supply chain finance and builds a supply chain financial alliance architecture based on blockchain technology and an underlying model of the Ethereum blockchain system suitable for supply chain finance. We innovated new supply chain finance models and operating mechanisms and proposed business scenarios for supply chain finance from the perspective of blockchain. Taking into account the actual operation of the blockchain supply chain financial platform, the principal-agent model and the incentive theory are applied, and the supply chain financial accounts receivable model is taken as an example in the case of complete information and incomplete information. The incentive mechanism between the service provider of the chain supply chain financial platform and the core enterprise promotes the better implementation of blockchain technology and supply chain finance. Based on the existing theoretical research, this paper identifies the key influencing factors of the supply chain’s cross-enterprise incentive mechanism. These influencing factors system includes two dimensions: transaction factors and relationship factors. Transaction factors include resource dependence, uncertainty, and cooperation experience; relationship factors include corporate reputation, trust level, and relationship commitment. Based on the nature of the incentive mechanism, information sharing and revenue sharing are extracted as the measurement dimensions of the supply chain’s cross-enterprise incentive mechanism. On this basis, this article draws on the existing enterprise life cycle division method and constructs a hypothetical model of the influencing factors of the incentive mechanism in the incubation period, the growth period, and the maturity period. Relevant data was collected through questionnaires, and SPSS and AMOS software were used to perform statistical analysis, reliability analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation hypothesis testing on the data. The performance of each influencing factor in different stages of the enterprise’s life cycle and the importance of each influencing factor in the same life cycle stage are obtained.

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